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An examination of contemporary challenges in deceased donor kidney allocation Rose, Caren Lee 2014

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     AN EXAMINATION OF CONTEMPORARY CHALLENGES IN DECEASED DONOR KIDNEY ALLOCATION  by  Caren Lee Rose  MSc, Dalhousie University, 2003 BSc, University of British Columbia, 2000    A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY   in   THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES  (Health Care and Epidemiology)   THE UNIVERSITY OF BRITISH COLUMBIA  (Vancouver)  October 2014   © Caren Lee Rose, 2014   ii  Abstract Transplantation is the preferred treatment for patients with kidney failure, but the need for transplantation exceeds the organ supply. Strategies to address the organ shortage include: preventing end-organ failure, increasing the number of deceased donor kidneys (DDK) for transplantation, and ensuring appropriate allocation to avoid organ waste. This thesis: develops an improved metric for deceased donation activity; describes an age-matching allocation strategy to reduce organ waste; and examines the impact of selected wait-list policies on disparities in access to DDK transplantation.  Using national administrative databases, we: Estimated and validated the number of potential deceased organ donors among in-hospital deaths using diagnostic codes; Calculated differences in DDK and transplant candidate survival by age using Cox regression to determine the area between survival curves (ABSC), and combined these measures with information on DDK and candidate ages to define age cut-points for DDK allocation; Described the use and outcomes of older DDKs (≥ 65 years) in countries with different allocation systems using Cox regression and ABSC, and identified patients that achieved a lifetime of transplant function from older DDKs; and Examined longitudinal use and outcomes of wait-listing candidates at multiple transplant centres using logistic and Cox regression.  Three percent of Canadians who die in-hospital were identified as potential organ donors, suggesting significant potential to increase deceased donation. We determined DDK and  iii  candidate age cut-points for Canadian allocation, and estimated that implementation of these cut-points could have eliminated 500 years of wasted donor kidney function, and prevented 800 years of post-transplant dialysis compared to the current allocation strategy. We found that older DDKs provided a lifetime of kidney function for patients aged >60 years, suggesting targeted use of these organs could safely increase transplantation. Finally, we determined that multiple wait-listing helped minimize geographic disparities in accessing transplantation and may be an important policy consideration in countries that do not currently allow multiple listing.  As transplantation wait-lists grow at unprecedented rates, the potential to increase deceased donation, implement allocation policies to decrease organ wastage, safely expand the use of older deceased donors and promulgate wait-list policies to increase access to transplantation will become more important.     iv  Preface This statement is to certify that the work in this thesis was conceived, conducted and written by Caren Rose. Ethics approval was granted from the University of British Columbia Research Ethics Board (UBC REB # H09-02915-A002). Caren Rose was entirely responsible for Chapters 1,3,4, and 9. A version of Chapter 2 has been submitted for publication and is awaiting revisions. The manuscript is entitled: ‘Estimating the number of potential deceased donors in Canada’; Caren Rose, Peter Nickerson and John Gill. Caren Rose was responsible for the study design, data access, data analysis, writing and revising the manuscript. Dr. Gill assisted in the study design and revisions of the manuscript. Dr Nickerson approved the study design, assisted in data access and edited the manuscript. The findings of Chapter 2 were presented at the Canadian Society of Nephrology annual general meeting in Vancouver April 2014. The findings of Chapters 5 and 6 have been written up and presented to the Canadian Kidney Working Group as policy recommendations for the allocation of deceased donor kidneys by age matching.  A version of Chapter 7 has been submitted for publication. The manuscript is entitled: ‘Lifetime of allograft function- a new metric to inform the use of expanded criteria donor  v  transplantation’; Caren Rose, Elke Schaeffer, Jagbir Gill, Ulrich Frei and John Gill. Caren Rose was responsible for the study design, data analysis, writing and revising the manuscript. Dr John Gill assisted in the study design, writing and revisions of the manuscript. Dr Schaeffer and Dr Frei provided access to Eurotransplant data and edited the manuscript. Dr Jagbir Gill edited the manuscript. A version of Chapter 8 was presented at the World Transplant Congress in San Francisco in July 2014. The project is entitled: ‘Multiple wait-listing’; Caren Rose, John Gill. Caren Rose was responsible for the study design, data analysis, writing and revising the manuscript. Dr Gill participated in designing the study, and revising the manuscript.  Dr Joel Singer and Dr Jacek Kopec provided epidemiologic input and editing of all chapters.     vi  Table of contents Abstract ........................................................................................................... ii Preface ............................................................................................................ iv Table of contents ............................................................................................. vi List of tables ................................................................................................... ix List of figures .................................................................................................. xi Abbreviations ............................................................................................... xiii Acknowledgements....................................................................................... xiv Dedication ...................................................................................................... xv 1 Introduction ................................................................................................ 1 1.1 The epidemiology of end-stage renal disease .........................................................1 1.1.1 Renal replacement therapies .............................................................................2 1.1.2 Supply of organs ...............................................................................................4 1.2 Allocation of kidneys for transplantation ...............................................................8 1.2.1 Ethical considerations for allocation: utility and justice ..................................9 1.3 Outstanding questions and study justification ......................................................11 1.3.1 Challenges in allocation .................................................................................11 1.3.2 Recipient and deceased donor kidney life expectancies .................................12 1.3.3 The problem with age matching- introduction of inequities in access to transplantation ............................................................................................13 1.3.4 Attitudes about deceased donor kidney allocation .........................................15 1.3.5 Regional disparities in access to transplantation ............................................17 1.3.6 Summary.........................................................................................................19 1.4 Research hypotheses and study questions ............................................................20 1.5 Outline of thesis ....................................................................................................21 2 Estimating the number of potential deceased organ donors ..................... 24 2.1 Introduction ...........................................................................................................24 2.2 Methods ................................................................................................................25 2.2.1 Identification of potential donors ...................................................................26 2.2.2 Accuracy of the study method estimates ........................................................27 2.2.3 Conversion of potential donors to actual donors ............................................27 2.3 Results...................................................................................................................28 2.3.1 Accuracy of the study method estimates ........................................................29 2.3.2 Conversion of potential donors to actual donors ............................................29 2.4 Interpretation .........................................................................................................30 3 The ethics of deceased donor kidney allocation ....................................... 39 3.1 Principles ..............................................................................................................39 3.1.1 Justice .............................................................................................................40 3.1.2 Utility ..............................................................................................................41 3.2 Examining utility through different lenses ...........................................................43  vii  3.3 Transplant candidates ...........................................................................................43 3.3.1 Likelihood of accessing transplantation .........................................................44 3.3.2 Life expectancy after transplantation .............................................................45 3.3.3 Quality of life .................................................................................................46 3.4 Summary ...............................................................................................................50 4 The allocation of deceased donor kidneys for transplantation ................. 52 4.1 Overview ...............................................................................................................52 4.2 Eurotransplant Senior Program .............................................................................54 4.3 Changing a deceased donor kidney allocation system- An American narrative ................................................................................................................55 4.3.1 Allocation prior to 2014 .................................................................................55 4.3.2 Need for change ..............................................................................................57 4.3.3 Kidney allocation score ..................................................................................58 4.3.4 2011 Proposed national allocation policy.......................................................65 4.3.5 American allocation summary ........................................................................67 4.4 Summary ...............................................................................................................67 5 The type and quantity of inefficiency in donor-candidate age matching: measuring the area between the curves ................................... 69 5.1 Introduction ...........................................................................................................69 5.2 Methods ................................................................................................................72 5.2.1 Study population and data source ...................................................................72 5.2.2 Analytical methods .........................................................................................73 5.3 Results...................................................................................................................76 5.3.1 Summative utility ...........................................................................................77 5.4 Interpretation .........................................................................................................78 6 Defining equitable-based utility cut-points for donor-candidate age matching ................................................................................................... 89 6.1 Introduction ...........................................................................................................89 6.1.1 Deceased donor kidney and candidate ages ...................................................89 6.1.2 Considerations for allocation by donor and candidate age matching .............92 6.1.3 The Canadian perspective ...............................................................................95 6.2 Definitions ............................................................................................................96 6.2.1 Nominal definitions of young and old ............................................................96 6.2.2 Operational definitions of young and old .......................................................97 6.2.3 Quantifying ages of donors and candidates for age matching ........................99 6.3 Results.................................................................................................................103 6.3.1 Donor-candidate age matching cut-points ....................................................103 6.3.2 Recommendations and hypothetical redistribution of deceased donor kidneys to recipients .....................................................................................104 6.4 Interpretation .......................................................................................................106  viii  7 Lifetime of allograft function – a new metric to inform the optimal use of expanded criteria donor kidney transplantation .......................... 115 7.1 Introduction .........................................................................................................115 7.2 Methods ..............................................................................................................117 7.2.1 Comparison of the use and outcomes of ECD kidney transplantation in the Eurotransplant Senior Program and the United States .......................117 7.2.2 Analysis of recipient outcomes after ECD kidney transplantation in the United States ...........................................................................................119 7.3 Results.................................................................................................................120 7.3.1 Comparison of the use and outcomes of ECD kidney transplantation in the Eurotransplant Senior Program and the United States .......................120 7.3.2 Analysis of recipient outcomes after ECD kidney transplantation in the United States. ..........................................................................................122 7.4 Interpretation .......................................................................................................123 7.4.1 Disclosure .....................................................................................................128 8 Multiple wait-listing ............................................................................... 137 8.1 Introduction .........................................................................................................137 8.2 Methods ..............................................................................................................139 8.2.1 Data source and study population.................................................................139 8.2.2 Statistical analyses ........................................................................................140 8.3 Results.................................................................................................................142 8.3.1 Factors associated with multiple wait-listing ...............................................142 8.3.2 Association of multiple wait-listing with access to deceased donor transplantation ..............................................................................................143 8.4 Discussion ...........................................................................................................145 8.4.1 Conclusion ....................................................................................................148 8.4.2 Disclosure .....................................................................................................148 9 Conclusion .............................................................................................. 161 9.1 Summary .............................................................................................................161 9.2 Key findings and contributions ...........................................................................162 9.2.1 Estimating the number of potential deceased donors ...................................162 9.2.2 Defining equitable utility-based cut-points for age matching ......................163 9.2.3 Implications of not age-matching .................................................................165 9.2.4 Multiple wait-listing .....................................................................................167 9.3 Strengths and limitations ....................................................................................167 9.4 Study implications and future work ....................................................................169 9.5 Conclusion ..........................................................................................................173 References .................................................................................................... 175 Appendices .................................................................................................. 185     ix  List of tables Table 2.1. Regional metrics for death and deceased organ donation.................................36 Table 2.2. The identification of potential donors by age group using the study method ...............................................................................................................37 Table 2.3.  Number of potential donors identified by chart audit and study method in Winnipeg area hospitals compared to actual number of donors ...................37 Table 2.4. Number of potential donors identified by the chart audit and study method in Winnipeg area hospitals by age at death. .........................................38 Table 2.5. The conversion of potential donors to actual donors by age group ..................38 Table 5.1 Recipient and donor characteristics ...................................................................86 Table 5.2. Study sample size by recipient and donor kidney age categories .....................87 Table 5.3. Area under and between recipient survival and graft survival curves ..............88 Table 5.4. The summative utility of two allocation systems .............................................88 Table 6.1. Area under and between recipient survival and graft survival curves ............113 Table 6.2. The designation of transplant candidates as young or old relative to the age of the deceased donor kidney. ..................................................................114 Table 7.1. Characteristics of patients who received kidneys from donor aged ≥ 65 years. ...............................................................................................................132 Table 7.2. Characteristics of patients aged ≥ 65 years who received kidneys from donor aged ≥ 65 years .....................................................................................134 Table 7.3. Relative hazard of transplant failure in ESP compared to U.S. transplant recipients ........................................................................................135 Table 7.4. Unadjusted mean difference in patient survival versus graft survival in elderly ESP versus U.S. recipients after five years of transplantation ............136 Table 7.5. Patient survival ten years after transplantation with a donor kidney <65 years stratified by kidney donor profile index and after transplantation from a donor kidney ≥ 65 years ......................................................................136  x  Table 8.1. Characteristics of multiply versus singly listed wait-listed candidates (N=310,475) ....................................................................................................151 Table 8.2. The multivariate odds ratio for a candidate being multiply (two or more centres) versus singly wait-listed for deceased donor transplantation. ...........154 Table 8.3.  Among candidates who are multiply wait-listed for deceased donor kidney transplantation, the multivariate odds ratio of being listed singly at more than two centres versus two centres. ..................................................156 Table 8.4. Median time to deceased donor kidney transplantation among multiply versus singly wait-listed candidates. Table shows median (q1, q3) years. ...............................................................................................................159      xi  List of figures Figure 2.1. A flow chart describing the study method used to estimate the number of potential deceased organ donors ...................................................................35 Figure 2.2. Potential donors, actual donors and the age-standardized donor conversion Ratio by province of transplantation ..............................................35 Figure 3.1. A description of the intersection of life expectancy, access to transplantation, and quality life from the transplant candidates perspective.........................................................................................................51 Figure 5.1 Panel A shows possible differences in predicted patient and deceased donor kidney survival between donor kidneys and their recipients under current allocation rules. Panel B shows possible differences in predicted patient and deceased donor kidney survival for the same aged donor kidneys and recipients using allocation by life expectancy matching. ...........................................................................................................82 Figure 5.2 A description of the inefficiencies that occur when the same recipient is transplanted with deceased donor kidney grafts with differential expected survival.The dark grey bars represent the two types of inefficiency that occur when the recipient and the donor kidney have unequal survival ................................................................................................82 Figure 5.3 Left panel: Area between the recipient and graft survival curves represents the time a patient would be required to return to dialysis and await repeat transplantation. Right panel: area between the recipient and graft survival curves represents the loss of potential kidney function. ............................................................................................................83 Figure 5.4. Histograms showing the distribution of recipient (top panel) and deceased donor kidney (bottom panel) ages .....................................................84 Figure 5.5. Left panel: Recipient survival by recipient age categories. Right panel: Graft survival by donor age categories. ............................................................85 Figure 6.1 The distribution of Canadian recipient age and deceased donor kidney age by year of transplantation. Recipient mean age (std): 44 (14.7) in 1995, 53 (15.1) in 2010; Donor kidney mean age (std): 36 (16.9)  in 1995, 43 (17.0) in 2010.  P-value for trends in recipient age and deceased donor kidney age over time p<0.0001. ............................................111  xii  Figure 6.2 The distribution of deceased donor kidneys to recipients by age. Top panel shows how deceased donor kidneys from 2008-2010 were allocated in practice to recipients. Bottom panel shows the redistribution of the same aged deceased donor kidneys to the same aged recipients following the recommendations for donor-candidate age matching in this chapter. .................................................................................112 Figure 7.1. Kaplan-Meier plots comparing transplant outcomes among the N = 1520 ESP and n=446 U.S. recipients who were ≥ 65 years of age at the time of kidney transplantation from a deceased donor ≥ 65 years. (P<0.0001 for each comparison) .....................................................................129 Figure 7.2. Distribution of age of recipients of kidney transplantation from ECD kidneys from 1995-2010. ................................................................................130 Figure 7.3. Ten year mean patient and death censored graft survival and difference between curves. ..............................................................................131 Figure 8.1. The odds ratio of multiple listing by year of candidate wait-listing compared to candidates wait-listed between 1995 and 1998 (error bars represent 95% confidence intervals). The model included the following covariates: candidate demographics (i.e. age at wait-listing, sex, race, cause of end-stage renal disease, body mass index), biologic factors (i.e. peak panel reactive antibody titre, ABO blood group), socioeconomic factors (i.e. level of education, employment status, health insurance provider), and quintile of median waiting time for deceased donor transplantation in the candidate’s primary centre of wait-listing. .....................................................................................................149 Figure 8.2. The proportion of candidates multiply listed by organ procurement organization of wait-listing .............................................................................149 Figure 8.3. The relative hazard of transplantation over time for multiply versus singly wait-listed candidates (reference=1.00 singly wait-listed) in different years of transplantation. The model was adjusted for: candidate demographics (i.e. age at wait-listing, sex, race, cause of end-stage renal disease, body mass index), biologic factors (i.e. peak panel reactive antibody titre, ABO blood group), socioeconomic factors (i.e. level of education, employment status, health insurance provider), and quintile of median waiting time for deceased donor transplantation in the candidate’s primary centre of wait-listing. ................................................150 Figure 8.4. The proportion of patients who were transplanted at five years after wait-listing date. ..............................................................................................150  xiii  Abbreviations ABSC BMI CCDT CCI CI CKD CORR CVA DAD DCD DDK DRPM DT ECD ESP ESRD GED HLA HR HRSA ICD-9-CM  ICD-10-CA KAS KDPI KDRI KPD LYFT OPO OPTN OPTNKC OR PRA Q1 Q3 SCD SRTR STD USRDS Area between survival curves Body mass index Canadian Council for Donation and Transplantation Canadian classification of health intervention Confidence interval Chronic kidney disease Canadian Organ Replacement Register Cerebrovascular disease Discharge Abstract Database Donation after cardio-circulatory death Deceased donor kidney Donor rate per million population Dialysis time Expanded criteria donor Eurotransplant Senior’s Program End-stage renal disease General educational development Human leukocyte antigen Hazard ratio Health Resources and Services Administration International Classification of Diseases, Ninth Revision, Clinical Modification   International Classification of Diseases, 10th Revision, Canadian enhanced version Kidney allocation score Kidney donor profile index Kidney donor risk index Kidney paired exchange Life years from transplant Organ procurement organization Organ procurement and transplantation network Organ procurement and transplantation network kidney committee Odds ratio Panel reactive antibody First quartile Third quartile Standard criteria donor Scientific Registry of Transplant Recipients Standard deviation United States Renal Data System    xiv   Acknowledgements The research presented in this thesis would not have been possible without the limitless support of my thesis committee (Drs John Gill, Joel Singer and Jacek Kopec), who provided their time and expertise to share feedback on the work presented in this thesis and ultimately helped improve the research. In particular, I will be forever grateful for the mentorship I have received over the past decade from Dr Gill. Dr Gill has taught me how to think critically, challenged me to solve problems by thinking outside every box, and helped refine my writing skills. I cannot thank Dr Gill enough for his enduring support throughout the PhD process and in the development of my career.  I would also like to thank my colleagues and funding programs for giving me opportunities to discuss my work, and vet my solutions and ideas. I have learned an immense amount through conversation with my peers and mentors in my scholarship programs.  Most importantly, I would like to thank my family for their love and patience during the writing of this dissertation. They provided me with constant encouragement and time, both essential to the completion of this degree. Thank you for always believing in me, and nurturing the belief in myself that I was capable of anything I could imagine. You bring love and happiness into my life, and your humour keeps me grounded.      xv  Dedication To my Family     A   1  1 Introduction 1.1 The epidemiology of end-stage renal disease Chronic kidney disease (CKD) is the progressive and irreversible loss of kidney function over time. The leading causes of CKD are diabetes, cardiovascular disease, hypertension and obesity. CKD is the 10th leading cause of death in Canada and the 12th leading cause of death worldwide,1, 2 contributing to 3,803 and 927,592 deaths in 2009 in Canada and the world respectively.1, 3 The burden of this disease may be underestimated as there are a large number of disability adjusted life years lost with CKD, and many patients with CKD die of other causes (e.g. cardiovascular disease).  Patients who survive to develop end stage renal disease (ESRD) will die if they do not receive renal replacement therapy.  Estimating the prevalence of ESRD worldwide is difficult because many developing countries do not have the means to provide renal replacement therapy. Among countries that do provide renal replacement therapy, many collect data on patients with ESRD in national registries. These national registries provide data on the incidence and prevalence of ESRD, as well as the characteristics of the population and outcomes data. Unfortunately, the data across registries are collected differentially and are of variable quality. Nonetheless, these registries provide the best available data on ESRD, and allow for international comparisons 4.   Canadian data is collected in the Canadian Organ Replacement Register (CORR). CORR is a national information system for renal dialysis and solid organ transplantation housed  2  at the Canadian Institute for Health Information. The register collects, processes, analyzes and reports the level of activity and outcomes of solid organ transplantation and renal dialysis activities.5 CORR obtains patient- level data through voluntary data submission from hospital dialysis programs, regional transplant programs, organ procurement organizations and independent providers of dialysis.  Further details on CORR, including coverage, reliability and validity, can be found in Appendix A.  In Canada in 2009, there were 5 375 incident cases of ESRD, an increase of 137% since 1990. 6  In the same period, the prevalence of ESRD also increased more than 200% from 11 042 to 37 744. 6 As the leading causes of CKD continue to increase, the impact and repercussions of ESRD on the Canadian health care system will be significant.  1.1.1 Renal replacement therapies The primary functions of the kidney are: to maintain the body’s internal equilibrium of water and minerals, to excrete end-products of metabolism, and to function as part of the endocrine system.7 For patients with ESRD, whose kidneys no longer provide these functions, there are two types of renal replacement therapy: dialysis and kidney transplantation.   Dialysis uses a machine to mimic the major roles of the kidney: diffusion (eliminating waste) and ultrafiltration (eliminating fluids). Dialysis is an imperfect replacement to natural kidney function because it cannot replicate the endocrine functions of the kidney.  3  Kidney transplantation is the engraftment of a human kidney from a donor to a recipient with the goal of restoring kidney function. Transplant recipients require continuous immunosuppressive drug therapy to prevent graft (i.e. transplanted kidney) rejection. Compared to dialysis, transplantation is life prolonging, quality of life enhancing, cost-saving and can be life saving for patients who are unable to dialyze.8, 9 Therefore, despite the requirement for on-going immunosuppression, transplantation is the preferred form of renal replacement therapy for most patients with ESRD without a contraindication to transplantation, such as infection, cancer or a short life expectancy due to advanced age or multi-system disease.  Both deceased and living people can donate kidneys for transplantation. Deceased donor kidneys come from patients who die in hospital with a diagnosis of brain death or cardio-circulatory death, who have no absolute contraindications to donation (e.g. metastatic cancer or seropositivity for human immunodeficiency virus).10 In Canada, these patients or their families must provide consent for donation. Approximately 2.5% of Canadian patients who die in hospital are eligible for donation (roughly 8 300 per year) (see Chapter 2). Unfortunately, primarily due to difficulty with identification, only 15% of these potential donors become actual donors.   Living donor kidney transplantation provides timely access to transplantation; and living donor kidney transplant outcomes are superior to those achieved with transplantation from a deceased donor. Living kidney donors are most often related to their recipient through a blood or emotional bond. Potential living donors must be ABO blood group  4  and Human Leukocyte Antigen (HLA) compatible with their recipient, and must undergo a thorough medical and psychological evaluation before being accepted for living organ donation. In British Columbia approximately 50% of all kidney transplants are from a living donors (19% of living donors are spouses, 59% blood related, and 22% emotionally related (e.g. friend, in-law)). 11  1.1.2 Supply of organs The need for transplantation exceeds the availability of transplantable organs. In Canada, there are more than 3 000 people waiting for kidney transplantation,12 but only 1000 of these patients receive transplantation yearly (34% living donor, 66% deceased donor)6;  The waiting list provides a limited view of the need for transplantation, as many patients are never wait-listed, and there are more than 23 000 patients whose life is sustained with dialysis in Canada.12 Further, the fact that only 2% of patients die on the waiting list underestimates the magnitude of the organ shortage problem as many other patients are removed from the waiting list prior to death for declining health concerns.12 The median waiting time for kidney transplantation varies three-fold across Canadian provinces.6 This variation occurs because deceased donor kidneys are allocated within seven regions that follow provincial boundaries (i.e. they are not shared nationally).  Ongoing strategies to address the shortage of kidneys for transplantation include: 1) decreasing the incidence of ESRD, 2) increasing the number of deceased and living donor organs for kidney transplantation, and 3) decreasing the need for repeat kidney  5  transplantation by improving kidney transplant survival.   Improvements in immunosuppression and general medical and surgical management have greatly increased kidney survival, and patient survival in the early period post-transplant. However, despite these successes little further gain has been made in increasing patient life with kidney function in the long term. Unfortunately, diabetes, hypertension and obesity are leading causes of CKD/ESRD, and despite the best efforts of the medical community the prevalence of kidney disease continues to increase worldwide. 13-15  1.1.2.1 Expanding deceased kidney donation Because of the organ shortage, medical professionals endeavour to use every viable deceased donor kidney for transplantation. As such, the criteria for accepting deceased donors has been expanded to include organs from older aged donors or donors with medical conditions, such as hypertension, that would not have routinely been used for transplantation in the past. These donors are termed expanded criteria donors (ECDs). Although ECD kidney transplant outcomes are inferior to outcomes from non-ECD donors, these organs are safe to transplant and provide a survival advantage relative to treatment with dialysis for elderly transplant candidates, patients residing in regions with extremely long waiting times, and patients who tolerate dialysis poorly.16   Deceased organ donors usually have sustained severe brain injuries and meet strict  6  medical criteria for neurological brain death. Donation after circulatory death (DCD) describes the retrieval of organs for transplantation using circulatory, not neurologic, criteria. The use of DCD differs across provinces. Kidneys from DCD donors currently comprise more than 20% of all deceased donors in Ontario and Quebec, but are not used in other provinces.17 Despite consensus internationally and in Canada,18 some physicians maintain ethical objections to DCD and believe more research is necessary.  Widespread efforts to increase deceased donation and the limited introduction of DCD in Canada , have produced a modest 25% increase in the number of Canadian deceased donors over the last decade, however, this increase remains inadequate to meet the growing need for kidney transplantation.6 1.1.2.2 Measuring deceased donation Efforts to increase deceased donation are critically dependent on timely, accurate and insightful information about deceased donor activity and the success rate of converting potential donors to actual donors. The currently reported metric for deceased donation activity is the donor rate per million living population (DRPM). Wide variation exists in the DRPM internationally with Canada performing in the bottom half of all reported countries (DRPM=15).3  In addition, there is a three-fold variation in DRPM across Canadian provinces.3 Although the DRPM may be used as a comparative metric in the same population over time, it is limited for comparisons between populations.19 Importantly, it does not account for baseline differences in population characteristics among patients who die and are eligible for donation.20 A measure of deceased donation  7  that more accurately reflects the population of potential donors is needed. Such a metric could be used to compare donation activity across regions, and inform strategies to increase donation. A new method to estimate deceased donation activity will be introduced in Chapter 2.  1.1.2.3 Expanding living kidney donation Several strategies have been used to increase living donation. Living donation was expanded from blood-related donors to include emotionally related, but biologically unrelated donors. Over the last decade the use of unrelated donors in Canada has increased by 64%.3 In addition, older age living donors are now more frequently transplanted (i.e. the number of Canadian living donors aged ≥ 55 years has tripled since 2003). Another expansion of living kidney donation is the inclusion of non-directed anonymous donors.  These donors have no relationship with a specific transplant recipient, and do not decide which patient will receive their kidney. Kidney donations from non-directed anonymous donors were first accepted in Vancouver in 2003, and are now accepted in most transplant programs in Canada. Kidneys from non-directed anonymous donors were originally allocated to the first matched person on the deceased donor waiting list, but are now most commonly allocated as part of another program intended to increase living kidney donation: a Canadian national living kidney donor paired exchange program (KPD), launched by Canadian Blood Services as a pilot project in 2009. 21  More than 20% of individuals that come forward to donate their kidney to a blood or  8  emotionally related person in need of transplantation are unable to do so because of a biologic incompatibility.11  KPD facilitates donation from these willing but incompatible donor-recipient pairs by matching these pairs with other similarly incompatible pairs.22 Entry into the program is voluntary, and a computer algorithm is run with all incompatible pairs every three months that determines feasible chains of pairs for donation. Although the use of non-directed anonymous donors and KPD have helped to promote living donation, it is unclear whether the impact of these programs has led to an increase in the number of living kidney donors or simply changed the type of living donor kidney transplantations.  The number of living donors in Canada increased from 435 to 539 from 2003-2012, 6 and 240 kidney transplantations were facilitated by KPD between 2009-2013.23   Although the new initiatives to expand both living and deceased kidney donation have been marginally successful in increasing the absolute number of transplanted kidneys, their successes have been overwhelmed by the increasing number of patients with renal disease. As a result, addressing the widening gap between supply and demand for organs requires alternative and additional strategies.  1.2 Allocation of kidneys for transplantation Living donors are selected based on their psychological and medical suitability, as well as their biologic compatibility (i.e. blood group and tissue compatibility) with their intended recipient. Aside from the less common non-directed anonymous donors, a living donor has an emotional relationship (either blood related or unrelated) with their recipient.  9  Therefore, transplantation from living donors is directed, i.e. the recipient is specified a priori. In contrast, there is no relationship between deceased donors and patients on deceased organ transplant waiting lists and decisions must be made about which transplant candidates will receive the limited number of available deceased donor organs.   In Canada, deceased donor kidneys are allocated to biologically compatible transplant candidates, almost exclusively within geographic regions. Allocation within these groups then follows national consensus recommendations, assigning overriding priority for kidney transplantation to patients with the greatest medical need. 24 This comprises patients who are unable to receive dialysis treatment, pediatric patients whose physical and psychological development can be severely stunted on dialysis, and highly sensitized patients (patients who are estimated to be tissue incompatible with a high percentage of deceased organ donors). Within prioritized groups, the need for kidney transplantation is assumed to be equal and ties between transplant candidates are decided by regional point systems that include various patient factors. Allocation rules are updated intermittently to address the changing needs of the transplant candidate population. 1.2.1 Ethical considerations for allocation: utility and justice Two key ethical principles guide the ranking systems for allocation of deceased donor organs to transplant candidates: utility and justice 25. In the ethics literature on resource allocation, utility commonly refers to ‘making optimal use of the resources so that the greatest total benefit is obtained’ and justice to the ‘equal treatment of people so as not to advantage or disadvantage any group’.26   10  For non-renal organ failure (e.g. heart, lung, liver), transplantation is the only long-term treatment and the sickest patients are prioritized. Utility is the precedent focus in allocation of these organs, and is measured by the prevention of imminent death. In contrast, ESRD patients can be treated chronically with dialysis and can live years waiting for kidney transplantation. In this setting, allocation rules seek to determine an acceptable balance between utility and justice.  In kidney transplantation, utility most commonly refers to allocating a ‘kidney to the patient in whom it will survive the longest’ and justice to ensuring that ‘each patient who could benefit from transplantation would have equal opportunity to receive one’.14 The balance of these two allocation principles has changed historically, and is driven by the successes of kidney transplantation and the availability of deceased donor kidneys. The definitions of utility and justice will be explored more thoroughly in Chapter 3. In the 1970s and early 80s, clinical transplantation was in its infancy and graft and patient survival outcomes following deceased donor kidney transplantation were mediocre. Use of transplantation as a therapy was therefore reserved for young, otherwise healthy patients who were expected to have superior survival 27 At this time, few patients were waiting for transplantation and deceased donor kidneys were allocated to obtain optimal outcomes. For example, graft rejection was a significant issue and allocation was driven by biologic considerations (i.e. matching transplant candidates to the most immunologically compatible donors-defined by compatibility of Human Leukocyte Antigens (HLA)) to decrease the risk of rejection. As a result of medical and surgical advancements in the mid-80s and 90s, graft rejection became less common and short- 11  term graft and patient survival increased. Transplantation has become the gold standard treatment for ESRD and is no longer reserved for young and healthy dialysis patients. There is no absolute age restriction for transplantation, and many of the sickest patients (e.g. diabetics) derive the greatest relative survival benefit from kidney transplantation, because their dialysis survival is limited.28 The liberalization of transplant eligibility combined with an increased prevalence of ESRD has led to an incessant growth in the demand for kidney transplantation that outstrips the supply of transplantable organs. In consequence, many countries have all but eliminated HLA-matching in their allocation algorithms in favour of emphasizing time on the kidney transplant waiting list- a shift from utility to justice based allocation.  There is no or limited attempt to optimize post-kidney transplantation outcomes by matching the anticipated longevity of the deceased donor kidney with that of the potential recipient. 1.3 Outstanding questions and study justification 1.3.1 Challenges in allocation The current allocation system, which prioritizes fairness in access to kidney transplantation, allows the possibility of discordance in recipient survival and survival of the deceased donor kidney. For example, transplantation of a 20-year old deceased donor kidney to a patient aged > 60 years would result in loss of potential kidney transplant function because the anticipated life expectancy of the transplanted organ is greater than that of the transplant recipient.29 Loss of potential kidney function occurs when a patient dies with a transplant that could have continued to function had the patient not died. Transplanted kidneys cannot be re-transplanted after the death of the recipient.   12   Alternatively, if a 60-year old deceased donor kidney is transplanted into a 20-year old recipient, the recipient’s life expectancy will exceed that of the deceased donor kidney and the recipient will require another transplant. Repeat transplantation is a significant burden on the Canadian organ supply, accounting for 11% of kidney transplantation 6. In addition, failed transplant recipients may develop immunological barriers to transplantation that lessen their likelihood of repeat transplantation, leading to prolonged requirement for dialysis after transplant failure. Therefore, matching the anticipated life expectancies of transplant recipients and deceased donor kidneys has the potential to avoid organ wastage and minimize the need for renal replacement therapy after deceased donor kidney failure.29  1.3.2 Recipient and deceased donor kidney life expectancies Accurately predicting post-kidney transplant recipient and deceased donor kidney life expectancies prior to transplantation is imperfect, in large part because life expectancies are dependent on post-transplant factors, which are unpredictable. Recipient and donor ages are the most important predictors of post-kidney transplant recipient and deceased donor kidney survival15, 30 and have the advantage of being objectively measurable and transparent factors for both patients and medical personnel. The inclusion of additional variables in models estimating recipient and deceased donor kidney survival, has been proposed but rejected. The basis for rejection of this approach is that it is too complex to be understood by patients, subjective, and only marginally superior to models including donor and recipient ages alone.31, 32 For these reasons, donor and recipient ages will be  13  used as the primary determinants of recipient and deceased donor kidney life expectancies in this thesis.   Although the independent effects of deceased donor kidney and recipient ages on post-transplant outcomes are well described, it is not clear if deceased donor kidney age modifies the relationship between recipient age and post-transplant outcomes.33, 34 For example, although older age for both donors and recipients is associated with worse deceased donor kidney and recipient survival, it is not clear if the effect of increasing deceased donor kidney age on deceased donor kidney survival is as marked in older recipients with shorter expected survival, as it would be in younger recipients with longer expected survival.33, 34   1.3.3 The problem with age matching- introduction of inequities in access to transplantation In this thesis, age matching refers to the preferential allocation of deceased donor kidneys of a given age to ABO blood group and human leukocyte antigen (HLA) compatible transplant candidates in given age categories. For example, an age matching policy might allocate deceased donor kidneys aged ≥ 40 years to transplant candidates aged ≥ 55 years and deceased donor kidneys aged < 40 years to transplant candidates < 55 years. Within organ allocation algorithms age matching would be superseded by established criteria that prioritize certain wait-listed candidates for transplantation such as pediatric candidates and highly sensitized candidates.   14   The age distribution of deceased donors is a moving target and somewhat unpredictable, but is generally increasing over time, while the age distribution of transplant candidates has been increasing more rapidly over time. An age allocation system that is based on matching deceased donor kidney and recipient ages therefore has the potential to introduce inequities in access to transplantation between candidates of different age groups. The most recently proposed deceased donor kidney allocation rules in the United States emphasize utility by including components that match estimated donor kidney and transplant candidate life expectancies (detail provided in Chapter 4). Although the results from preliminary simulations showed improvement in lifespan benefit per kidney transplantation compared to current allocation, the results also showed that there was a reduction in the proportion of older recipients receiving kidney transplantation (10% and 20% reduction in the number of recipients aged 50-64 and ≥ 65 respectively).35, 36    Even if age matching could increase the utility of deceased donor kidney allocation, the magnitude of the change in utility and its effect on equity in Canada is unknown. A sample of data from all deceased donor kidney transplantation in the United States in 2006, showed that recipients aged 18 to 35 received fewer than 5% of kidneys from deceased donors aged ≥55 years, and only 1% from deceased donors aged ≥60 years 37. In contrast, recipients aged ≥65 years received more than 40% of their kidneys from deceased donors aged < 35 years (this represented 24% of all deceased donor kidneys aged < 35 years). Similar statistics showing the donor-recipient pairings at age extremes are not currently available for Canada. The potential increase in utility arising from an  15  age matching allocation strategy needs to be estimated, and considered in the context of its potential impact on access to transplantation among patients in different age groups, including the number of patients transplanted and waiting times for transplantation.  1.3.4 Attitudes about deceased donor kidney allocation Attitudes among stakeholders vary on how to appropriately balance utility and justice in the allocation of deceased donor kidneys. Specifically in the United States, this has made it difficult to implement change to current allocation policies. Some believe utility to be of major importance, advocating for a greater emphasis on donation to younger and healthier patients, while others are steadfast in their belief that equal access to this scarce health resource is a necessity.  A survey in the United States in 1996 reported that the public believe small improvements in post-transplant outcomes are not justified at the expense of longer waiting times in some patient subgroups.38  In another small study (N=33) in the United States, transplant candidates had varying views about whether longer waiting times were justified in order to ensure a better tissue matched kidney for transplantation.39 However, this study may have been biased by including a cohort of patients who were waiting for repeat kidney transplantation (i.e. they may have been familiar with the agony of graft failure, and the difficulty in accessing another donor kidney), and therefore, the study’s external validity is uncertain. A larger survey of dialysis patients and transplant recipients (N=232) in the United Kingdom, found that participants favoured equitable allocation (waiting time) 2:1, compared to efficient allocation (tissue matching), but 66% favoured allocation by longer waiting times when  16  this factor was the only difference between candidates.40 The same survey asked patients to decide who should receive a deceased donor kidney transplant between two similar candidates, one aged 20 years and one aged 60 years. Fifty percent of respondents thought age should not be a determinant in allocation, while 35% allocated in favour of the younger candidate and only 7% to the older candidate (8% did not know). Interestingly, study patients aged > 70 years were the most likely to allocate the deceased donor kidney to the younger patient (56%), suggesting that older patients may not be averse to some inequity in access to transplantation by age.  However, only one of nine questions in this study was related to kidney allocation by age, and the study did not explore the extra waiting time or increased probability of death that an older candidate may experience in this scenario. To date, no studies have been published in Canada examining the attitudes of transplant candidates about deceased donor kidney allocation. The only record of Canadian patient perceptions is from focus groups in Manitoba. The focus group study results suggested that candidates wanted allocation policies to be transparent and free of unjust discrimination.41  No comment was made about utility and justice.  Although rules for allocating deceased donor kidneys to transplant candidates are predetermined, decisions about which ESRD patients to wait-list for transplantation, and which kidneys to accept for transplantation are at the discretion of the transplant nephrologist or surgeon. In addition, policy makers rely on expert opinion of these physicians to inform changes in allocation policy. Therefore, transplant physicians are major stakeholders in the allocation of deceased donor kidneys. A recent qualitative  17  survey of Australian nephrologists (N=25) ascertained their opinions about wait-listing and deceased donor kidney allocation.42 Overall, the nephrologists wanted to limit discrimination among sub-populations access to transplantation as well as increase the survival benefit gained from each kidney. Age matching was mentioned as a strategy to increase utility, suggesting preference in allocation for the young; although criticism arose at the potential disadvantage of transplanting older kidneys into older candidates (i.e. reduced patient survival). In contrast, matching older deceased donor kidneys to older candidates was also suggested as a strategy to make better use of older kidneys and reduce discard of these organs. Most importantly, the nephrologists did not want to be responsible for decision making regarding the appropriate balance of utility and equity in allocation, but believed that this was a necessary role for policy makers.    ESRD patients and their physicians have varying views about weighting the conflicting principles of utility and justice. Although age matching is a recurring theme in surveys about the allocation of deceased donor kidneys, there is no comprehensive data describing the considerations of health practitioners and patients regarding specific age matching policies, nor the degree of equity loss (reduced access to, or longer waiting times for, deceased donor kidney transplantation) that patients and physicians would be willing to accept for a given improvement in post-transplant survival outcomes. 1.3.5 Regional disparities in access to transplantation  With the exception of highly sensitized candidates, deceased donor kidneys are shared regionally, but not nationally in Canada. Therefore, the likelihood of accessing deceased  18  donor kidney transplantation depends on regional factors (e.g. wait-listing practices, the number of candidates on regional waiting lists, the number of living and deceased donors available for transplantation) as well as biologic factors (e.g. blood type, and genetic tissue profile of available donors and candidates). Despite similar allocation rules in practice across Canada, there is four-fold variation in the likelihood of accessing deceased donor transplantation across Canadian regions,43 and the median time to deceased donor kidney transplantation varies three-fold (median time in Nova Scotia 2.1 years; median time in British Columbia 5.9 years).3 Given the small population of some transplant regions in Canada, it is not known if the regional incorporation of new allocation policies (e.g. donor-candidate age matching) would reduce or exaggerate geographic disparities in access to transplantation. An example of a policy in the United States that may reduce geographic inequity in access to deceased donor kidney transplantation is the practice of multiple wait-listing (i.e. the ability to appear on a deceased donor waiting list in more than one region).  American candidates and health care practitioners have used the practice of multiple wait-listing, as a mechanism to improve individual patient access to transplantation.44 For example, the median waiting time for deceased donor transplantation was significantly longer in the candidates’ first centre of wait-listing suggesting that patients are exploiting the policy of multiple wait-listing to achieve quicker access to transplantation and reduce geographic disparities in access to transplantation.45 Multiple wait-listing was associated with an 88% increase in access to deceased donor transplantation in the United States (data up to June 2000).45 It is not known if the use and impact of multiple wait-listing on access to transplantation has increased in the current era where there has been rapid growth of the  19  deceased donor kidney waiting lists in the United States. Understanding the current impact of this policy in the U.S. would help inform the need for such a policy in Canada.    1.3.6 Summary The number of kidneys available for transplantation is not sufficient to transplant all patients who would benefit. The donor rate per million population is an imperfect measure of deceased donation and more accurate measures of the number of potential donors who die in Canadian hospitals are needed to more closely reflect our maximum possible supply of deceased donors. Accurate measurement of donation activity will help to inform strategies to increase deceased donation.   In the absence of an adequate donor supply, decisions must be made about how best to use (i.e. allocate) the organs that are available. There is consensus in the transplant community that avoiding large discrepancies between expected organ and patient survival is desirable. Although, individual programs and clinicians may actively try to restrict this practice, mismatches in life expectancy still occur. Age matching, in some format, is consistently proposed as a possible solution. There is a discord in opinion on how to balance utility and justice in deceased donor kidney allocation, providing challenges for policy makers. Gill46 proposes that there is a need to revisit the strategies by which increased utility will be incorporated into allocation policies, while maintaining justice. The solution that may be the most currently acceptable is a strategy that would not change the population characteristics of future recipients from current recipients, but  20  would instead allocate deceased donor kidneys differentially among the same pool of transplant candidates. 1.4 Research hypotheses and study questions The overarching goals of this thesis are: 1) to develop a new method to estimate deceased donation activity,  2) to examine the potential benefits and harms of allocating deceased donor kidneys by age matching, and inform the safe use of older donor kidneys for transplantation, and 3) to describe the impacts of wait-listing policies on regional disparities. The primary determinant of patient survival after kidney transplantation is recipient age, and the primary determinant of deceased donor kidney survival after kidney transplantation is the age of the donor kidney. To date, age has not been widely accepted as a criterion for the allocation of deceased donor kidneys in North America.  As a result, older recipients are likely to die with a functioning deceased donor kidney, leading to varying amounts of unrecognized kidney function. Similarly, young recipients are likely to outlive their donor kidneys and return to dialysis for varying times or require another transplant. A strategy that allocates deceased donor kidneys by age matching would minimize both kidney function waste and time back on dialysis after kidney transplant failure.  The specific research questions addressed in this thesis are:  1) To develop and validate a new method to estimate the number of deceased donor kidneys available for transplantation in Canada, including stratification by age.  21  2) To develop a new metric for the utility of deceased donor kidney transplantation, and use this to define equitable utility-based age cut-points for the allocation of deceased donor kidneys. 3) To compare the utility of allocating older deceased donor kidneys in a system that incorporates age matching versus one that does not; to provide evidence to inform the safe use of older donor kidneys for transplantation, and decrease organ discard; and to determine recipient outcomes after transplantation when older donor kidneys are not allocated using age-matching.  4) To describe longitudinal changes in the use of the multiple wait-listing for deceased donor transplantation, and assess whether the impact of multiple wait-listing on access to deceased donor transplantation has changed over time. 1.5 Outline of thesis The research chapters in this thesis are intended for publication elsewhere. As such, they have been formatted to resemble stand-alone papers, with reduced repetition across chapters (except as needed for clarity), and with transition pieces.  This chapter serves as an overview to native kidney disease and kidney transplantation. In addition, outstanding questions in the field of deceased donor kidney allocation were presented, and the thesis objectives and an outline of the thesis are presented.  Chapter 2 focuses on the measurement of deceased donation activity. Specifically, this chapter develops a new method to estimate the number of potential deceased donors in Canada, and assesses the accuracy of this method in one Canadian region. In addition, the  22  number of deceased donors estimated using the study method are compared to the number of actual deceased donors in Canada to calculate the conversion rate of potential donors to actual donors.  Chapters 3-7 focus on deceased donor kidney allocation. Chapter 3 defines the concepts of utility and justice as they are commonly used in the transplantation ethics literature, and provides thesis specific definitions of these concepts. In addition, this chapter explores the perspectives of transplant candidates and policy makers in regards to the allocation of deceased donor kidneys. Chapter 4 provides an overview of the policy of deceased donor kidney allocation, including an extensive look at current and proposed allocation rules in the United States. Chapter 5 and 6 use Canadian data to describe a new metric of utility, and the use of this utility measure along with information about deceased donor kidney and recipient ages to define and develop equitable utility based cut-points for the allocation of deceased donor kidneys. In Chapter 7, the allocation of older donor kidneys (i.e. which candidates are receiving transplantation from these kidneys), as well as the recipient survival and donor kidney survival are compared between two allocation systems: one which allocates older donor kidneys by age matching, and one which does not allocate older donor kidneys by age matching.  In addition, post-transplant outcomes for recipients of older deceased donor kidneys in the system that does not require age matching are described.  In the United States, patients can be wait-listed for deceased donor transplantation at more than one transplant centre. Chapter 8 describes the advantage of being multiply  23  wait-listed for deceased donor kidney transplantation, and the factors associated with multiple wait-listing. The implications of this policy of geographic disparities in access to transplantation will be discussed.  The final chapter, Chapter 9, summarizes the findings of the thesis, and integrates the discussion. In addition, Chapter 9 reviews the strengths and limitations of the research, synthesizes the implications of the research, and presents suggestions for future work.    24  2 Estimating the number of potential deceased organ donors 2.1 Introduction Despite numerous initiatives, there has been no substantial increase in the number of deceased organ donors in Canada during the past decade. 47, 48 To what extent this stagnation is related to: 1) fewer potential deceased donors (individuals who have sustained severe brain injuries without medical contraindications to organ donation) due to aging of the Canadian population and public safety initiatives that have reduced the number of traumatic deaths, or 2) failure to identify and obtain consent for donation from potential deceased donors remains uncertain. The understanding of these issues is impeded by the lack of national data regarding the number of potential donors who die in Canadian hospitals. Information regarding the potential pool of deceased donors in Canada is essential to determine system performance, and devise strategies to increase deceased donation.    The most commonly reported metric of deceased donation, the donor rate per million inhabitants living in a region (DRPM),48 does not account for regional or secular differences in mortality, or for the cause of death among hospitalized patients,19, 49 and therefore may lead to regions being misclassified as underperformers.50 There is more than three-fold variation in the DRPM across Canadian provinces (Table 2.1).51  The gold standard method of obtaining information on potential donors is by prospective audit of all in hospital deaths; however, with more than 150,000 deaths annually in Canadian hospitals,52 it is extremely challenging to obtain this information on an ongoing basis.  25  These audits are performed periodically in different Canadian regions, 53 but are intermittent, costly, and not standardized between provinces. For example, a different estimate of potential donors would be generated if only individuals referred to an organ procurement organization were considered for chart review, versus all individuals who died in hospital.  In order for a potential donor to become an actual donor, the potential donor needs to be identified, and then undergo formal medical assessment to confirm eligibility for organ donation. Finally, consent for donation from the potential donor has to be established. Various metrics have been developed to measure health system performance in deceased donation based on the above process.   The objectives of this chapter are: 1) to develop a practical and timely method to estimate the number of potential deceased donors using information already collected for patients who die in Canadian hospitals; 2) to estimate the accuracy of this study method to identify potential deceased donors; and 3) to compare the number of potential deceased donors identified by the study method with the number of actual deceased donors to determine the conversion ratio of potential donors to actual donors.  2.2  Methods  This is a retrospective analysis of all in-hospital deaths captured in the Discharge Abstract Database (DAD) between April 1, 2005 and March 31st, 2009. The DAD contains demographic, administrative and clinical data for all acute care hospital  26  separations, excluding emergency room admissions, and still births for all provinces and territories, excluding Quebec.54 Diagnostic and procedural information in the DAD is recorded in a standardized format using International Statistical Classification of Diseases, 10th Revision, Canadian enhanced version (ICD-10-CA) and Canadian Classification of Health Intervention (CCI) codes54.   2.2.1 Identification of potential donors The primary outcome measure, the number of potential deceased organ donors, was determined using a unique study method based on previous work from Australia by Holt et al,55 that defined a limited number of International Classification of Diseases, Ninth Revision, Clinical Modification  (ICD-9-CM) codes that were prevalent among organ donors. These ICD-9-CM codes are also frequently recorded in the hospital separation records of Canadian organ donors56. For the purposes of this analysis, the Canadian Institute for Health Information supplied a mapping of ICD-9-CM codes specified by Holt et al to ICD-10-CA codes recorded in the DAD. The list of ICD-10-CA codes used to identify included causes of death are listed in Appendix B.  Figure 2.1 provides an overview of the study method used to identify potential donors. ICD codes, equivalent to those published by Holt et al,55 were used to identify a sub-group of patients who died in hospital with diagnoses compatible with organ donation. We further excluded individuals with absolute and relative contraindications to donation (e.g. metastatic cancer or seropositivity for human immunodeficiency virus), based on a  27  list of ICD codes described by the Canadian Standards Association (Appendix C).10 With the understanding that donation is highly unlikely unless patients have access to critical care services, we further restricted our identification of potential donors to individuals for whom there was a CCI code for mechanical ventilation. As only a small proportion of in-hospital deaths in individuals aged >70 years are eligible for donation, the primary analyses were restricted to hospital deaths in patients aged ≤70 years.57 The number of potential donors was calculated overall, by age group, by gender and by province.    2.2.2 Accuracy of the study method estimates To determine the accuracy of our potential donor estimates, we compared the number of potential donors identified in a chart audit of in-hospital deaths in six greater Winnipeg area hospitals during the study time frame with the estimated number of potential donors in the same hospitals identified in the DAD using the study method. These estimates were compared overall and by age group. The identified potential donors from each method were not linkable at the patient level, and thus it is not possible to determine if the cases did or did not represent the same patients in both cohorts.  2.2.3 Conversion of potential donors to actual donors The donor conversion ratio represents the number of potential donors who become actual donors (actual donors ÷ potential donors). We compared our estimates of the number of potential organ donors in the DAD with the number of actual organ donors recorded in  28  the Canadian Organ Replacement Register (CORR) in the study period, to calculate the donor conversion ratio. CORR receives information annually for all deceased organ donors in Canada, directly from provincial or regional organ procurement organizations57. CORR defines an actual deceased donor as an individual from whom ≥ 1 organ is transplanted.  Actual donors from CORR were not directly linkable to potential donors identified in the DAD.  Donor conversion ratios were calculated by age group, by gender and by province. Provincial donor conversion ratios were standardized for age distribution using direct standardization.  All analyses were performed using SAS 9.4 (Carey, NC).  2.3 Results There were 335 793 in-hospital deaths captured in the DAD during the study period. After excluding 228 800 patients aged > 70 years, 80 820 patients without diagnostic codes consistent with organ donation, 11 353 patients with absolute or relative contraindications to organ donation defined by the Canadian Standards Association standards, and 6 546 patients without an intervention code for mechanical ventilation, we identified 8 274 potential donors. The potential donors represented 2.5% of all deaths among hospitalized patients during the study period (Figure 2.1).     29  Table 2.2 shows the number of in-hospital deaths in different age groups, and summarizes the number of patients remaining after each step in our algorithm identifying potential donors. The proportion of potential donors among all individuals who died in hospital ranged from 5.8 % among patients 61-70 years to 19.5%, among patients aged 18-40 years. Potential donors were disproportionately male; among all individuals who died in hospital, 2.9% of males were identified as potential donors, compared to only 2.0% of females.  2.3.1 Accuracy of the study method estimates The chart review of 10 573 patients who died in greater Winnipeg area hospitals from 2005 –2009, identified 126 potential donors (Table 2.3), among whom 52 individuals were actual organ donors (Table 2.3). Application of the study method identified 266 potential donors from the same hospitals in the same time period, indicating the study method overestimates the number of potential organ donors by approximately two-fold.  The overestimate of potential donors using the study method was similar across years (Table 2.3), but was exaggerated with the increasing age of individuals who died in hospital (Table 2.4).  2.3.2 Conversion of potential donors to actual donors There were 1 209 actual deceased organ donors aged ≤ 70 identified in CORR during the study period - producing an estimated overall donor conversion ratio of 15% (1 209  30  actual ÷ 8 274 potential donors). The donor conversion ratio varied by age, ranging from 5% in patients aged 61-70 years to 43% among patients < 18 years of age (Table 2.5). Females had a higher donor conversion ratio (19%) compared to males (14%). Information on actual donors was not available for the intersections of age group and gender so these ratios were not age-standardized. Figure two shows that the provincial age-standardized donor conversion ratios ranged from a low of 11% in British Columbia, to a high of 21% in Saskatchewan.   2.4  Interpretation This study provides a method to estimate the number of potential deceased organ donors and the conversion of potential donors to actual donors using pre-existing administrative data.  Overall, 2.5% of individuals who died in hospital (7.7% of all patients aged ≤ 70 years) were identified as potential organ donors.  A comparison of the study method to the gold standard method of identifying potential donors by chart audit showed that the study method overestimated the number of potential donors by a factor of approximately two.   However, even after accounting for this overestimation, the results suggest there is significant potential to increase deceased organ donation in Canada.  The conversion of potential donors to actual donors was highest in younger age groups, and females; there was a two-fold variation in the age-standardized conversion ratio of potential donors to actual donors between provinces. Compared to the deceased donor rate per million population, the estimate of potential deceased donors and the donor conversion ratios in  31  this study provide significantly more information that may prove useful in improving the delivery of deceased donor services in Canada.   Our findings extend recent observations showing low organ procurement rates among potential donors in the province of Ontario,58 but differ from recent findings in a study from Calgary suggesting few critically ill patients with severe brain injuries qualify as potential donors. 59 However, the Calgary study relied on electronic charting of a neurological diagnosis of brain death to identify potential donors, and it was unclear how often patients were in fact evaluated for neurologic brain death, or how complete the capture of brain death diagnoses were in the electronic charts included in the study.59 Our study method, which does not require a neurologic diagnosis of brain death to identify potential donors, provides a more comprehensive estimate of potential deceased donors in Canadian hospitals, including individuals who would meet criteria for neurological brain death as well as those who may qualify for donation after circulatory death. Donation after circulatory death comprises fifteen percent of deceased organ donors in the United States60 and forty-three percent in the United Kingdom.61 Although organ donation after circulatory death varies between provinces, the most recent CORR data indicates that such donors comprised more than twenty percent of all donors in Ontario and Quebec in 201262 – indicating that methods to estimate potential donors should ideally not be restricted to neurologically brain dead donors.    Importantly, the study method of estimating potential donors does not obviate the need for detailed chart audits in Canadian hospitals. The study method is based on ICD codes,  32  the recording of which may vary in accuracy and completeness. We propose that chart audits, such as that from Winnipeg in this study, be used to estimate the accuracy of the study method in different regions. In fact, we are currently working with BC Transplant and the Canadian Institute for Health Information to further validate this work. The proposed validation in BC will be able to directly link patients in the provincial chart audit, with patients in the DAD, and allow for determination of sensitivity and specificity of the study method in this region. Determination of the accuracy in different regions could be used to modify the study method to improve the comparability of estimates between different regions, while periodic validation exercises could also be used to longitudinally monitor the accuracy of the study method. Hospital chart audits are also necessary to understand the reasons why potential donors are not converted to actual donors, which may include failure to identify potential donors or failure to obtain consent for donation. Importantly the DAD excludes deaths in outpatient hospital areas as well as in emergency rooms, and thus potential donors in these settings are not captured by the study method.  The major strength of the study is that it provides a feasible strategy to estimate the number of potentials donors in all Canadian provinces included in the DAD.  In contrast to the donor rate per million population, the study method provides information that is insensitive to regional and secular variations in hospitalized mortality, and provides an estimate of the potential to increase deceased organ donation. Although hospital chart audits are acknowledged as the best method to obtain information regarding potential organ donors, such data are self-reported by hospitals, collected by multiple abstractors,  33  and not standardized between regions. These limitations together with the cost and workload required to perform chart audits, make it unlikely that this source of information will be longitudinally available in most provinces on an ongoing basis.  Therefore, the study method represents a pragmatic solution to the need for comprehensive and timely information regarding deceased organ donation activity in Canada. We are currently working with the Canadian Institute for Health Information and the CORR Board to annually report the number of potential donors estimated by the study method along with donor rate per million.   Importantly, we were not able to link individual actual donors in CORR with potential donors identified in the DAD. Therefore, it is not clear if all actual donors are identified as potential donors using the study method, or if misclassification exists. In addition, we were also not able to link individuals in the Winnipeg chart audit with individuals in the DAD. The ability to do so may provide greater information about which information in the DAD could be used to refine our estimates of potential donors. A future step would be to determine the donor conversion ratios within provinces for different subgroups, such as age and gender, in order to determine whether the provincial differences are consistent across subgroups. This could target education strategies to increase deceased donation.  In conclusion, the study identified 2.5% of patients dying in Canadian hospitals as potential organ donors. The number of actual donors was only 15% of the estimated number of potential donors.  Although the study method likely overestimates the number  34  of potential organ donors by more than two-fold, there is still significant potential to increase deceased organ donation in Canadian hospitals. For example, if the true conversion ratio was closer to 30% (i.e. two times 15%), 70% of potential donors would still not proceed to donation. Estimating the number of potential deceased organ donors from data already collected from hospital separations represents a feasible strategy to obtain information needed to inform improvements to the deceased organ donation system in Canada.       35  Figure 2.1. A flow chart describing the study method used to estimate the number of potential deceased organ donors  Figure 2.2. Potential donors, actual donors and the age-standardized donor conversion Ratio by province of transplantation    0 5 10 15 20 25 0 1000 2000 3000 BC  AB  SK   MB  ON  NS   % Number of Donors Province Potential Donors Actual Donors Donor Conversion Rate In-Hospital        N=55,610   N=37,385  N=16,918  N=19,666  N=161,384  N=44,227    Deaths  36  Table 2.1. Regional metrics for death and deceased organ donation  Donor rate per million population (2012)a Crude death rate per thousand population b Study method donor conversion ratioc Canada 15.5 7.3 15.0e British Columbia 15.5 6.9 11.2 Alberta 15.1 5.9 13.1 Saskatchewan 5.6 9.0 20.9 Manitoba 9.5 8.5 17.3 Ontario 18.7 7.2 16.9 Quebec 14.9 7.3 N/A Nova Scotia 15.5d 9.4 20.3d New Brunswick  9.0  Newfoundland  9.3  Prince Edward Island  8.6  a Data from Canadian Institute of Health Information/ Canadian Organ Replacement Register 2014 b Data from Statistics Canada 2010 c Donor conversion ration obtained using actual donor from Canadian Organ Replacement Register and potential donors identified in the Discharge Abstract Database using the study method d Includes New Brunswick, Newfoundland, Prince Edward Island e Excludes Quebec     37  Table 2.2. The identification of potential donors by age group using the study method  Age Group (years)  <18 18-40 41-50 51-60 61-70 All in-hospital Deaths (N) 6 267 6 381 12 942 29 814 51 589 Without contraindication to transplantation**  971 2 632 3 756 8 057 15 911 Medical diagnoses compatible with organ donation***  570 1 742 2 088 3 876 6 544 Potential organ donors  (i.e. mechanically ventilated patients)   419 (6.7%)* 1 245 (19.5%) 1 381 (10.7 %) 2 232 (7.5%) 2 997 (5.8%) * Percentage of in-hospital patient deaths identified as potential donors by the study method. **Appendix B  *** Appendix A  Table 2.3.  Number of potential donors identified by chart audit and study method in Winnipeg area hospitals compared to actual number of donors  Potential Donors Actual Donors Fiscal Year Chart Audit of Winnipeg Hospitals Study Method Ratio  (Study method: chart audit) Canadian Organ Replacement Register 2005 -2006 27 59 2.2 10 2006 -2007 30 61 2.0 12 2007 -2008 37 76 2.1 14 2008 -2009 42 70 1.7 16 Total 126 266 2.1 52     38  Table 2.4. Number of potential donors identified by the chart audit and study method in Winnipeg area hospitals by age at death. Age Chart Audit Study Method Ratio (Study Method: Chart Audit) <18 years 11 14 1.3 18-40 years 39 44 1.1 41-50 years 26 53 2.0 51-60 years 29 67 2.3 61-70 years 18 88 4.9 Total 123* 266 2.2 *3 individuals missing age data  Table 2.5. The conversion of potential donors to actual donors by age group  Age Group N <18 18-40 41-50 51-60 61-70 Potential  donors 419 1 245 1 381 2 232 2 997 Actual Donors 181 322 281 285 140 Donor Conversion Ratio 43% 26% 20% 13% 5%     39  3 The ethics of deceased donor kidney allocation 3.1 Principles The early allocation of medical resources, such as in war times, was based on triage whereby patients with the greatest expected benefit would be treated first63. Now, in an era of evidence informed practice, there is an eagerness to use objective measures to allocate resources fairly with the greatest benefit.64 Although competing theories exist, in democratic nations, such as Canada and the United States, the allocation of deceased donor organs has been founded on the principles of autonomy (patient choice), fidelity (keeping commitments), veracity, transparency, utility and justice.25 These former five principles should underlie or constrain any allocation policy. Thereafter, the latter two principles (utility and justice) can be incorporated, and are the primary factors guiding allocation policies for deceased donor organs. Utility and justice are constantly being pitted against one another in an effort to achieve a balance in allocation priorities that is acceptable to all stakeholders (transplant candidates, donors and their families, and the public).   For non-renal organ failure (e.g. heart, lung, liver), deceased donor transplantation is the only (or significant) long-term treatment and the sickest patients are prioritized. In contrast, ESRD patients can be treated chronically with dialysis or living donor transplantation and can wait years for deceased donor kidney transplantation. In this context, the competing and complementary roles of utility and justice in the allocation of deceased donor kidneys is different from other solid organs and the following chapters  40  will be restricted to the exploration of these principles as related to deceased donor kidneys. 3.1.1 Justice In the transplantation ethics literature justice refers to ‘equal treatment of people so as not to advantage or disadvantage any group’ .26 Equal treatment here is taken to be equity of access to transplantation, where access is proportional to the medical need of the patient.65 Some authors believe that organ allocation policies should diverge from equal access ONLY where there are substantial differences in patient benefit ,66 however, ‘substantial’ has not been quantified. Examples of unequal (i.e. especially high) medical need are: 1) a patient who cannot access another form of treatment, and will therefore die imminently without transplantation, or 2) a pediatric patient who will suffer developmentally without transplantation.  Inequities in access to transplantation exist in deceased donor kidney allocation. For example, certain blood types and rarer genetic profiles are common amongst racial-specific candidate groups, but are less common among deceased donors, and therefore some racial groups have inevitable inequity in access to transplantation. In addition, candidates who are sensitized (i.e. will mount an immunologic response to a large proportion of the donor pool), are less likely to find an acceptable donor match and thus have inequitable access to transplantation. Allocation policies strive to achieve justice for these patient groups, including registries for highly sensitized patients, but are not sufficient to overcome these biologic barriers.  41  3.1.2  Utility In the transplantation ethics literature utility refers to medical utility. Medical utility has been defined solely with respect to the transplant candidate as ‘maximizing the welfare of patients suffering from end-stage organ failure’ ,66 and with respect to the deceased donor organ and transplant candidate in tandem as ‘making optimal use of the resources so that the greatest total benefit is obtained’ .26  These definitions differentiate medical utility from social utility, which would rank eligible candidates for transplantation based on their potential to benefit society or the greater good. A comparable task was undertaken at the University of Washington in the 1960s when the allocation of scarce hemodialysis machines was determined by an anonymous public ‘representative’ committee who ranked patients with kidney failure based on social and health determinants.67  For example, the committee decided that a young, male, businessman was considered to have greater social worth than a housewife; and an aircraft worker with six kids was voted to have greater social worth compared to a professional with two kids. As a result the businessman and aircraft worker were offered the elusive dialysis treatment, while many others were denied.   Deciding the potential worth of an individual is controversial, and may lead to greater disutility if included as a factor in allocation.25  In addition, the consideration of social utility in allocation would undermine any sense of justice. Therefore, in this thesis the definition of utility is restricted to medical utility and defined by: the optimal use of deceased donor kidneys, with maximal recipient survival with a functioning deceased donor kidney allograft.  42  3.1.2.1 Measures of utility The medical utility of deceased donor kidney transplantation can be measured by the following: 1) patient survival after transplantation, 2) deceased donor kidney survival after transplantation, 3) patient death on the kidney transplant waiting list, 4) patient quality of life, and 5) wasted organ function (i.e. loss of potential kidney function that occurs when the transplant candidate dies with a functioning kidney).68 These outcomes can be measured in isolation or in combination using different metrics. The first three outcomes can be measured by estimating group life expectancies, or death/failure rates. This can be done in a number of ways. For example, one could use median expected survival, mean survival (area under the survival curve) or mortality rate per 100 patient years.31  The fourth metric of utility, quality of life, is commonly measured using quality adjusted life years. Quality of life is difficult to measure objectively because its significance varies between individuals, and it is also difficult to quantify.  Importantly, it may be equally weighted with the extension of patient life as a reason for pursuit of transplantation. A final metric that combines all four outcomes is life years (gained) from transplantation (LYFT)- the additional years of life a patient is expected to live with a transplant compared to remaining on dialysis (see LYFT, described in Chapter 4.31 The final utility measure of organ waste is more difficult to measure. A method to measure organ waste will be described in Chapter 5.  Integrating rules into allocation algorithms with the intent of increasing these measures of utility without consideration of justice may lead to greater inequity in access to transplantation amongst groups with less favourable expected utility outcomes. In  43  addition, it is most often the positive components of utility that are examined (e.g. allocating kidneys of higher quality to candidates with longer expected survival after transplantation), thus ignoring the disutility that may occur when less healthy candidates receive transplantation from poorer quality kidneys. For example, lower quality kidneys reduce recipient survival with a functioning graft69 and also shorten recipient survival compared to transplantation with higher quality kidney.70  3.2 Examining utility through different lenses Optimizing the use of deceased donor kidneys while maximizing the benefit and minimizing the harm to the transplant candidate population is the common overarching utility goal of deceased donor kidney allocation. However, the operational definitions of these concepts may conflict for different stakeholders, and should be integrated when formulating decisions about which quality deceased donor kidneys should be allocated to different transplant candidates. This section describes my assessment of the considerations for offering and accepting deceased donor kidneys for various players. 3.3 Transplant candidates Eligible transplant candidates make an informed decision to be added to the deceased donor kidney waiting list. As such we can assume that transplantation is their preferred treatment.  However, various considerations apply from the patient perspective when determining what quality of kidney a patient would be willing to accept. Here, quality  44  refers to the expected survival of the deceased donor kidney1. Some transplant candidates may wish to wait longer to receive a deceased donor kidney that will maximize their total expected survival, while others may be willing to trade future life years for immediate quality-improved years.71 Parfit’s claim about compensation72 argues that ‘one’s burdens are not compensated for by benefits provided for someone else’, but candidates may be willing to accept a lesser quality kidney that meets their needs, perhaps at the expense of increased waiting time, in order to allow another patient to benefit from a higher quality deceased donor kidney.39  A patient’s choice in accepting or declining an offer of transplantation from a given quality deceased donor kidney can be described by the candidate’s:  1) Likelihood of accessing transplantation (surviving the waiting time) 2) Life expectancy after transplantation, and 3) Quality of life (with and without transplantation). 3.3.1 Likelihood of accessing transplantation Likelihood of accessing transplantation is a continuous concept composed of three components: 1) the candidate’s risk of death on the transplant waiting list , 2) the candidate’s probability of finding a compatible deceased donor kidney, and 3) the average waiting time in the candidate’s region of wait-listing. An individual who has a high risk of death on the waiting list, or one who has a low probability of finding a donor match is unlikely to access transplantation (poor access), while a healthier individual with                                             1 The quality of a deceased donor kidney may also refer to the risk of unknown comorbidities such as HIV or hepatitis. Complete knowledge about donor health is not always available for donors that die quickly upon arrival in hospital. Laboratory test results to rule out more serious comorbidities may take time, and    45  a high probability of finding a donor match is likely to access transplantation (good access). Access to transplantation is not directly related to time spent on dialysis. For example, a patient with poor access due to a low deceased donor kidney match probability will most likely spend more time on dialysis compared to a patient with poor access due to a high likelihood of death on the waiting list. Therefore, patient utility factors related to dialysis (i.e. quality of life) are independent from access to transplantation, and need to be considered separately.   Geography is another factor impacting the likelihood of accessing deceased donor transplantation. The rates of deceased donation vary regionally across Canada,51 as well as in the United States.50 Importantly, in the United States transplant candidates can be wait-listed for kidney transplantation at multiple centres simultaneously, whereas in Canada candidates can only be wait-listed in one province at a time. The implications of multiple wait-listing as a strategy to increase likelihood of access transplantation will be explored in the United States in Chapter 8. 3.3.2 Life expectancy after transplantation Life expectancy after transplantation is a continuous concept representing the predicted years of survival a given candidate will realize if they are successfully transplanted. This concept is correlated with the requirement for repeat transplantation. For example, a candidate with a long life expectancy is likely to outlive their graft, return to dialysis and require repeat transplantation. Thus, all candidates will need to consider not only their risk of graft failure with deceased donor kidneys of different qualities, but also their  46  future likelihood of repeat transplantation.  Repeat transplantation is not without surgical risk, and candidates will be more highly sensitized after transplantation, decreasing their likelihood of another match and thus reducing their access to future transplantation. Therefore, it may be in the best interest of a candidate with longer life expectancy to refuse a poorer quality kidney and wait on dialysis for a deceased donor kidney with a longer life expectancy.  3.3.3 Quality of life Quality of life is defined as ‘an individual’s perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns’.73 The definition includes consideration of psychological and physical health, independence, and social and spiritual environment.73 Therefore, quality of life on dialysis relative to living with a transplant varies significantly between individuals. Several factors may lead to an individual’s determination of their quality of life; only a couple of possibilities are described here. First, this could depend on the level of independence and freedom an individual felt prior to requiring dialysis. For example an able-bodied, active or jet-setting patient who suddenly requires long, restrictive in-hospital dialysis sessions three times per week may feel more burdened by the change in lifestyle, compared to a less active individual or a lonely individual seeking socialization. Another factor may be the level of comfort a patient feels with the medical aspects of the treatment (e.g. needles, hospitals).  Patients will need to consider quality of life on dialysis prior to transplantation, as well as quality of life after transplantation, including time back on dialysis after graft failure.9, 74  47   It is not possible to predict the importance of each of these concepts in the evaluation of utility for each candidate. Nevertheless, an exploration of the important determinants is discussed below (Figure 3.1). Note, this thought experiment does not consider: 1) medically urgent candidates who are unable to be treated with dialysis and thus require immediate transplantation, 2) pediatric candidates in whom transplantation may impact physiologic or anatomic development, nor, 3) differences in surgical risk for transplantation (assumed to be low for all candidates).  Figure 3.1 panel A gives a simplified description of characteristics of transplant candidates that might occur in the intersection created by combining and dichotomizing the continuous concepts of access to transplantation and life expectancy. (Quadrant I: age 25, blood type A; Quadrant II: age 25, blood type B; Quadrant III: age 60, blood type B; Quadrant IV: Age 60, blood type A) Figure 3.1 Panel B shows the intersection of access to transplantation and life expectancy, stratified for two extremes of quality of life on dialysis. Figure 3.1 Panel B shows that for the highest quality of life on dialysis patients in quadrant I would be tempted to wait for a pristine deceased donor kidney because they will likely receive an offer for transplantation quickly, and want to maximize their graft survival because they have a long life-expectancy. In contrast, the candidate in quadrant 3 would be tempted to take the first offered deceased donor kidney because they will likely not receive another offer, either because of their low likelihood of finding a match, or because of their poor life expectancy. Candidates in quadrants II and IV can take a slightly more selective approach, perhaps only reneging offers of the poorest quality  48  deceased donor kidneys. As quality of life on dialysis deteriorates (Figure 3.1 Panel B), all candidates may persuade themselves to accept a wider range of quality deceased donor kidneys to offset increased time waiting on dialysis. In this example, the healthiest candidates with good access, may no longer wait for an ideal deceased donor  kidney, but might only refuse the lowest quality deceased donor  kidneys; and candidates with either poor access or poor life expectancy would be more apt to accept a wider range of deceased donor  kidneys quality. The candidate’s decision making for accepting a deceased donor kidney of different quality will depend on where they are positioned in the 3-dimensional continuum of these factors.  3.1.2.2 The policy maker Similar to the transplant candidate, utility from the policy maker perspective depends on the overarching goal. If the primary goal is saving lives, then deceased donor kidneys would be prioritized to patients with medical urgency (unable to undergo dialysis) or pediatric patients for whom transplantation drastically improves neurologic and physical development. These patients are currently prioritized in North American allocation systems and are not considered in the discussion below. Therefore, this section discusses other outcome goals such as: short term patient survival (e.g. avoidance of acute rejection), total life years gained from transplantation, total years of graft life, total number of patients transplanted or total quality adjusted life years. It may be argued that the first priority from the policy maker perspective is to get the most use (i.e. graft survival) out of each deceased donor kidney donated. That is, the focus should be on reducing the waste of kidneys that occurs when these kidneys are transplanted into  49  candidates with a life expectancy that is shorter than that of the kidney they received. In theory, transplanting all deceased donor kidneys into transplant candidates with the greatest life expectancies would minimize kidney waste. It has been suggested that there may be an interaction between recipient and deceased donor kidney life expectancies, such that the youngest recipients may use up the graft life of their deceased donor kidneys more quickly (i.e. due to physiologic stress placed on the kidney by the active immune system of the younger recipient), thus reducing the total graft survival of older kidneys.75 Although this hypothesis was not supported in a large American cohort study,33 if an interaction does exist, deceased donor kidneys should be transplanted into candidates who will realize their maximum benefit.   Efficient allocation (better use of deceased donor kidneys) will also result in improved patient outcomes. For example, in the European transplant program preferentially allocating lower quality deceased donor kidneys (age ≥65) to candidates with shorter life expectancies (age ≥ 65) has been proven to decrease the rate of discard of these older kidneys by facilitating their acceptance.76 This has resulted in more candidates receiving kidney transplantation.  In addition, this “old” to “old” prioritization has led to reduced time between organ retrieval (i.e. organ surgically removed from the donor) and transplantation as well as delayed graft function (often defined by a requirement of dialysis in the first week after transplantation). These factors are related to the health of the graft, and their reduction is associated with improved recipient survival.76 After constraining allocation policies such that the potential waste of deceased donor kidneys is avoided, the policy maker will want to ensure that other utility measures are  50  maximized. Measuring the total utility of different strategies will depend on perceived benefit. A solution that optimizes short-term patient survival (e.g. matching genetic tissue) for the candidate population, may compromise total population survival or quality of life.  With continued advancements in short-term transplant survival, the focus on maximizing longer-term outcomes will probably be more heavily weighted. The determination of which long-term measure to highlight at this level is most likely subjective.  In contrast to transplant candidates, whose focus is primarily on individual benefit, policy makers focus on the benefit to the system or the entire transplant candidate population. 3.4 Summary Two ethical principles jockey for their place in the allocation of deceased donor kidneys. Justice, defined in this thesis as equitable access to transplantation, refers primarily to the selection of candidate subgroups for transplantation (i.e. justice determines the likelihood with which different candidate subgroups will be offered transplantation). Utility, defined in this thesis as reducing organ waste while maximizing patient outcomes, refers more so to the optimal distribution of deceased donor kidneys to these candidates. The definitions of justice and utility discussed in the remainder of this thesis are from the perspective of the policy maker, with consideration of the value of different utility outcomes for individual candidates.    The roles of utility and justice in deceased donor kidney allocation have been dynamic over time. The following chapters discuss the roles of utility and justice in historical and  51  current deceased donor kidney allocation.  Figure 3.1. A description of the intersection of life expectancy, access to transplantation, and quality life from the transplant candidates perspective.        52  4 The allocation of deceased donor kidneys for transplantation 4.1 Overview In the 1970s and early 80s, clinical transplantation was in its infancy and graft and patient survival outcomes following deceased donor kidney transplantation were mediocre (i.e. five year combined outcome of graft or patient survival <50%).77  Use of kidney transplantation as a therapy was therefore reserved for young, otherwise healthy patients who were expected to have superior survival 27. At that time, few patients were waiting for transplantation and deceased donor kidneys were allocated to obtain optimal outcomes by matching transplant candidates to donors with the most genetically compatible tissues.78 As a result of advances in immunosuppression therapy in the mid-80s and 90s, rates of acute and chronic graft rejection decreased, resulting in increases in short-term graft and patient survival (American graft and patient survival in 2010: one year 95% and 96%; five year 84% and 86%).15 As a result of these advances, kidney transplantation is no longer reserved for the healthiest patients, but is considered a viable treatment for most ESRD patients, including those of advanced age or with comorbid diseases. In fact, the relative benefit of transplantation is greater in patients with disease conditions such as diabetes who do very poorly on dialysis. In particular, there is no absolute age restriction for transplantation, and many of the sickest patients (e.g. diabetics) derive the greatest relative survival benefit from kidney transplantation, because their dialysis survival is limited. 28    53  The liberalization of transplant eligibility combined with an increased prevalence of ESRD has created the current situation where the number of ESRD patients who could benefit from transplantation exceeds the number of kidneys available for transplantation- resulting in a waiting list. In Canada, there are close to 6 000 incident ESRD patients annually (a 20% increase since 2000);3, 79 and more than 3 400 prevalent ESRD patients in 2012 were on a Canadian waiting list for kidney transplantation.80 Comparatively in the United States, there are close to 115 000 incident ESRD patients annually and more than 100 000 prevalent patients awaiting kidney transplantation.81 As a result of this inequality between supply and demand, many transplant programs in different countries have shifted their focus in allocation away from utility to increased equity.    The expanded eligibility criteria for deceased donor kidney transplant candidates, has created the need to utilize every organ that can be safely transplanted. This has led to a liberalization of donor acceptance (i.e. older donors or donors with greater comorbid burden). Deceased donors that previously may not have been considered for transplantation are now routinely used.76  In 2011, more than 40% of Canadian deceased donor kidney transplant recipients were aged ≥60 years (compared to 27% of recipients aged ≥60 years in 2003) , and 25% of deceased donors were aged ≥ 60 years (compared to 20% of deceased donors aged ≥ 60 years in 2003).3  Despite this increase in expanded criteria donors, there remain only about 750 deceased donor kidneys available for transplantation per year;3 only enough to transplant roughly 20% of current wait-listed patients.    54  Patient (recipient) life expectancy varies by transplant candidate case-mix, and many older transplant recipients die with a functioning kidney. The current justice based allocation system allows the transplantation of candidates with deceased donor kidneys that either do not function long enough to treat the patient for the remainder of their lifetime, or would be expected to function longer than the patient’s life expectancy.  Some countries have explored matching candidates and deceased donor kidneys with similar life expectancies, in an effort to increase the utility of the available donor pool and these approaches are described below. 4.2 Eurotransplant Senior Program Eurotransplant is the organization responsible for facilitating allocation and ‘cross-border exchange’ of deceased donor organs in eight counties: Austria, Belgium, Croatia, Germany, Hungary, Luxembourg, the Netherlands and Slovenia) .82 Eurotransplant is responsible for a population of close to 120 million, 100 000 of those have ESRD, and close to 12 000 patients are wait-listed for deceased donor transplantation. In January 1999, in response to an increasing number of elderly transplant candidates on deceased donor kidney waiting lists, Eurotransplant established the Eurotransplant Senior Program (ESP) as a means to increase transplantation for elderly candidates.83 ESP is intended to facilitate the matching of the shorter life expectancies of older deceased donor kidneys (age ≥ 65 years) and older transplant candidates (age ≥ 65 years).   Enrolment in ESP for the allocation of deceased donor kidneys aged ≥ 65 years was voluntary by center in the first two years, but became mandatory in 2001. Meanwhile,  55  transplant candidates aged ≥ 65 years have the option of enrolling in either ESP for prioritized access to donor kidneys aged ≥ 65 years, or in the Eurotransplant kidney allocation scheme where they will compete for deceased donor kidneys with all other candidates.82, 84 In ESP, allocation is restricted within close regions by blood type and waiting time alone with the goals of: 1) increasing the utilization of older donor kidneys, 2) decreasing time to deceased donor kidney transplantation for older candidates, and 3) ensuring graft and patient outcomes after transplantation are not negatively impacted.76  The outcomes of ESP after five years were positive: the number of deceased donors aged ≥ 65 years doubled, waiting times for deceased donor kidney transplantation among ESP recipients decreased, and recipient (age ≥ 65 years) survival was similar with deceased donor kidneys aged ≥ 65 years and < 65 years.76 4.3 Changing a deceased donor kidney allocation system- An American narrative 4.3.1 Allocation prior to 2014 In the United States prior to 2002, the acceptability of different quality deceased donor kidney for transplantation was decided by physicians and individual organ procurement organizations. In October 2002 the expanded donor criteria program was established with the mandate of classifying and allocating poorer quality kidneys.85 The objectives of the expanded criteria donor program were: 1) to decrease the number of marginal quality kidneys that were retrieved (removed from the donor for transplantation), but then discarded prior to transplantation (i.e. to reduce the number of wasted kidneys), and 2) to increase system efficiency by facilitating the allocation of these kidneys such that the  56  time from retrieval to transplantation would be minimized, and graft survival would be increased.85  With this program deceased donors in the United States were classified into two quality categories for the purpose of kidney allocation: standard criteria donors (SCD) and expanded criteria donors (ECD).  ECD kidneys by definition portend a 70% greater risk of graft failure compared to SCD kidneys,69 and are classified by a donor age ≥ 60 years, or donor age 50-59 years with at least two of the following comorbidities: a high donor serum creatinine, donor death due to cereberovascular accident or a donor history of hypertension. In practice, all non-ECD donors are considered SCD.86 A separate kidney transplant candidate waiting list exists for each type of deceased donor kidney. Transplant candidates can be on both waiting lists at the same time, but must give explicit consent to be a member of the ECD list. The intended recipients of ECD kidneys were candidates with poorer survival on dialysis, or candidates in regions with long waiting times on dialysis who would benefit from receiving such kidneys (i.e. kidneys at increased risk of graft failure), if they were transplanted faster and had less exposure to dialysis.16 The reduced waiting time on dialysis was expected to result from fewer candidates vying for transplantation from these ECD kidneys.  SCD kidneys are allocated first to candidates with perfect genetic tissue matches anywhere in the country. Allocation is then based on a system that awards prioritization points for a) pediatric candidates, b) time on the SCD kidney transplant wait-list, c) degree of genetic tissue mismatch, d) high sensitization (i.e. expectation of tissue incompatibility with a high percentage of deceased organ donors) and e) previous living donation.87 Of note, SCD kidneys aged < 35 are prioritized to pediatric recipients unless  57  they are promised to another candidate with perfect genetic tissue match. SCD kidneys are first offered locally, then regionally and nationally, except for perfect genetically matched kidneys as noted above.   In contrast, ECD kidneys are allocated within blood groups by waiting time alone.87 4.3.2 Need for change Over the last decade the difference between the number of wait-listed transplant candidates and the number of deceased donor kidney transplantations has widened.88 The current American kidney allocation system has neither minimized death on the kidney transplant waiting-list, nor maximized survival after transplantation.31 In 2004, the American organ procurement and transplantation network (OPTN) board of directors charged the OPTN kidney committee (OPTNKC) with reviewing the allocation policies for deceased donor kidneys. Particular concern was voiced about increasing utility of the current system, particularly by avoiding extreme age mismatches (or the allocation of deceased donor kidneys with long life expectancies into candidates with much shorter life expectancies).36 Members of the Scientific Register of Transplant Recipients collaborated with the OPTNKC to develop new tools for allocation that would increase the utility gained from transplanted deceased donor kidneys. During the multi-year review, the OPTNKC considered various proposals in conjunction with the members of the transplant community and other stakeholders. The review culminated with a proposal presentation of a new allocation policy (the Kidneys Allocation Score) at a public forum in St Louis, MO in 2009.89   58  During the development of the Kidney Allocation Score, OPTNKC was guided by the OPTN Final Rule- a regulatory framework implemented by the U.S. Department of Health and Human Services.64 The Final Rule states that the OPTN should develop policies for the equitable allocation of deceased donor organs that must 1) ‘be based on sound medical judgement’, 2) ‘seek to achieve the best use of donated organs’, 3) ‘be designed to avoid wasting of organs’, 4) ‘avoid futile transplants’ , 5) ‘promote patient access to transplantation’ and 6) ‘promote the efficient management of organ placement’.64  4.3.3 Kidney allocation score The primary proposal entertained and put forth by the OPTNKC was the Kidney Allocation Score (KAS). The goal of KAS was to ‘provide equitable access to deceased donor kidneys for all transplant candidates, while improving the outcomes of recipients of such kidneys’.90 Therefore, the KAS ranking system for priority for deceased donor kidneys contains components of both utility and justice. Three components (described below) are included in the calculation of KAS: patient life years (gained) from transplant, the donor profile index (which is used to estimate the organ quality and survival), and dialysis time. KAS is calculated so that deceased donor kidneys with the greatest expected survival (i.e. top 20%) are allocated to candidates with the greatest expected survival (i.e. top 20%), while deceased donor kidneys with lower expected lifetimes are allocated by the justice principle to candidates with the longest times on dialysis.   59  4.3.3.1 Life years from transplant- measure of deceased donor kidney transplant utility ‘Life years from transplant’ (LYFT) is the number of extra years of life a transplant candidate would be expected to live with a deceased donor kidney transplant compared to never receiving a transplant.8, 31, 91 Each candidate has a unique LYFT score based on his/her patient characteristics, for specified deceased donor kidney characteristics (e.g. the same patient would have a different LYFT score with two donor kidneys that differed by age alone). LYFT is intended to be calculated for matched candidates at the top of the deceased donor kidney waiting lists after a deceased donor kidney has been identified for transplantation. The concept of LYFT can be adjusted to account for differences in expected quality of life with and without a functioning transplant, using a fractional constant Q. LYFT is calculated in the literature with Q=0.8 as:  LYFT =     1.0 x (median expected lifetime of candidate with a functioning             transplant)             +     0.8 x (median expected lifetime of candidate after transplant failure) -  0.8 x (median expected lifetime of candidate without a transplant)31  4.3.3.1.1 LYFT methodology Estimates of kidney transplantation survival benefit prior to LYFT were biased, using referent populations of all dialysis patients.31 Transplant candidates are a highly selected ‘healthy dialysis’ population, and as such LYFT calculations use the more appropriate population of patients wait-listed for deceased donor kidney transplantation as a reference cohort. The three outcomes in LYFT (patient survival without a prior to transplantation, patient survival with a functioning transplant, and patient survival after transplant failure)  60  are estimated using separate adjusted Cox proportional hazards regression models.  Three methods were examined to estimate the lifetimes of particular candidates in each time period using the survival probabilities from the Cox models: 1) ‘expected lifetime’ (calculated as area under the survival curve), 2) ‘truncated expected lifetime’ (calculated as area under the survival curve limited to a specific time period, e.g. 10 years after transplantation), and ‘median lifetime or half-life’ (calculated as the time at which half the population has died).  The ‘expected lifetime’ method was abandoned because it could not directly estimate patient and graft survivals after the study end of follow-up (15 years) at which point many patients/grafts were still alive.  The ‘truncated expected lifetime’ method was able to be estimated with the data, but was rejected because it was believed that the loss of LYFT calculated after the truncated time would be differential in patients/ grafts with shorter versus longer expected lifetimes and thus bias LYFT away from the youngest and healthiest patients. As a result, the ‘median lifetime’ method was selected for final calculations of LYFT. Median lifetimes were able to be calculated up to 15 years for 99% of candidates without a transplant and 72% of candidates with a transplant. Estimates of LYFT in the remaining populations were calculated using extrapolation.  4.3.3.2 The kidney donor profile index In 2009, expanded criteria donors accounted for 16% of deceased donors in the US population.92 The use of a dichotomous classification for donor quality allows patients the opportunity to accept organs of lower quality in exchange for shorter waiting times to transplantation, and also allows for patient counselling about the risk of graft failure for a  61  given donor. Due to the limitations of a dichotomous classification, there was overlap in quality of kidney in each category (ECD/ SCD). In 2009, Rao et al93 developed a new and continuous score (the kidney donor risk index (KDRI_Rao)) to determine deceased donor kidney quality.  The KDRI_Rao is the relative hazard of graft failure for a given deceased donor kidney compared to a reference deceased donor kidney (brain dead donor, aged 40-years, non-African American race, serum creatinine =1.0, no history of hypertension or diabetes, cause of death not cereberovascular disease, height=170 cm, weight=80 kg, hepatitis C negative, 2 human leukocyte antigen (HLA) B mismatches2, 1 HLA DR mismatch with a cold ischemic time of 20 hours).  The index was developed using data from all (N=69,440) adult, first kidney-only deceased donor ABO compatible transplant recipients between 1995-2005 in the Scientific Registry of Transplant Recipients (United States).  The KDRI_Rao was modeled using a multivariate Cox regression stepwise deletion model. The baseline model included all recipient and deceased donor data available in the data set.   The OPTN has amended the KDRI_Rao to the KDRI_Median (KDRI), such that the reference deceased donor is the median quality donor. The KDRI is calculated as the KDRI_Rao using only donor factors divided by the median KDRI_Rao of the previous year. The KDRI is commonly reported as the Kidney Donor Profile Index (KDPI), a direct 1:1 mapping of the KDRI to the ranked percentile of deceased donors (i.e. the median donor would have KDRI=1.00 and KDPI=50%). A donor with a KDRI of 1.7                                             2 Human leukocyte antigens (HLA) are proteins found on the surface of cells of the body that are inherited genetically. HLAs are used to determine the biologic compatibility between a donor and recipient. In transplantation, 3 different loci are generally examined: A, B and Dr. Each of these loci has two antigens, representing a possibility of up to 6 different HLA mismatches per donor-recipient pair.   62  would have a 70% increased relative risk of graft failure compared to the median donor. Similarly, a donor with a KDPI of 80% would have a higher likelihood of graft failure compared to 80% of the donor population.  The KDPI has higher predictive ability compared to ECD, and is more discriminative because it is continuous and not dichotomous. This allows for the identification of higher and lower quality ECD kidneys; allowing for more efficient allocation of marginal kidneys.94  4.3.3.3 Dialysis time The third component accounted for in KAS is dialysis time. In current deceased donor kidney allocation in the United States, patient waiting time has been calculated as the time since referral for transplantation (i.e. placement on the waiting list). Waiting time is an objective measure, and the major tiebreaker for allocation based on justice. So as not to disadvantage patients who are referred for transplantation long after dialysis start, the time since the start of dialysis treatment (DT) is included as a modified component of the proposed allocation score.94 4.3.3.4 Criticisms of KAS and LYFT The primary advantage of including LYFT in deceased donor kidney allocation is the increased number of life years that would be gained with the same kidneys transplanted into different people.91 DT was included in KAS to offset the probable inequity in access to transplantation among patients with poorer expected survival after transplantation, and  63  the KDPI was included to calculate the life expectancy of deceased donor kidneys, to ensure that the healthiest kidneys would be allocated to transplant candidates with the longest life expectancies. Despite the utilitarian advantages of KAS, the allocation score has been strongly criticized.  KAS has been judged to be complex and non-transparent, making it difficult for patients and caregivers to predict how long patients will be required to wait on dialysis for transplantation, and which patients will be transplanted next.37, 90, 94, 95 One author predicts that KAS is more likely to change which candidates are transplanted, and not the quality of organ that a given candidate will receive.29 Also, it is unclear whether the transplant community should be responsible for making decisions about the allocation of a public resource.95   In addition to these valid concerns, the most widespread criticism about KAS has focused on the LYFT component. LYFT predicts population but not individual life years from transplant.29, 91  The LYFT models have been validated neither externally90 nor prospectively95 and their predictive power is low. Specifically, the ability of the LYFT models to discriminate between all candidates with different survival probabilities is poor (c-statistic3: 0.61-0.68),37, 90, 91, 94, 95 although LYFT is good at differentiating between candidates with the shortest and longest survival probabilities (c-statistic 0.83-0.91).91  Hippen et al95 predicts that the long-term use of KAS would result in a homogeneous candidate waiting list, where LYFT will be forced to choose between similar patients,                                             3 The c-statistic (or concordance statistic) is a measure of model discrimination. Traditionally, the c-statistic is used to determine the ability of a statistical model to assign a higher predicted value to a subject who experienced a dichotomous outcome compared to a subject who did not experience the outcome. In survival analysis, the c-statistic is extended to represent the ability of the model to assign higher predicted survival times to a subject with longer survival compared to a subject with shorter survival. In this example, the c-statistic is the probability of the model predicting a greater survival time in the subject with the longer survival time among all possible pairs in the model.   64  potentially encouraging gaming. That is, manipulating the waiting list to leverage access to transplantation for a patient (e.g. multiply wait-listing patients, wait-listing candidates prior to transplant suitability). The quality and definitions of the data elements in LYFT are limited because they are from administrative data.90, 95 Also, the addition of variables after the inclusion of age in the models only marginally improves prediction, but adds to model complexity.29 The LYFT models are dependent on the length of follow-up. Long time horizons are needed to show the added benefit of transplantation in the young and healthy, but longer follow-up biases against the older and sicker.90  In addition to the analytic exceptions to LYFT are some moral concerns. First, for non-renal organs survival is the primary goal of transplantation, whereas for kidney transplant candidates quality of life is of preeminent importance.37 Allocating kidneys based on life years gained from transplantation as opposed to gain in quality of life may not be appropriate. Second, each year after transplantation is given the same value in the LYFT models, but the first year of life after transplantation may not be equivalent to the 20th year of life after transplantation.95  Incorporating discounting into the measurement of LYFT may be valuable. Third, it is unclear how prioritizing kidneys for the young and healthy through LYFT will impact living donation.37, 90, 95 Fourth, LYFT does not account for patient preferences and autonomy over what quality of kidneys patients would be willing to accept.90 Fifth, LYFT focuses on only one side of increasing utility, maximizing life years post transplantation;  but there is no discussion about minimizing harm (e.g. inequity in transplantation, decreased post-transplant survival and increased waiting list deaths for certain patient groups).95    65   As a result of many harsh reviews of LYFT, the KAS was not supported as presented in St Louis, and the needs and wants of the community were discussed. Many in the community believe that a national, transparent and comprehensible system, able to incorporate change based on new data and outcomes is necessary.29, 94 Some suggestions to improve allocation have included wider geographic sharing of organs,32 allocating the youngest kidneys to the youngest candidates,32, 90 allowing candidates to indicate an acceptable range of kidney quality,90, 94 allocating the lowest 20% quality kidneys (using KDPI) to the highest 20% candidates (using LYFT),37 using estimated survival time instead of LYFT as a measure of transplant life expectancy,94 and limiting regression models for survival (such as LYFT) to three to four factors.32    4.3.4 2011 Proposed national allocation policy After the public forum in 2009, and feedback from transplant professionals, patients, donor families and the public, the OPTN Kidney Transplant Committee developed a new deceased donor kidney allocation proposal. This proposal was released in February 2011 with a request for comments. The three key limitations to the current allocation system stressed by the committee at this time were: high discard rates of poorer quality (ECD) kidneys, variability in access to transplantation by different candidate subgroups, and lack of matching the life expectancies of deceased donor kidneys to transplant candidates.  Age matching was a recommendation after the previous review and was incorporated into the new proposal.89   66   The 2011 proposed allocation first calculated the donor quality using the KDPI. If the KDPI ≤ 20% (i.e. the highest quality kidneys), then the kidney was allocated with priority to candidates with the highest 20% expected post-transplant survival (EPTS)4. Kidneys with KDPI > 20% were allocated with priority to candidates aged within 15 years of the kidney age (e.g. a 50 year old kidney would be allocated to a 35-65 year old recipient). Priority ranking within the two aforementioned priority groups was proposed to be similar to current allocation priorities. The 2011 proposed allocation was for kidney-only transplants and did not alter priority for multi-organ (e.g. kidney-pancreas) transplantations.   The OPTNKC performed simulations to determine if under the 2011 proposal certain groups would have disadvantaged access to transplantation compared to current allocation.35 Candidates were not differentially disadvantaged by blood group, or by race. However, fewer older candidates with diabetes and high sensitization were simulated to receive transplantation. A simplified alternative proposal dropped the special allocation by KDPI < 20%, and had all deceased donor kidneys being allocated by age matching (within 15 years). This alternative proposal showed similar results to the 2011 proposal, but was rejected for being less modifiable. It is believed that allocation priorities will need to be adjusted with constantly updated data and the mixed 2011 proposal allocating by life expectancies and by age matching was determined to be more flexible for future amendment.                                             4 The expected post-transplant survival is calculated using 4 variables: candidate age, duration of dialysis exposure (DT), diabetes mellitus as a comorbidity or cause of ESRD and whether candidate was a prior organ donor.  67  4.3.5 American allocation summary The United States Department of Justice determined that allocation of organs for transplantation based on age alone was discriminatory.96 Therefore, the 2011 proposal has since been revised. The latest version of the new allocation system, which eliminates age matching within 15 years, was approved in 2013 by the OPTN. This approved allocation maintains the proposed top 20% KDPI to top 20% EPTS, and broadens the geographic allocation of kidneys. For example, the most highly sensitized patients will now be offered kidneys from the national pool, and allocation for the lowest quality expanded criteria donor kidneys (KDPI > 0.85) will now be regional, as opposed to local. The SRTR/OPTN are currently disseminating information about the new allocation system, and enhancing their data collection. The new allocation model is expected to be implemented in December 2014. 4.4 Summary The growth in the number of patients with ESRD who would benefit from transplantation is remarkable. Despite ongoing efforts of programs to increase donation, and the expanded criteria for donors, the increase in deceased and living donation in the last decade has been minimal, and innovation is needed to address the widening gap between the demand for and supply of kidneys for transplantation. A consequence of long waiting lists for kidney transplantation, is that current allocation systems favour justice by heavily prioritizing patients who have been waiting the longest for transplantation. This practice may lead to discrepancies in donor kidney and candidate life expectancies (i.e. organ waste, or candidate need for repeat transplantation) (more detail provided in Chapter 5).   68  The use of age matching to increase utility in these justice-based systems has been explored in Europe and the United States. The Eurotransplant Senior program which began allocating donor kidneys aged ≥ 65 years to candidates aged ≥ 65 years in 1999 has been successful and is ongoing. In the United States, allocation of donor kidneys by age alone was rejected by the Department of Justice, despite public and medical support to include age matching in allocation algorithms. The new allocation system that will be implemented in the United States by the end of 2014 will maintain a component of age matching that will preferentially allocate the highest quality kidneys to the highest quality candidates (donor age and candidate age are the greatest predictors of donor kidney and candidate quality respectively). However, the exclusion of the 15-year age matching component from the 2011 proposal allows young candidates to elect to receive the lowest quality (i.e. oldest) kidneys. The potential impact of the policy allowing old to young transplantation in the United States will be explored in Chapter 7.      69  5 The type and quantity of inefficiency in donor-candidate age matching: measuring the area between the curves 5.1 Introduction Transplantation is the optimal treatment for patients with kidney failure, but the number of organs is not sufficient to transplant all patients who could benefit. Therefore, allocation rules dictate the method by which transplant candidates are offered kidneys for transplantation. Allocation rules with the intent of maximizing the use of the scarce resource would prioritize transplantation for the youngest and healthiest candidates, while a justice based system would prioritize candidates with the longest wait times on dialysis. The current allocation systems prioritize justice in candidate access to transplantation in this way by heavily weighting candidate time on the transplant waiting list. This justice-based allocation allows the possibility of system inefficiencies (i.e. discordance in the expected survival times of the transplant recipient and the deceased donor kidney). In contrast, allocation of organs by matching life expectancies of the donor kidney and recipient is an opportunity to decrease these inefficiencies (Figure 5.1).   A perfectly efficient system would allocate deceased donor kidneys to candidates such that the transplanted patient would outlive the kidney graft by one day 37. This ideal system would maximize the benefit to the population of transplant candidates by minimizing: 1) the loss of potential kidney transplant function that occurs when the recipient dies before the time the graft would otherwise fail (organ waste) and 2) the return to dialysis and need for repeat transplantation that occurs when the deceased donor  70  kidney fails prior to recipient death and the recipient returns to the wait list to compete for a subsequent transplant (Figure 5.2). For example, transplantation of a 20-year old deceased donor kidney to a patient aged > 60 years would result in a loss of potential kidney transplant function because the anticipated life expectancy of the transplanted organ is greater than that of the transplant recipient 29. Alternatively, if a 60-year old deceased donor kidney is transplanted into a 20-year old recipient, the recipient’s life expectancy will exceed that of the deceased donor kidney and the recipient will require another transplant. Repeat transplantation is a significant burden on the Canadian organ supply, accounting for 11% of kidney transplantation.3 Therefore, matching the estimated life expectancies of transplant candidates and deceased donor kidneys has the potential to reduce inefficiencies in allocation. 29  Accurately predicting post-kidney transplant recipient and deceased donor kidney life expectancies prior to transplantation is an imperfect science, in large part because life expectancies are dependent on post-transplant factors, which are unpredictable prior to transplantation (e.g. the recipient’s immunologic response to the transplanted kidney, post-transplant disease development (e.g. diabetes, cancer), procedural factors (e.g. time between organ retrieval and transplantation)). Pre-transplant information available to estimate candidate life expectancy includes patient case-mix; and similar information available to estimate deceased donor kidney life expectancy includes donor factors (e.g. cause of death, hypertension, kidney function). Recipient and donor ages are the most important predictors of post-kidney transplant recipient and deceased donor kidney survival30, 97 and have the advantage of being objectively measurable and transparent  71  factors for both patients and medical personnel. In contrast, the presence and severity of other factors (e.g. diabetes) may be more difficult to characterize.  The inclusion of variables in addition to recipient and deceased donor kidney age, in models to estimate recipient and deceased donor kidney survival, has been proposed but rejected for being only marginally superior to models including donor and recipient ages alone, and too complex for patients and policy makers.31, 32 For these reasons, donor and candidate ages are reasonable proxies for recipient and deceased donor kidney life expectancies.95  In the United States, a proposed allocation strategy incorporated age matching (± 15 years) into allocation rules to exploit the existing differences in deceased donor kidney and recipient survival.89  This strategy eliminates extreme age mismatches thereby increasing the system’s utility. Two disadvantages of this system are 1) the distribution of deceased donor kidney ages is younger than the distribution of candidate ages, and therefore older candidates have reduced access to transplantation,35 and 2) the life expectancies of candidates and deceased donor kidneys of similar ages (i.e. ± 15 years) may not be equivalent, and therefore candidates may be disadvantaged because they are not eligible to be allocated a deceased donor kidney that has adequate graft survival for them. For example, a 55 year old candidate may be expected to live 15 years with a transplant, but a 55 year old deceased donor kidney may be expected to survive for only 7 years. In this example, the 55 year old candidate may be disadvantaged if they are not eligible to receive a younger deceased donor kidney (e.g. a deceased donor kidney aged 39 years with 15 years of life expectancy). This example suggests that direct age matching may not be satisfactory.  72  In order to select appropriate age matching cut-points for allocation, it is imperative to measure the inefficiency that occurs for each possible donor-recipient pair. Therefore, using deceased donor kidney and recipient ages as surrogates for life expectancies, the objectives of this paper are to determine for each recipient age group 1) the type of inefficiency (organ waste or return to dialysis), and 2) the quantity of inefficiency, that occur when recipients are transplanted with deceased donor kidneys of different ages. The type and quantity of these inefficiencies will also be used to compare the utility of different allocation systems.  5.2 Methods 5.2.1 Study population and data source Adult (age > 18 years) recipients of deceased donor kidney-only transplantation captured in the Canadian Organ Replacement Register between January 1, 1995 and December 31, 2008 were included in the study. Pediatric recipients were excluded from the study because they a priori receive prioritization for allocation due to the impact of dialysis on their neurologic and physical development. Patients transplanted in Quebec were not available at the time of data request and were not included. For each recipient, only the first kidney transplantation that occurred during the study period was included. Recipients were excluded from the study if they had missing data on either recipient or donor age at transplantation.    73  Population level characteristics of recipients and deceased donor kidneys were represented as means ± standard deviations (or medians and first and third quartiles) for continuous variables, and proportions for categorical variables.  5.2.2 Analytical methods 5.2.2.1 Selection of age strata For each of recipient and deceased donor kidney age, dummy variables were assigned for the following categories: age <19 (pediatric, deceased donor kidney age only), 19-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, and ≥ 65 years. A Cox proportional hazards regression analysis was performed to compare the patient survival of recipients of different ages adjusted for deceased donor kidney age, and a similar analysis was performed to compare the graft survival of deceased donor kidneys of different ages adjusted for recipient age. Age groups were collapsed to form final recipient and donor age strata for the analysis by taking into consideration overlap between survival curves by recipient and donor ages respectively, as well as the limited sample size in some age strata. 5.2.2.2 Estimating deceased donor kidney and recipient survival The two primary dependent variables in this study were recipient survival and deceased donor kidney survival (graft survival). Recipient survival refers to the probability that a transplant recipient is still alive at a given time after transplantation; and graft survival refers to the probability that the deceased donor kidney is still functioning at a given time after transplantation. Each dependent variable is time to event, and time was counted  74  from the date of transplantation until the outcome of interest (recipient death or deceased donor kidney failure (i.e. either recipient return to dialysis, or repeat transplantation)), or the end of follow-up (December 31, 2011). The primary outcome of recipient survival was neither censored at deceased donor kidney failure nor repeat transplantation because the outcome of interest was absolute patient survival after kidney transplantation, independent of the recipient’s type of renal replacement therapy. In contrast, for the outcome of graft survival, recipient death was treated as a censoring event.   5.2.2.2.1 Area under the survival curve The area under a survival curve represents the expected (or average) survival time for subjects.98 For the outcome of recipient survival, the area under the survival curve (mean survival) was calculated using the Kaplan-Meier product limit method with stratification by recipient age strata. Similarly, the area under the graft survival curve was calculated with stratification by donor kidney age. The area below the recipient and graft survival curves were provided by SAS 9.4 (Carey, N.C) using Irwin’s restricted mean, truncated at 120 months (10 years).99 Additional covariates were not included in the models because recipient and graft survival curves were directly compared within the same population.  In the models, the inter-cluster correlation between deceased donor kidneys from the same donor (maximum 2 kidneys per donor) was accounted for using the robust sandwich covariance matrix.100, 101  5.2.2.2.2 Area between survival curves When two populations are compared, the surface area between their corresponding survival curves is the average duration of life gained in the population with the greatest survival relative to the population with the least survival 98. For example, the average life  75  gained for a study treatment group relative to a control. Similar to Meier-Kriesche et al,102 we extended this argument to compare population level recipient and graft survival after kidney transplantation.  We quantified the area between the recipient and deceased donor kidney survival curves as either the expected time a recipient would be required to return to dialysis after deceased donor kidney failure (i.e. when recipient survival > deceased donor kidney survival) or the expected loss of potential kidney function after the recipient died (i.e. when deceased donor kidney survival > recipient survival).   The area between the curves was calculated as the difference in the areas under the two survival curves. Positive values for area between the curves represented the recipient outliving the deceased donor kidney, while negative values represented the recipient dying with residual deceased donor kidney function.  5.2.2.3 Allocation utility Each individual in the study was assigned a type (organ waste or return to dialysis) and quantity of inefficiency equivalent to the area between the curves corresponding to the intersection of their recipient and donor age strata. These inefficiencies were totalled over all recipients to calculate the summative utility of a given allocation system. This was done for each recipient based on the actual deceased donor kidney they received (actual allocation), as well as by assuming the same deceased donor pool had been allocated to the same recipient pool under an alternative allocation rule. In this study we examined a rule that ranked each recipient and donor by age and allocated deceased donor kidneys to recipients by matching their rank order (rank allocation matching). For example, the  76  youngest deceased donor kidney was allocated to the youngest recipient, and the oldest deceased donor kidney to the oldest recipient.  5.3 Results There were N=6 443 patients who received deceased donor kidney transplantation between 1995 and 2008. Of these, N=19 were missing data on deceased donor kidney age and a further N=300 recipients were aged < 19 years. These recipients were excluded from the analyses leaving a final population of N=6 124 patients.  The mean potential follow-up of study patients was 10 years. Recipients were mostly Caucasian, male, and without diabetes (Table 5.1). Recipients were not highly sensitized (i.e. not estimated to be tissue incompatible with a high percentage of deceased organ donors as measured by the peak panel reactive antibody >30% (8%)), and perfect genetic tissue matching (HLA mismatch=0) was infrequent. The median (q1, q3) waiting time for transplantation on dialysis was 2.6 years (1.4, 4.1). The distribution of recipient ages was normal and centred at 50 years of age, while the distribution of donor ages was bimodal with peaks near 19 and 50 years of age (Figure 5.4).   Cox proportional hazards models for life expectancy outcomes by recipient and deceased donor kidney ages are shown in Figure 5.5. Final age strata (and the corresponding sample sizes) for area-between-the-curve analyses, determined by collapsing age strata with overlapping survival curves from Cox proportional hazards models were: recipient ages (19-39, 40-49, 50-54, 55-59,  ≥ 60) and deceased donor kidney ages (< 35, 35-49, ≥50) (Table 5.2).   77  Table 5.3 shows for each strata the number of months of recipient and deceased donor kidney survival (maximum 120 months=10 years), and the difference in area (inefficiency) for each age combination. Boxes where the recipient outlived the deceased donor kidney are shaded in red and the difference in survival represents a return to dialysis and need for repeat transplantation. Boxes shaded in blue show age combinations where the deceased donor kidney outlives the recipient and the difference in survival represents the amount of organ waste. Boxes with no shading represent deceased donor kidney and recipient age strata with roughly equivalent survival, and negligible differences between the curves. Recipients aged less than 40 years outlived deceased donor kidneys of all ages; recipients aged 40-54 outlived older deceased donor kidneys, but had no difference in survival compared to younger donor kidneys. In contrast, recipients aged 55 years and over died before their donor kidney failed with the youngest deceased donor kidneys, but had no difference in survival with the oldest donor kidneys. The magnitude of inefficiency increased as the discrepancy between deceased donor kidney and recipient ages increased. 5.3.1 Summative utility The type and quantity of inefficiency for the current allocation system and the rank matching allocation system are shown in Table 5.4. The summative utility for the actual allocation, which treats the two types of inefficiencies equally, was 5 266 years (11 months per person), and for the rank matching allocation was 3 937 years (8 months per person). This resulted in a difference in summative utility between the two systems of  1 328 years (or 3 months per person).  78  5.4 Interpretation This study provides a method, using area between survival curves, to categorize and quantify the inefficiency that results when there is a difference in the life expectancy between a transplant recipient and their transplanted kidney. We found that adult recipients younger than 40 years outlived deceased donor kidneys of all ages and required repeat transplantation. Recipient aged 40-54 outlived donor kidneys that were young relative to them, and had similar survival to older donor kidneys. In contrast, recipients aged ≥ 55 years were most likely to die with a younger functioning donor kidney, but had similar life expectancy to older donor kidneys (Table 5.3). For each recipient age, the amount of inefficiency increased with more discrepant deceased donor kidney age. When comparing an age-rank based allocation system compared to actual allocation we found that we could eliminate close to 500 years of wasted graft function, and more than 800 years of dialysis (Table 5.4). This would necessarily result in increased recipient and graft survival.  Several studies have suggested alternative methods to incorporate age matching into allocation rules to exploit the differences in deceased donor kidney and recipient survival that arise in the current justice favoured systems.35, 103 These studies have estimated improvements in efficiency by calculating changes in recipient and deceased donor kidney survival. The new American proposal, which prioritizes the top 20% quality kidneys to the 20% of candidates with the greatest expected survival, may result in an increase in patient survival with a functioning kidney graft (i.e. improvement in utility) as a result of transplanting a greater proportion of younger and healthier people;  but their  79  increased efficiency comes at the expense of equitable access.35 Ross et al103 propose a similar allocation structure that redistributes the youngest deceased donor kidneys to the youngest recipients, but maintains equity in access to transplantation by restricting candidate age groups to receive a proportional number of deceased donor kidneys. Although both systems avoid extreme age mismatches, they do not account for inefficiencies that occur for non-extreme ages, and may disadvantage moderate aged well candidates from receiving deceased donor kidneys that meet their survival needs.  The measure of inefficiency in this study is unique because it simultaneously characterizes the type (organ waste and the need for repeat transplantation), as well as the magnitude of the difference in deceased donor kidney and recipient life expectancies. In addition, it does not assume a strategy for age matching (i.e. rank order allocation) but allows for the evaluation of efficiency under different age constraints.  Depending on the importance of inefficiency type and magnitude to the decision maker, the measure of inefficiency in this study can be used to suggest appropriate and inappropriate utility based cut-points for allocation using age matching. For example, to avoid organ waste all deceased donor kidneys could be allocated to the youngest candidates, but this would be offset by an increase in need for repeat transplantation in those young candidates who receive the oldest deceased donor kidneys. Alternatively, allocating all deceased donor kidneys to the oldest candidates would minimize the need for repeat transplantation in these candidates, at the expense of increased organ waste. Ideally, these inefficiencies could be used in tandem with the candidate and deceased donor kidney age distributions to identify equitable utility-based age cut-points for  80  balanced allocation.  In addition, the summative utilities calculated under different proposed allocation systems could be used to compare the efficiency of different allocation strategies.   The calculation of inefficiency in this paper is limited by restricting the follow-up time to ten years. However, the additional area between the curves at the age extremes would likely inflate the estimated inefficiencies, as the curves tend to separate over time, not reduce them. In addition, in the model for deceased donor kidney life expectancy, recipient death was treated as a non-informative censoring variable. The inclusion of recipient death as a competing risk was considered, but declined. The purpose of the model was to estimate deceased donor kidney failure from an allocation (i.e. decision maker) perspective. From this vantage, a recipient death was considered to be independent of the deceased donor kidney life expectancy that we try to predict pre-transplant (i.e. we assume a prioi in some cases that the deceased donor kidney will outlive the recipient). In contrast, when considering the outcome of graft failure from the recipient’s perspective, recipient death could be considered a competing risk for deceased donor kidney death because it precludes the recipient from realizing the outcome of graft failure without death.   Furthermore, the most accurate way to estimate deceased donor kidney survival would be in recipients with the greatest expected survival. This was not done because it would not allow for an interaction for the same aged deceased donor kidney in different aged recipients; and also deceased donor kidneys of the same age transplanted into different candidates may differ in quality due to confounding by  81  indication.  Ideally, this would be accounted for in a paired kidney analysis, in which the two kidneys from one deceased donor would be allocated to candidates of different ages.  The estimated inefficiencies in the study model can be used to compare between similar Canadian populations and over time, but should be recalculated to evaluate inefficiencies in different populations (e.g. other countries). Although the numbers from Table 5.3 are not generalizable outside of the study population, the methods are commutable. An advantage of this measure of inefficiency is its reliance on donor and recipient ages alone. As the age distributions of the candidate and donor pool change over time, utility-based allocation could be altered simply by changing the age cut-points. The inclusion of other important factors in models to estimate life expectancy, such as diabetes and cardiovascular disease in candidates, may slightly increase the predictive ability of these models, but remains a limited improvement due to the inability of administrative data on these reported dichotomous variables to accurately account for the spectrum and severity of these comorbidities. Given the impact of diabetes on recipient life expectancy, it would be advantageous to recreate this analysis, in future work, by stratifying on diabetes as a comorbidity or cause of renal failure.  In conclusion, the study provides a method of measuring the type and quantity of inefficiency for different recipient and deceased donor kidney ages. These measures can be used in tandem with information about the distribution of deceased donor kidney and candidate ages to inform the selection of cut-points for age matching in deceased donor kidney allocation.  82  Figure 5.1 Panel A shows possible differences in predicted patient and deceased donor kidney survival between donor kidneys and their recipients under current allocation rules. Panel B shows possible differences in predicted patient and deceased donor kidney survival for the same aged donor kidneys and recipients using allocation by life expectancy matching.    Figure 5.2 A description of the inefficiencies that occur when the same recipient is transplanted with deceased donor kidney grafts with differential expected survival.The dark grey bars represent the two types of inefficiency that occur when the recipient and the donor kidney have unequal survival.   83  Figure 5.3 Left panel: Area between the recipient and graft survival curves represents the time a patient would be required to return to dialysis and await repeat transplantation. Right panel: area between the recipient and graft survival curves represents the loss of potential kidney function. The vertical distance between each pair represents the difference in predicted patient and deceased donor kidney survival.        84  Figure 5.4. Histograms showing the distribution of recipient (top panel) and deceased donor kidney (bottom panel) ages                   85  Figure 5.5. Left panel: Recipient survival by recipient age categories. Right panel: Graft survival by donor age categories.    0 2 4 6 8 10Time from transplantation (years)0.50.60.70.80.91.0Probability of Remaining Event FreeRecipient survival19-2930-3435-3940-4445-4950-5455-5960-6465+0 2 4 6 8 10Time from transplantation (years)0.50.60.70.80.91.0Graft survival<1919-2930-3435-3940-4445-4950-5455-5960-6465+ 86  Table 5.1 Recipient and donor characteristics  N=6 124 Recipient  Age mean (std); median (q1,q3) 50 (12.9);  50 (41,60) min=19 max 84 Female sex (%)  2 730 (45) Race Caucasian Other  4 049 (66) 2 075 (34) Cause of End-Stage Renal Disease Diabetes Other  695 (11) 4 429 (89) Peak panel reactive antibody % 0 1-30 31-80 >80 Missing*  3 708 (76) 796 (16) 274 (6) 104 (2) 1 242 Time on dialysis prior to transplantation (years) Median (q1,q3) 3.4 (1.8, 5.8) Province of transplantation Alberta British Columbia Saskatchewan Manitoba Ontario Nova Scotia  1 019 (17) 826 (14) 295 (5) 268 (4) 2 959 (48) 757 (12) Year of transplantation 1995-1999 2000-2004 2005-2008  2 282 (37) 2 027 (33) 1 815 (30) Donor  Age 40 (16.9); 43 (26,53) min 0 max 86 Cause of death: cerebrovascular disease 600 (10)  Donation after cardiocirculatory death 79 (1)   87  Table 5.2. Study sample size by recipient and donor kidney age categories  Sample Size (N) Deceased donor kidney age (years) <35 35-49 ≥50 Recipient age (years) 19-39 649 428 376 40-49 590 491 448 50-54 261 235 276 55-59 255 252 362 ≥60 393 421 687        88  Table 5.3. Area under and between recipient survival and graft survival curves   Deceased donor kidney age (years)  <35 35-49 ≥50 Recipient age (years) 19-39 R Survival Graft Survival Δ Survival 9.15 (0.08)a 8.28 (0.13) 0.87 (0.15) 9.47 (0.09) 8.05 (0.15) 1.42 (0.17) 9.17 (0.10) 7.06 (0.20) 2.11 (0.22) 40-49 R Survival Graft Survival Δ Survival 9.02 (0.09) 8.83 (0.11) 0.19 (0.14)   8.97 (0.11) 8.39 (0.14) 0.58 (0.18) 9.04 (0.11) 7.91 (0.17) 1.13 (0.20) 50-54 R Survival Graft Survival Δ Survival 8.84 (0.15) 8.62 (0.16) 0.22 (0.22) 8.73 (0.17) 8.39 (0.17) 0.34 (0.24) 8.33 (0.17) 7.71 (0.21) 0.62 (0.27) 55-59 R Survival Graft Survival Δ Survival 8.63 (0.17) 9.70 (0.12) -1.07 (0.21) 8.28 (0.20) 8.36 (0.17) -0.08 (0.26) 8.24 (0.15) 8.47 (0.17) -0.23 (0.23) ≥60 R Survival Graft Survival Δ Survival 7.81 (0.16) 9.03 (0.13) -1.22 (0.21) 7.60 (0.16) 8.81 (0.14) -1.21 (0.21) 7.39 (0.14) 7.61 (0.12) -0.22(0.18) R= recipient; ∆= difference in recipient and graft aData presented as mean (standard error) White boxes represent non-significant difference in area between recipient and graft survival curves p>0.05; Red boxes represent donor and recipient age strata where the life expectancy of the recipient was greater than that of the donor kidny (p<0.05); Blue boxes represent donor and recipient age strata where the life expectancy of the donor kidney was greater than that of the recipient (p<0.05) Table 5.4. The summative utility of two allocation systems  Actual allocation Rank matching allocation Column difference Organ waste (negative inefficiency) 1975 years  (4m/person) 1480 years (3m/person) 495 years (1m/ person) Return to dialysis (positive inefficiency) 3291 years  (7m/ person) 2457 years (5m/ person) 833 years (2m/person) Row totals 5266 years (11m per person) 3937 years (8m per person) 1328 y (3 m per person)      89  6 Defining equitable-based utility cut-points for donor-candidate age matching 6.1 Introduction 6.1.1 Deceased donor kidney and candidate ages The supply of deceased donor kidneys is limited, thus decisions need to be made about which patients to prioritize for transplantation, and which deceased donor kidneys to allocate to which candidates. Donor kidney age and candidate age have been suggested as components for allocation in different countries with varying utilization.  Children treated with chronic dialysis have impaired growth and neurological development, and are therefore, prioritized for transplantation in most countries (i.e. greater medical need for treatment with transplantation). Based on the principle that increased (but potentially unequal) access to treatment in patients with greater need is equitable, maximizing access to transplantation in pediatric patients can be considered just. In addition, because deceased donor kidney graft function is not maintained indefinitely, allocating the highest quality deceased donor kidneys (i.e. kidneys from younger deceased donors with the longest expected survival) to pediatric candidates increases utility because it reduces the duration of time that these patients will need a different form of ESRD treatment (i.e. repeat transplantation or dialysis) after failure of their first transplant.   Similarly, young adults have the longest life expectancies and prioritizing these young adult ESRD patients for transplantation with young donor kidneys would maximize their survival with a functioning transplant, and reduce or eliminate the potential wasted graft  90  function that occurs when these higher quality kidneys are transplanted into older candidates with shorter expected survival. However, because young adults are not subject to the same developmental problems experienced by children, the same equity considerations do not apply.  Preferential allocation of young donor kidneys to young adult candidates may therefore be inequitable as a policy in isolation. In order to maintain equitable access to deceased donor kidney transplantation among all adult candidates, additional allocation constraints are essential to ensure that efforts to match organ survival with patient survival do not decrease elderly access to transplantation.  Specifically, equity would be preserved by an organ allocation policy that increases the utility from the available organ supply by minimizing differences in patient and donor kidney age, without altering the age distribution of the population transplanted.     One possibility to offset the advantaged access to young donor kidneys for young adult candidates is to prioritize older candidates for another group of deceased donor kidneys. These kidneys are expanded criteria donors (ECD) kidneys. An ECD kidney is a physiologically marginal kidney, differentiated by an increased risk of graft failure. The widely used American definition of an ECD kidney includes donor kidneys aged ≥ 60 years or aged 50-59 years with specified comorbidities.69 There is no equivalent Canadian definition for deceased donor kidneys at increased risk of graft failure, and ECD kidneys in Canada are generally defined as kidneys from deceased donors aged ≥ 60 years.    91  Deceased donor kidneys are usually transplanted if they are expected to increase the candidate’s survival relative to remaining on dialysis. Despite providing shorter expected graft survival, transplantation with older deceased donor kidneys (i.e. ECD kidneys) provides a survival advantage relative to remaining on dialysis for older and less healthy candidates, as well as candidates living in regions with long expected waiting times for transplantation.16 However, older deceased donor kidneys provide reduced long-term graft and patient survival for all candidates relative to transplantation with younger deceased donor kidneys.70 For example, although a 60-year old kidney is expected to increase the life expectancy of a 65-year old candidate compared to remaining on dialysis, these kidneys may be associated with a shorter life expectancy for the same candidate compared to transplantation with a 40-year old donor kidney. Transplantation of these lower quality kidneys may in part be justified if they can be transplanted more rapidly than younger donor kidneys because the risks of continued dialysis exposure while waiting for a transplant are particularly high in older candidates (i.e. candidates may die waiting for a higher quality kidney, or their condition may deteriorate rendering them ineligible for transplantation). For example, transplantation of a 60-year old donor kidney to a 50-year old candidate with diabetes may be justified when the waiting time is less than the waiting time for a 40-year old donor kidney because the risk of death on dialysis in older ESRD patients with diabetes is high. However, if the 60-year old donor kidney was transplanted under a circumstance with equal or similar waiting time to the 40-year old kidney, the candidate may be done an injustice, even though their life expectancy was still increased compared to treatment with dialysis. This injustice is  92  currently accepted for some patient groups because there simply are not enough young donor kidneys for all candidates.  6.1.2 Considerations for allocation by donor and candidate age matching In age matching, young donor kidneys are allocated to young candidates to provide increased survival with graft function. However, older donor kidneys may not provide adequate graft survival to non-young candidates. Therefore, a criticism of donor-candidate age matching is that it will advantage younger candidates, but adversely affect older candidates by reducing their access to higher quality kidneys.104 Importantly, in the Eurotransplant Senior Program deceased donor kidneys aged ≥ 65 years are preferentially allocated to candidates aged ≥65 years, and these older kidneys have been used safely to increase transplantation in elderly candidates.76 These successes in Europe challenge the notion that ‘old’ to ‘old’ age matching necessarily leads to inferior outcomes in older candidates. Despite this information, there is a reluctance to use older kidneys, particularly in the United States where older kidneys are discarded at a high rate (i.e.40%).81   Importantly, it is not clear if the lower post-transplantation life expectancy that is associated with older donor age is due to the age of the kidney alone, or perhaps attributable to unmeasured confounding by indication. For example, candidates with poorer expected outcomes (e.g. high comorbid burden or older age) may have a higher likelihood of being transplanted with lower quality (older) kidneys.105    93  Finally, the impact of donor-candidate age matching on decreased access to transplantation in elderly candidates requires consideration. For example, age matching proposed in the American system increases recipient and graft survival, but does so at the expense of transplanting fewer candidates aged > 60 years.36 35 Restricting access of older patients to young donors kidneys may be problematic if similar limits on access to younger recipients are not put into place . For example, the failure to restrict younger candidate access to ECD kidneys, despite that fact that ECDs will likely not provide younger candidates with a sufficient duration of graft function to obviate the need to return to dialysis after ECD failure and/or repeat transplantation. Reese and Caplan104 suggest that despite decreased access to elderly transplantation, the proposed allocation is not inequitable by the ‘fair innings’ argument. The ‘fair innings’ argument as applied in this context maintains that young people who develop ESRD are worse off than older patients developing ESRD because they have experienced fewer healthy life years (i.e. they deserve a chance to be old, whereas older patients have already had the chance to be young).103, 106   The implications of donor-candidate age matching depend on how strict the matching criteria are. The strictest matching might fix a minimal difference between donor kidney age and candidate age of one, five or ten years, compared to a looser or more fluid policy of age matching that is proportional by donor and candidate ages. The choice of age matching strategy may accentuate or diminish inequities in access to transplantation by age. For example, a proportional age-matching strategy that allocates by decile (i.e. the youngest 10% of donor kidneys to the youngest 10% of candidates, up to the oldest 10%  94  of donor kidneys to the oldest 10% of candidates) would eliminate inequity in access to transplantation by candidate age, and would inherently account for any changes in donor and candidate ages that occur over time. In addition, proportional age-matching as described would be equitable even in the presence of current differences in donor kidney and candidate ages. In contrast, an allocation strategy that requires matching of donor kidneys and candidates within one year of age, would result in a recipient population with an age distribution similar to the donor kidney age distribution, but not necessarily the same as the candidate age distribution. In the current environment, donor kidneys are younger than candidates and therefore a stricter age-matching allocation strategy would disadvantage older candidates.   Existing differences in international clinical practice surrounding discard of older donor kidneys may make the policy of age matching more attractive in different countries. For example, in Eurotransplant the discard rate of older donor kidneys is lower than in the United States, and this may be an accepted clinical practice because the intention is that these older donor kidneys will be used to increase transplantation in older patients.   In an organ poor environment, the goal of donor-candidate age matching is to increase utility by reducing organ waste and increasing recipient survival with a functioning graft. In order to maintain equity in access to transplantation across adult age subgroups while age matching, the limited number of young donors preferentially allocated to young adult candidates should be offset by the additional and expeditious transplantation of older adult candidates with kidneys from older donors. Ideally, the addition of donor-candidate  95  age matching in allocation algorithms would improve recipient outcomes, without changing which patients are transplanted. 6.1.3 The Canadian perspective In Canada, healthcare is administered provincially; although there is general agreement on some principles of organ allocation, there is still variation in allocation policies across provinces. In 2006, the Canadian Council for Donation and Transplantation (CCDT) convened a forum to develop recommendations for the allocation of deceased donor kidneys that could be incorporated in each province. An underlying premise of the forum was that organs be allocated ‘fairly, considering both equitable access and optimal outcomes for transplantation’. 107 As part of these recommendations, deceased donor age and candidate age were considered as key determinants of allocation policy; and age-specific recommendations for kidneys from deceased donors aged < 60 years (Canadian definition of standard criteria donor) and deceased donor aged ≥ 60 years (Canadian definition of expanded criteria donor) were provided.107    The CCDT age specific recommendations for the allocation of standard criteria donor kidneys included prioritization for: 1) pediatric candidates (high priority), 2) young standard criteria donors to pediatric candidates (high priority), and 3) young standard criteria donors (young donors) to young adult candidates (medium priority) .107  The CCDT recommended that ECD kidneys should be allocated by waiting time, preferentially to candidates aged ≥60 years or candidates aged < 60 years with significant comorbidity.107  96  In Canada, the allocation of deceased donor kidneys across provinces is aligned with the principles put forth by the CCDT recommendations, but the constructs of young donor kidney and young adult recipient are not explicitly defined, and the age cut-point for expanded criteria donors is empirical. Therefore, there is no uniformly accepted formula for donor-candidate age matching across Canada. As such, the objective of this paper is to qualify and quantify equitable utility-based definitions for age cut-points for the allocation of deceased donor kidneys to transplant candidates using age matching in Canada.  6.2 Definitions 6.2.1 Nominal definitions of young and old The designation of a candidate as young or old can be practically dictated by the age (i.e. life expectancy) of the donor kidney. When the life expectancy of the candidate is longer than that of the donor kidney, the candidate is considered young; and when the life expectancy of the candidate is shorter than that of the donor kidney the candidate is considered old. For example, a candidate aged 50 years with a life expectancy of fifteen years may be designated old in relation to a donor kidney aged 18 years with a life expectancy of twenty years, or young relative to a donor kidney aged 55 years with a life expectancy of ten years.    Similarly, whether a donor is considered young or old depends on the age of the intended recipient. For example, a donor kidney aged 50 years with a hypothetical life expectancy of ten years could be young in relation to a candidate aged 70 years with a life  97  expectancy of five years, or old in relation to a candidate aged 25 years with a life expectancy of twenty years. It is possible that some donor kidneys may always have a shorter life expectancy relative to any aged candidate and may always be considered old.  In practice, if the life expectancy of donor kidneys changed, a previously defined young donor, could be considered old, or vice versa. 6.2.2 Operational definitions of young and old 6.2.2.1 Young donor kidneys and candidates The number of deceased donor kidneys available for transplantation is greatly exceeded by the number of patients who would benefit from transplantation (candidates). Therefore, the total life expectancy of candidates is greater than that provided by the pool of deceased donor kidneys available for transplantation. There is a group of adult transplant candidates who will always be considered young because their life expectancy is greater than that provided by even the highest quality kidney (i.e. youngest adult donor kidneys). These candidates are young adult candidates. In the absence of a living donor, the best treatment for young adult candidates is transplantation with the youngest adult deceased donor kidneys (i.e. young donor kidneys). In order to maintain equity for older candidates, a limit on the number of young donor kidneys preferentially allocated to young recipients is required.   The maximum donor age cut-point for young adult candidates should be informed by the supply of ECD kidneys that can be preferentially allocated to older candidates. As previously stated, older donor kidneys are associated with shorter patient and graft life  98  expectancy relative to younger donor kidneys, and transplantation of these ECD kidneys may only be justified in older candidates in the context of rapid transplantation with minimal dialysis exposure. If the number of young donor kidneys allocated to young adult candidates is too large, the number of older donor kidneys remaining for non-young candidates is reduced, and the waiting time for transplantation of older candidates is increased, limiting the benefit of transplantation from ECD kidneys. Therefore, the upper age cut-point for young donor kidneys should be defined by the available supply of ECD kidneys.   Importantly, the time that donor kidneys of different ages become available is not known in advance.  In practice, balancing the number of young donor kidneys preferentially allocated to young candidates, with the number of ECD kidneys preferentially allocated to older candidates, is based on the assumption that there is no difference in the time of availability for younger and older donor kidneys. If the discrepancy in the supply of young donor kidneys and ECD kidneys changes over time, one candidate age group may have to wait longer for kidney transplantation. Therefore, any implemented age-matching policy will require ongoing evaluation to assess the impact of variations in donor kidney availability by age.    6.2.2.2 Older donor kidneys and candidates The definition of an ECD kidney was operationalized by a donor age above which the deceased donor kidney does not provide a lifetime of graft function in younger adult  99  candidates, but does provide a lifetime of graft function in an older group of candidates (older candidates). That is, an older candidate is defined by a candidate age above which an ECD kidney provides an expected lifetime of graft function. In addition, an ECD kidney should not decrease the expected life span of the older candidate.  6.2.2.3 Summary The designation of a candidate/donor as young or old is in reference to the age of the respective donor/candidate. To determine cut-points to define young and old candidates and donors both the utility (i.e. the years of graft function that a given aged donor kidney will provide a given aged candidate) and equity (i.e. the allocation of donor kidneys fairly to candidates of different age groups) of age matching should be considered. The following section will outline the study method used to quantify the utility and equity components of age matching in Canada. 6.2.3 Quantifying ages of donors and candidates for age matching 6.2.3.1 Utility component of donor and candidate age cut-points  The following analyses were performed with Canadian recipients captured in the CORR database, as described in Chapter 5. Pediatric candidates receive the highest priority for deceased donor kidney allocation, and are thus excluded from the utility components of the definitions below.   100  To calculate the difference in donor and candidate life expectancy, we used the area-between-the-curve methodology from Chapter 5. Using the operational definition for young adult candidate above, we determined the age cut-point for a young adult candidate from the results in Table 5.3.  That is, a young adult candidate was determined to be 19-54 years of age; an age range where recipients were expected to live as long or longer than deceased donor kidneys of all ages. Based on this definition of a young adult candidate, we determined a maximum utility age cut-point for a young donor by calculating the time back on dialysis (i.e. the area between patient and graft survival curves) for young adult recipients with deceased donor kidneys of different ages (i.e.  donor age <35 years, 35-39 years, 40-44 years, 45-49 years, 50-54 years, 55-59 years and ≥ 60 years).    Among candidates who do not meet the criteria to be considered young  (i.e. age ≥ 55 years), the subset of oldest patients (with the shortest life expectancy) will derive a lifetime of transplant function even when transplanted with a kidney with the lowest expected post-transplant survival (i.e. ECD). Finally, a third intermediate group of patients who are considered old with respect to young donor kidneys, but are considered young relative to ECD kidneys can be defined.   In order to determine the age cut-point below which candidates will be considered young or old in relation to ECD kidneys, we divided older recipients into two age groups: 55-59 and ≥ 60 years. (The number of age groups here was restricted due to constraints with sample size). Using the methods from Chapter 5, we calculated the area between the  101  unadjusted patient and graft survival curves for these recipient age groups with donor age cut-points (possible ECD kidney age threshold) of 55-59 years and ≥ 60 years.   Among candidates who we determined would always be considered old relative to deceased donor kidneys of any age (i.e. older candidates), we determined the degree to which patient survival was negatively impacted by older donor age in a multivariate Cox proportional hazards regression model adjusted for the following covariates: recipient sex, cause of ESRD, peak panel reactive antibody titre, duration of dialysis prior to transplantation, and year of transplantation.  6.2.3.2 Equity component of donor and candidate age cut-points  In the previous section we outlined methods to determine a cut-point for ECD kidneys that would provide the oldest candidates with a lifetime of graft function, without reducing patient survival.  To determine an acceptable age cut-point for young donors we examined the distribution of deceased donor kidney and recipient ages from transplants recorded in the last three years of available CORR data (2008-2010). Specifically, we first determined the number of deceased donor kidneys that met our utility definition for ECD kidneys and could reasonably be prioritized for transplantation in older candidates. We then used this number to determine the maximum number and age limit for young donor kidneys that could be prioritized for transplantation in young recipients. This approach to defining the  102  limits of prioritization of young recipients based on the availability of suitable organs to be prioritized for older recipients may be considered an “equity-based ceiling”.  Finally, we determined any longitudinal change in the supply of deceased donor kidneys and the age of recipients. This was done to inform the potential stability of the age cut-point selected over time. 6.2.3.3 Recommendations and hypothetical redistribution of deceased donor kidneys  to recipients The utility and equity analyses above were combined to put forth recommendations of age cut-points for donor and candidate age matching. Using the ages of deceased donor kidneys and recipients of actual transplanted donor-recipient pairs from 2008-2010 in the data set, we performed a hypothetical redistribution of these deceased donor kidneys to the same group of recipients based on the age matching recommendations in this study, specifically: deceased donor kidneys aged <35 years to candidates aged 19 to 54 years; deceased donor kidneys aged ≥55 years to candidates aged ≥60 years; and deceased donor kidneys aged 35-54 years to all candidates on the list (see Section 6.3.2). The redistribution did not consider any discrepancy in age distribution that may exist between transplanted recipients and candidates on the waiting list.   All analyses were performed using SAS 9.4, Carey, N.C.   103  6.3 Results 6.3.1 Donor-candidate age matching cut-points 6.3.1.1 Young adult candidate age cut-point Using the operational definition for young adult candidate above and the results from Table 5.3, the age range for a young adult candidate was defined as 19-54 years; 55 years is the age below which young adult recipients lived as long, or longer, than deceased donor kidneys of all ages.   6.3.1.2 ECD kidney and older candidate age cut-points Donor age cut-points < 50 years were not considered for older donors because these donors’ kidneys survived as long or longer than older adult recipients (Table 5.3). When non-young adult recipients were further stratified by age, donors aged ≥ 55 years did not provide adequate graft survival to recipients aged 55-59 years, but did provide adequate graft survival for recipients aged ≥60 years (Table 6.1). In addition, recipients aged ≥ 60 years had similar patient survival when transplanted with deceased donor kidneys aged 55-59 years and aged ≥60 years [HR (95% CI): 0.85 (0.60, 1.21) reference = donor age ≥60 years]. Therefore, donors aged ≥55 years meet the utility definition for ECD kidneys, when transplanted into recipients aged ≥60 years (older candidates).  Table 6.2 summarizes the designation of candidates as young or old relative to deceased donor kidneys of different ages.  104  6.3.1.3 Young donor age cut-point Donors aged < 45 years offer superior graft survival for recipients aged < 55 years (Table 6.1). Therefore, from a utility perspective the cut-point for young donor age could be any age less than 45 years. To maintain equity in access to transplantation by candidate age, we must offset the number of young donors prioritized for young, by the number of mature donors prioritized for mature recipients. From 2008-2010, there were N=462 kidneys aged ≥55 (29%), and this matched the number of deceased donor kidneys that were 33 years and younger. Therefore, to maintain equity in distribution of deceased donor kidneys, and given that kidney aged < 35 are also prioritized for pediatric candidates we selected a young donor age cut-point of 35 years which is consistent for our utility requirement that the young donor age be less than 45 years. Importantly, the age distribution of deceased donor kidneys was not constant by study year (p<0.0001) (Figure 6.1).  6.3.2 Recommendations and hypothetical redistribution of deceased donor kidneys to recipients The results of this study were presented as recommendations for allocation using age matching to the Canadian National Kidney Working group, a group comprised of transplant nephrologists and other health care workers directly involved in managing deceased donor kidney transplantation and informing deceased donor kidney allocation. There were no new recommendations presented with respect to pediatric transplant candidates, but consensus is that these candidates continue to be prioritized for transplantation with deceased donor kidneys aged < 35 years. The following age  105  matching cut-point recommendations for allocation of deceased donor kidneys to adult candidates were presented: 1. Deceased donor kidneys aged <35 years should be allocated to candidates aged 19 to 54 years. 2. Deceased donor kidneys aged ≥55 years should be allocated to candidates aged ≥60 years. 3. Deceased donor kidneys aged 35-54 years should be allocated irrespective of age to all candidates on the list.  Within each of these age recommendations, candidates continue to be selected for transplantation based on previous Canadian Council for Donation and Transplantation recommendations (i.e. biologic compatibility, sensitization, waiting time).107 6.3.2.1 Redistribution: a hypothetical example Using the ages of deceased donor kidneys and recipients of actual transplanted donor-recipient pairs from 2008-2010 in the data, we performed a hypothetical redistribution of these kidneys to the same group of recipients under the age matching recommendations put forth above. That is, deceased donor kidneys aged < 35 years were first allocated to pediatric recipients, then to recipients aged 19-54, and deceased donor kidneys aged ≥55 years were allocated to recipients aged ≥60 years. The remainder of kidneys were divided between the remaining recipients in all groups (in practice these donor kidneys would be allocated to candidates with the same blood type, with the first offer to the candidate with the highest allocation points (e.g. longest waiting time)).  This example ignored the time sensitive nature of the availability of deceased donor kidneys, and assumed all transplantation could occur at the same time. Following the recommendations, the redistribution of deceased donor kidneys to recipients using the defined age matching strategy resulted in a reduction of donor-recipient age mismatch, and therefore  106  improvements in allocation efficiency, without altering the transplant candidate population (Figure 6.2). 6.4 Interpretation This study presents equitable utility-based nominal and operational age definitions for young adult candidates, young donors, ECD donors and older candidates; and puts forth specific age recommendations for the use of donor/candidate age matching in the allocation of deceased donor kidneys.   The current system proposed in the United States35 (detailed in Chapter 4), increases allocation utility similar to this chapter’s proposed age matching strategy by eliminating the extreme age mismatch that occurs when the highest quality kidneys are allocated to the lowest quality candidates. The US proposal does this by offering the top 20% quality kidneys to the 20% youngest and healthiest candidates. In contrast to the study proposal, the American model does not address allocation at the other extreme (i.e. young, healthy candidates have the option of accepting ECD kidneys in the United States).   Unfortunately, the increase in utility in the United States comes at the expense of fewer patients aged > 60 years receiving deceased donor transplantation,35 whereas in Canada the recommendations from this chapter are aimed at maintaining distributive justice by not changing which candidates get transplanted by age (i.e. the proportion of each candidate age group that is transplanted should remain constant), but only redistributing the same kidneys to similarly aged people more efficiently (i.e. by offsetting the number  107  of young donor kidneys that are prioritized to the young, with a similar number of older donor kidneys prioritized for older patients).   This analysis has several limitations. First, this analysis was done at the population level, assuming that the age distribution of deceased donors and candidates is stable over time. However, the data show that donor age is increasing over time and therefore, the age cut-points recommended here should be re-evaluated every few years as the ages of the donor and candidate populations changes. In addition, CORR does not provide information on the age distribution of wait-list candidates; therefore, we cannot determine if the age distribution of transplant candidates is changing over time, nor can we assess the risk of candidate death on the waiting list to inform our allocation. However, given the increasing age of the end-stage renal disease population (i.e. population on chronic dialysis or transplantation)3 and the increasing age of transplant recipients over time in this study, we suspect that candidate age is also increasing over time and a re-evaluation of the recommendations will be necessary to ensure that the proportion of candidates from each age group being transplanted is consistent over time, not simply that the age of transplant recipients is remaining constant. The prioritization of young donors to young candidates and ECD donors to older recipients will increase utility in these groups, but it is unclear what the impact will be on candidates aged 55-59 years who aren’t directly prioritized.  Second, the analysis was based on the assumption that different aged kidneys would be available to the prevalent candidate population at the same time. Unfortunately, the  108  availability of deceased donor kidneys is unpredictable, and the implementation of these recommendations may change the waiting time for individual patients (i.e. either more quickly or more slowly), as well as the selection of individuals that will be offered transplantation. These recommendations are meant to be implemented at the population level, and maintain equity as such. Importantly, the implications of small additional changes to waiting times are not known, although increased dialysis time portends to worse outcomes.108 In Canada, it has been shown that there are no changes in outcomes with dialysis time up to four years,109 and thus if the changes are small, the detriment may be negligible. The greatest harm of additional waiting time is among individuals with poor access to transplantation due to biologic or geographic factors, or older patients whose life expectancy is limited. In contrast, for younger candidates the benefit of receiving a younger kidney that would provide them with more years of graft function and prevent them from returning to dialysis to compete for another transplant would most likely outweigh a small change in waiting time.  Third, the current recommendations are based on national data, but uptake of recommendations would occur regionally. Although, the given recommendations might be successful in large regions (e.g. Ontario) where the age distribution of donors and candidates may be closer to the study means, and time between deceased donors becoming available will be shorter, in smaller regions (e.g. Manitoba) the age distribution of donors and candidates may differ and deceased donation may be less frequent. Therefore, the specific allocation guidelines for age matching may require regional modification.  109  The acceptance and uptake of age matching allocation policies for deceased donation may differ internationally. For example, Eurotransplant aggressively uses older donor kidneys in order to transplant more older candidates, whereas in the United States, the reluctance to use older kidneys (i.e. high discard of ECD kidneys) may make an age matching proposal less attractive because there are fewer older donors available. In addition, the legal acceptability of age matching allocation may differ by region, as exemplified by the use of direct age matching in ESP in Europe, but the removal of direct age matching from the new American kidney allocation system. Based on our relative definitions of young and old, the number of young donor and ECD kidneys available for transplantation may depend on the case-mix of candidates in different regions.   In certain countries where dialysis outcomes are poor or dialysis is less accessible (e.g. India where patients pay for dialysis treatment), it may not be possible for candidates to wait for deceased donor kidneys to whom they are age matched. In countries such as India, living donation may be the most reliable treatment option.   In conclusion, including donor-candidate age matching in the allocation of deceased donor kidneys will increase utility, and the recommendations put forth in this chapter should do so while maintaining equitable access across candidate ages. These recommendations need to be reviewed every few years as the age of the donor and candidate populations change, and the implication of altering waiting times in individual candidates needs to be explored. Importantly, the implications of implementing these  110  recommendations may vary regionally, and individual regions need to take care when interpreting these recommendations within their populations.    111  Figure 6.1 The distribution of Canadian recipient age and deceased donor kidney age by year of transplantation. Recipient mean age (std): 44 (14.7) in 1995, 53 (15.1) in 2010; Donor kidney mean age (std): 36 (16.9)  in 1995, 43 (17.0) in 2010.  P-value for trends in recipient age and deceased donor kidney age over time p<0.0001.      0204060801995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010Recipient Age DistributionYear of transplantationAge0204060801995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010Donor Age DistributionYear of transplantationAge 112  Figure 6.2 The distribution of deceased donor kidneys to recipients by age. Top panel shows how deceased donor kidneys from 2008-2010 were allocated in practice to recipients. Bottom panel shows the redistribution of the same aged deceased donor kidneys to the same aged recipients following the recommendations for donor-candidate age matching in this chapter.       113  Table 6.1. Area under and between recipient survival and graft survival curves  Donor age in years Young recipient age 19-54 years Non-young recipient ≥55 years Recipient age 55-59 years Recipient aged ≥ 60 years <35 9.24 (0.06)a 8.69 (0.10) 0.55 (0.12) 8.19 (0.12) 9.20 (0.08) -1.01 (0.14)   35-39 9.23 (0.14) 8.55 (0.21) 0.68 (0.25) 8.00 (0.26) 8.97 (0.18) -0.97 (0.32)   40-44 9.16 (0.11) 8.51 (0.15) 0.65 (0.19) 8.16 (0.19) 8.84 (0.14) -0.68 (0.24)   45-49 9.12 (0.10) 8.27 (0.18) 0.85 (0.21) 7.58 (0.22) 8.89 (0.16) -1.31 (0.27)   50-54 9.16 (0.10) 7.85 (0.17) 1.31 (0.20) 7.86 (0.18) 8.66 (0.17) -0.80 (0.25)   55-59 9.02 (0.13) 7.55 (0.15) 1.47 (0.20) 7.83 (0.20) 8.49 (0.20) -0.66 (0.28) 8.29 (0.27) 7.96 (0.37) 0.33 (0.52) 7.55 (0.26) 8.78 (0.24) -1.23 (0.35) ≥60 8.84 (0.16) 7.22 (0.18) 1.62 (0.24) 7.63 (0.16) 7.88 (0.22) -0.25 (0.27) 8.78 (0.19) 8.40 (0.28) 0.38 (0.34) 6.86 (0.20) 7.71 (0.23) -0.85 (0.30) aData presented as mean (standard error) White boxes represent non-significant difference in area between recipient and graft survival curves p>0.05; Red boxes represent donor and recipient age strata where the life expectancy of the recipient was greater than that of the donor kidny (p<0.05); Blue boxes represent donor and recipient age strata where the life expectancy of the donor kidney was greater than that of the recipient (p<0.05)     114  Table 6.2. The designation of transplant candidates as young or old relative to the age of the deceased donor kidney.  Deceased donor kidney age Candidate age ≤ 35 years 36-54 years ≥ 55 years 19-54 years Young Young Young 55-59 years Old Old Young ≥ 60 years Old Old Old      115  7 Lifetime of allograft function – a new metric to inform the optimal use of expanded criteria donor kidney transplantation 7.1 Introduction The number of patients awaiting kidney transplantation in the United States (U.S.) recently  eclipsed 100 000.88 Despite these staggering numbers, a high number of deceased donor  kidneys from older aged donors are discarded. For example in 2013, 46% of the N = 1 019  kidneys recovered from deceased donors aged ≥ 65 years were not transplanted.88  This may in part be related to the inclusion of transplant outcomes in hospital accreditations in the U.S.  In the new U.S. kidney allocation scheme, in order to expedite placement and encourage utilization of expanded criteria donor (ECD) kidneys (i.e. donor kidneys with kidney donor profile index >85%), local allocation (allocation within an organ procurement organization (OPO)) will be by-passed and ECD kidneys will be offered at the regional level (allocation within nearby OPOs).110, 111 However, despite evidence that only certain patient groups will benefit from transplantation of ECD kidneys,16 and that patients who will not benefit continue to be listed and transplanted with ECD kidneys112, the new allocation scheme does not restrict which wait-list candidates can receive ECD kidneys. This policy is in contrast to the European Senior Program (ESP) which restricts the transplantation of kidneys from deceased donors ≥ 65 years to recipients ≥ 65 years,  116  while still allowing patients ≥ 65 years the option of waiting for a kidney from a younger deceased donor. Previous work has shown that the discard of ECD kidneys in ESP is significantly lower than that in the United States.113   This chapter reports a series of analyses to inform the optimal use (i.e. allocation) of ECD kidneys. The first set of analyses compared the use and outcomes of ECD kidneys in two transplant systems: ESP and the U.S. The purpose of these analyses was to demonstrate the impact of different policies on the utilization and outcomes of ECD kidney transplantation. The second set of analyses examined the consequences of continuing to allow any consenting wait-list candidate to undergo transplantation with an ECD kidney in the U.S.   Under the new U.S. kidney allocation system, ECDs will be defined by a Kidney Donor Profile Index (KDPI) greater than 85%. The KDPI is a linear scale from 0 -100 % that transforms the relative risk of graft loss for any deceased donor kidney compared to that of a kidney from a donor aged 40 years, with 0% representing the longest projected survival and 100% representing the shortest survival. The KDPI is calculated based on donor age, height, ethnicity, history of hypertension, diabetes, cause of death, serum creatinine, hepatitis C status and donation after circulatory death status.114 Given that KDPI is not utilized in the ESP, and because virtually all (>95%) deceased donors ≥ 65 years would be classified as ECD in the United States, we defined ECD based on deceased donor age ≥ 65 years to maintain consistency in all analyses.   117  7.2 Methods 7.2.1 Comparison of the use and outcomes of ECD kidney transplantation in the Eurotransplant Senior Program and the United States 7.2.1.1 Study population and data sources The study population included recipients of a first, kidney-only transplant from a deceased donor ≥ 65 years of age captured in Eurotransplant or the United States Renal Data System (USRDS).  A significant issue limiting international comparisons of transplant outcomes (i.e. recipient death and graft failure) is lack of validated outcome assessment.115 To overcome this limitation, we restricted the analysis to patients transplanted between January 1, 1999 to December 31, 2003 with follow up through April 30, 2005 because of the availability of rigorous outcome assessment in this cohort of Eurotransplant patients as part of a clinical study.76 Transplant outcomes in the USRDS cohort are routinely validated.15  7.2.1.2 Statistical analyses Donor and recipient characteristics were described using the mean ± standard deviation or median (and quartiles) for continuous variables, or frequencies and proportions for categorical variables; group differences were compared using the t-test, Kruskal Wallis, or Chi-square test as appropriate.  Among the subset of recipients aged ≥ 65 years, we determined the time to all cause graft failure (i.e. patient death or graft failure), time to graft failure (i.e. censored at patient death), and time to death with a functioning graft (i.e. patient death censored at graft loss)  118  in ESP and U.S. patients using the Kaplan-Meier product limit method and compared group differences using the log-rank test. Separate Cox multivariate proportional hazards regression models were used to determine the relative hazard of graft loss from any cause, death censored graft failure, death with a functioning allograft, in ESP compared to U.S. patients after adjustment for differences in: donor characteristics (age, sex, history of diabetes,  history of hypertension, cause of death (cerebrovascular accident versus other), recipient characteristics (age, sex, cause of end-stage renal disease, body mass index, duration of pre-transplant dialysis exposure, peak panel reactive antibody titre (measure of sensitization) and transplant characteristics (cold ischemic time, use of induction therapy (depleting antibody, non-depleting antibody, none), type of calcineurin inhibitor (tacrolimus, cyclosporine, sirolimus), and the use of mycophenolate mofetil or azathioprine). The proportional hazards assumption was tested using log-negative-log plots of the within group survivorship probabilities versus log-time in all models.   The area under survival curves represents the average (or mean) survival.98 We calculated the mean (standard error) patient survival and graft survival for ESP and the U.S. at five years using the Kaplan-Meier product limit method (methods outlined in Chapter 5). The difference (standard error) in mean patient survival and graft survival (i.e. area between survival curves) was then calculated to quantify the time back on dialysis (when patient survival exceeded graft survival) or potential lost graft function (when graft survival exceeded patient survival).    119  7.2.2 Analysis of recipient outcomes after ECD kidney transplantation in the United States 7.2.2.1 Statistical analyses  These analyses included recipients of a first, kidney-only transplantation from a deceased donor aged ≥ 65 years (ECD) captured in the USRDS between January 1, 1995 and December 31, 2010 with follow up through October 31, 2011.   We first determined the distribution of ECD transplants as a function of recipient age with recipient age categorized as follows: 18-39 years, 40-49 years, 50-59 years, 60-64 years, 65-69 years, and ≥ 70 years. In each of the recipient age groups, we calculated the mean patient survival and graft survival (i.e. area under the Kaplan-Meier survival curves), as well as the difference in these curves at ten years after transplantation using the methods described in Section 7.2.1.2.  To determine the extent to which the observed differences between patient survival and graft survival among recipients ≥ 60 years (i.e. age at which ECD kidneys outlive recipients in this cohort) was impacted by increased death after transplantation with an ECD kidney, we compared the patient survival of recipients aged  ≥ 60 years transplanted with an ECD kidney, with that of similar aged recipients who received a kidney from a deceased donor < 65 years with a KDPI 60-69%, 70-79%, 80-85% and >85%, during the same time period using separate Cox multivariate regression analyses adjusted for recipient factors (sex, race, cause of ESRD, peak panel reactive antibody titre, body mass index, primary insurer , comorbidities (inability to ambulate, chronic obstructive  120  pulmonary disease, congestive heart failure, cerebrovascular disease, peripheral vascular disease, cancer and ischemic heart disease)), transplant factors (HLA mismatch, cold ischemic time) and delayed graft function.   Among patients aged < 50 years who received an ECD kidney from a donor ≥ 65 years and suffered death censored allograft failure, we determined the proportion that were relisted for transplantation, their level of sensitization (measured by peak panel reactive antibody titre) at the time of repeat wait-listing, and the proportion subsequently re-transplanted with a either a deceased or living donor. 7.3 Results 7.3.1 Comparison of the use and outcomes of ECD kidney transplantation in the Eurotransplant Senior Program and the United States During the period 1999-2003 the number of deceased donor kidney transplants from donors aged  ≥ 65 years in ESP was 1 870/ 15 715 (12%) compared to only 1 312/ 41 611 (3%)  in the entire U.S.. ESP recipients received kidneys from donors that were older, and more frequently had a history of hypertension compared to U.S. recipients (Table 7.1). More than 80% of ESP recipients were ≥ 65 years compared to only 34% of U.S. recipients. ESP recipients were less likely to have diabetic ESRD or be obese compared to U.S. recipients, but had a longer exposure to dialysis prior to transplantation. Because ESP excludes sensitized patients,76 97% of ESP patients were not sensitized (i.e. peak panel reactive antibody  < 5%). Compared to ESP recipients, U.S. recipients were treated nearly twice as frequently with depleting antibody induction therapy and tacrolimus, and  121  only half as much with azathioprine. The incidence of delayed graft function (ESP: 32%; U.S. 34%) and primary non-function (ESP: 7%; U.S. 6%) were similar in ESP and U.S. recipients. Similar differences were observed among the subset of recipients aged ≥ 65 years (Table 7.2).  Figure 7.1 shows Kaplan-Meier plots comparing transplant outcomes among the N = 1520 ESP and N=446 U.S. recipients who were ≥ 65 years of age at the time of kidney transplantation from a deceased donor ≥ 65 years. The lower all cause graft survival in ESP recipients was due to a higher incidence of death with a functioning graft in U.S. recipients.   Table 7.3 shows the results of separate Cox multivariate regression analyses for the outcomes of graft loss from any cause (including death), graft failure, and death with a functioning graft (patient death censored at graft failure).  Among transplant recipients ≥ 65 years of age, there was a lower risk of graft loss from any cause, and death with a functioning graft in ESP compared to U.S. recipients, but the risk of death censored graft loss was similar in both groups.   Table 7.4 quantifies the difference in mean five-year patient survival and graft survival in ESP and U.S recipients aged ≥ 65 years. ESP recipients were more likely to outlive their kidneys requiring them to return to dialysis for an average of 5.2 months over the five- year follow up period. Among U.S. recipients, graft survival exceeded patient survival by  122  5.0 months, indicating that elderly U.S. recipients ≥ 65 years die with a functioning allograft after ECD transplantation.  7.3.2 Analysis of recipient outcomes after ECD kidney transplantation in the United States.  Figure 7.2 shows the age distribution of N= 5 257  U.S. kidney transplant recipients from a deceased donor ≥ 65 years during the period January 1, 1995 – December 31, 2010.  Figure 7.3 quantifies the difference (in months) between the average patient survival and average graft survival among different recipient age groups at 10 years after transplantation with a deceased donor ≥ 65 years. Among patients 18-39 and 40-49 years, the average patient survival exceeded the average death censored allograft survival. As a result 18-39 year old recipients returned to dialysis for an average (SE) of 32 (4) months, while 40-49 year old patients returned to dialysis for an average (SE) of 21 (3) months in the ten year time period after ECD transplantation. In contrast, among recipients aged 50 -59 years the average patient survival (85 months) and graft survival (83 months) over a ten period were nearly equivalent, while among recipients aged ≥ 60 years patient survival was lower than death censored allograft survival, indicating that on average ECD transplantation provided a lifetime of function for patients ≥ 60 years.  Table 7.5 shows patient survival among recipients aged 60-64,65-69,and ≥70 years who received a kidney from a deceased donor < 65 years with a KDPI 60-69%, 70-79%, 80-85% and >86%, or a deceased donor aged ≥ 65 years.  The unadjusted decrement in ten- 123  year mean patient survival with transplantation from a donor ≥ 65 years compared to a donor < 65 years with KDPI 60-69% was of 8.2 months, 7.3 months and 7.3 months respectively in recipients aged 60-64 years, 65-69 years and ≥70 years.  7.3.2.1 Disposition of recipients <50 year, with a failed ECD transplant  There were N=726 (14%) recipients age ≤ 50 years who underwent transplantation from a donor aged  ≥ 65 years in the U.S. from 1995-2010. Of these, N=408 (56%) suffered graft failure with a median time of 3.1 months (q1-q3: 0.9-6.2), and were forced to return to dialysis or undergo repeat transplantation. Among the graft failures, 196 (48%) were wait-listed with a median time of 7.7 months (q1-q3: 2.3-22.2 months), and the majority of these (61%) were highly sensitized (peak panel reactive antibody > 30%). Thirty-six percent of these patients received a second transplant  [N=121 received a deceased donor transplant with a median time of 25.4 months (q1-q3: 8.6-54.0 months) from first graft failure; N=27 received a living donor transplant with a median time of 3.5 months (q1-q3: 0-17.9 months) from first graft failure].  7.4 Interpretation This study was designed to inform the expanded utilization of ECD kidneys in the United States. The international comparison with ESP patients demonstrated that more liberal use of ECD kidneys (i.e. older with a greater comorbid disease burden) in a restricted patient population ≥ 65 years provided similar graft survival to that achieved in a contemporaneous and similarly aged cohort of U.S. transplant recipients despite better  124  patient survival in the ESP cohort. The inferior patient survival in the U.S. could be related to unaccounted for differences in patient case-mix between European and American transplant recipients aged ≥ 65 years, or due to increased transplant related complications in the U.S. that are not manifest in ESP due to differences in clinical transplant practice. These findings suggest that international collaboration may be very useful in understanding the key determinants of adverse outcomes after ECD transplantation in elderly patients. Specific issues that should be examined include differences in candidate selection, wait-list management, organ preservation, organ allocation and early and late post transplant management that might impact patient survival. For example, it is notable that ESP allocates kidneys from donors aged ≥65 years to recipients aged ≥65 years locally or in a narrow geographic area to minimize cold ischemic time and this resulted in shorter cold times in ESP in our analysis.  The new U.S. allocation policy to forgo local prioritization of ECD kidneys, may paradoxically increase cold ischemic times leading to increased adverse outcomes and resistance to accept ECD offers.     The estimates of the average difference between patient and allograft survival in ESP and U.S. recipients provide insight into the extent to which ECD transplantation succeeds in providing elderly patients with a lifetime of allograft function. Over the five-year follow- up period, we found that on average ECD recipients in ESP would return to dialysis for a period of 5.2 months; while in U.S. recipients, death censored allograft survival exceeded patient survival by an average 5.0 months, indicating that in the U.S., ECDs provide elderly transplant recipients with an expected lifetime of allograft function. The study  125  estimates provide another metric confirming the clinical utility of ECD kidneys in elderly patients, and support expanded use of ECD in elderly patients ≥ 60 years. Although there is limited literature regarding what transplant outcomes would be acceptable to elderly transplant candidates, in our experience most elderly patients would hope to enjoy transplant function for the remainder of their lives. The approach of calculating the difference in patient versus graft failure used in this analysis may therefore be useful in counselling elderly patients regarding the anticipated outcomes after ECD transplantation, especially if coupled with information from previous work from Merion and colleagues demonstrating the benefit of ECD compared to continued wait-listing for a standard criteria donor kidney.45    The second part of our study focused on determining the potential downside of continuing to allow any wait-list candidate to receive an ECD kidney in the new U.S. kidney allocation policy. These analyses demonstrated that transplantation of ECD kidneys provides patients aged < 50 years with an insufficient duration of transplant function and that these patients will have to either return to dialysis or undergo repeat transplantation. Our analysis also showed that fewer than half of these patients are re-listed for transplantation, but are frequently sensitized and are unlikely to receive a repeat transplant. In contrast, among 50-59 year old recipients, ECD kidney transplantation provided nearly equal patient and death censored allograft survival, while in patients ≥ 60 years death graft survival exceeded patient survival, indicating that the majority of ECD kidneys provide patients ≥ 60 years with a lifetime of allograft function.  To what extent the survival of patients ≥ 60 years was shortened by transplantation with an ECD kidney  126  is difficult to determine in this observational study. It is, however, reassuring that we only found a 7-8 month difference in the average ten year patient survival between recipients of a transplant from a donor ≥ 65 years compared to similar aged recipients of a deceased donor kidney transplant from a donor < 65 years with KDPI 60-69%.  Our findings challenge the appropriateness of continuing to allow any consenting patient to accept an ECD kidney, especially when there is evidence that patients who will not benefit from ECD continue to receive ECD transplants. Young transplant recipients have a high likelihood of returning to dialysis, and are highly sensitized when they do, making repeat transplantation unlikely. The added insult of an increase in candidates waiting for transplantation makes repeat transplantation even less likely for young failed transplant recipients. In addition, part of the benefit of ECD transplantation comes with the trade-off of shorter time on dialysis prior to transplantation. By allowing young patients to accept ECD kidneys, the benefit of ECD transplantation for all patients is reduced, and access to transplantation for older candidates becomes more inequitable. In earlier iterations of the kidney allocation policy a broad (15 year) age matching had been proposed for kidneys with a KDPI > 20%.89, 104 However, this proposal was rejected by the U.S. Department of Justice on the grounds that the use of age alone to determine organ allocation was discriminatory. Therefore, the default policy to allow any consenting patient receive and ECD transplant was maintained. Our findings suggest that the European approach to allow elderly patients to opt out of ESP, while prohibiting the transplantation of ECD kidneys in younger candidates, who clearly will not benefit, might have been a better alternative.   Although not specifically examined in our analysis, the allocation of ECD  127  kidneys to younger recipients also limits elderly patients from receiving these kidneys.  Readers of our study should consider the inherent limitation of observational studies and that our findings may not be directly applicable to individual patients. For example, the comparison between ESP and U.S. recipients is confounded by unmeasured differences in patient case-mix, donor characteristics and dialysis and transplant services that differ between the regions. We attempted to mitigate these population differences by restricting our analyses to the same inclusion and outcomes dates, in the same aged patients.  In addition, complete data to measure outcomes in ESP patients was only available until 2005. There may be variation in the acceptance criteria of donors and candidates over time in ESP, as well as improvements in ESP with familiarity of the policy, that may lead to differences in transplant outcomes. In the U.S. we examined the use of ECD kidneys in different recipient age groups, to determine whether ECD transplantation would be appropriate for all aged candidates. It is possible that confounding by indication exists in the allocation of these older donor kidneys. For example, it is possible that younger candidates who are transplanted with older kidneys are inherently sicker than their young candidate counterparts who do not receive these organs. However, even these potentially less well young candidates outlived their ECD kidneys; suggesting that the transplantation of ECD kidneys into any young candidates may be irresponsible.  In summary, these analyses 1) provide robust evidence to encourage increased utilization of ECD kidneys in elderly transplant candidates 2) highlight the need for international collaboration to devise strategies to minimize the risk of death after ECD transplantation,  128  3) suggest the need to carefully evaluate the impact of regional sharing on cold ischemic time in ECD transplants, and 4) challenge the U.S. policy to allow any consenting patient to proceed with ECD transplantation. These observations may be useful in increasing the safe utilization of ECD kidneys in the United States.    7.4.1 Disclosure The data reported here have been supplied by the United States Renal Data System (USRDS). The interpretation and reporting of these data are the responsibility of the author(s) and in no way should be seen as an official policy or interpretation of the U.S. government.       129  Figure 7.1. Kaplan-Meier plots comparing transplant outcomes among the N = 1520 ESP and n=446 U.S. recipients who were ≥ 65 years of age at the time of kidney transplantation from a deceased donor ≥ 65 years. (P<0.0001 for each comparison)                  130  Figure 7.2. Distribution of age of recipients of kidney transplantation from ECD kidneys from 1995-2010.  18-39 40-49 50-59 60-64 65-69 >=70020040060080010001200Recipient age (years)Frequency 131  Figure 7.3. Ten year mean patient and death censored graft survival and difference between curves.    132  Table 7.1. Characteristics of patients who received kidneys from donor aged ≥ 65 years.  ESP    N= 1870   U.S. N=1312  P-Value Donor Characteristics    Age (years) median (q1,q3)  69 (67,73)  69 (66,71)  <0.0001 Age  ≥ 70 years % 882 (47)  462 (35)  <0.0001 Male sex % 879 (47) 586 (45) 0.19 History of diabetes %  130 (7)  109 (8)  0.15 History of hypertension%  989 (53)  626 (48)  <0.01 Cerebrovascular accident as cause of death % 1309 (70)  1022 (78) <0.0001 Recipient Characteristics    Age (years) median (q1,q3) 66 (65,69) 60 (52,67) <0.0001 Age (years) ≥65 years  60-4  55-9  50-54  <50      1520 (81)    118 (  6)      64 (  3)      54 (  3)    114 (  6)   446 (34)  271 (21)  194 (15)  152 (12)  249 (19)   <0.0001  Male sex 1211 (65) 785 (60) <0.01 Race White Black Other  N/A  820 (63) 411 (31)   81 (  6)  -- Cause of ESRD Diabetes Other Missing  171 (9) 1699 (91) --  412 (33) 821 (67) 71  <0.0001 Body mass index (kg/m2) <30 ≥30 missing  1464 (90) 171 (10) 235  743 (75) 247 (25) 322  <0.0001 Time on dialysis (years) Median (q1,q3)  3.36 (1.97, 5.25)  2.85 (1.69, 4.61)  <0.0001 Panel reactive antibody  <5 % 5-30 % >30 % Missing  1802 (97) 44 (2) 20 (1) 4  850 (70) 237 (20) 122 (10) 103  <0.0001 Cold ischemic time (hours)  0-12   12.1-24  >24  Missing   824 (46)  875 (49)    99 (  5)  72    135 (12)   585 (53)   392 (35)  199  <0.0001    133  Table 7.1. Characteristics of patients who received kidneys from donor aged ≥ 65 years.  ESP    N= 1870   U.S. N=1312  P-Value Induction therapy Depleting antibody Non-depleting antibody Neither Missing  264 (16) 489 (31) 839 (53) 278  375 (31) 388 (32) 444 (37) 105  <0.0001 Calcineurin inhibitor Tacrolimus Cyclosporine Sirolimus Missing  426 (28) 1056 (71) 16 (1) 372  660 (58) 390 (34) 93 (8) 169  <0.0001 Anti-metabolite Mycophenolate mofetil Azathioprine Missing  1339 (90) 144 (10) 387  963 (96) 40 (4) 309  <0.0001     134  Table 7.2. Characteristics of patients aged ≥ 65 years who received kidneys from donor aged ≥ 65 years  ESP    N= 1 520  U.S. N=446 P-Value Donor Characteristics    Age (years) median (q1,q3)  69 (67, 73) 69 (67, 72) 0.07 Age  ≥ 70 years % 741 (49) 196 (44) 0.07 Male sex % 704 (46) 192 (43) 0.22 History of diabetes %  113 (7) 40 (9) 0.29 History of hypertension%  842 (55) 228 (51) 0.11 Cerebrovascular accident as cause of death %  1 063 (70)  358 (80)  <0.01 Recipient Characteristics    Male sex 988 (65) 286 (64) 0.73 Race White Black Other  N/A   315 (71) 102 (23) 49 (6)  -- Cause of ESRD Diabetes Other Missing  141 (9) 1379 (91) --  132 (30) 307 (70) 7  <0.0001 Body mass index (kg/m2) <30 ≥30 Missing  1208 (89) 150 (11) 162  293 (82) 65 (18) 88  <0.0001 Time on dialysis (years) Median (q1,q3) 3.36 (2.08, 5.16) 2.58 (1.58,3.87) <0.0001 Panel reactive antibody   <5 % 5-30 % >30 % Missing  1489 (98) 25 (2) 3 (0) 3  315 (73) 86 (20) 30 (7) 15  <0.0001 Cold ischemic time (hours)  0-12   12.1-24  >24  Missing   774 (53) 652  (44) 42 (3) 52  50 (13) 210 (56) 118 (31) 68  <0.0001 Induction therapy Depleting antibody Non-depleting antibody Neither Missing  240 (19) 421 (32) 639 (49) 220  98 (24) 151 (36) 165 (40) 32  <0.01  135  Table 7.2. Characteristics of patients aged ≥ 65 years who received kidneys from donor aged ≥ 65 years  ESP    N= 1 520  U.S. N=446 P-Value Calcineurin inhibitor Tacrolimus Cyclosporine Sirolimus Missing  344 (29) 840 (70) 13 (1) 323  213 (54) 142 (36) 41 (10) 50  <0.0001 Anti-metabolite Mycophenolate mofetil Azathioprine Neither  1107 (90) 119 (10) 294  328 (95) 16 (5) 102  <0.01   Table 7.3. Relative hazard of transplant failure in ESP compared to U.S. transplant recipients     Univariate Multivariate All cause graft loss 0.73 (0.62, 0.86) 0.74 (0.60, 0.93) Graft failure 1.07 (0.83, 1.36) 1.10 (0.79, 1.54) Death with a functioning graft 0.52 (0.42, 0.64) 0.54 (0.40, 0.73) Separate Cox multivariate regression analyses adjusted for differences in donor age, sex, diabetes and hypertension; recipient age, sex, cause of end-stage kidney disease, body mass index, peak panel reactive antibody, time on dialysis prior to transplantation;  immunosuppression and induction therapy at time of transplantation.     136  Table 7.4. Unadjusted mean difference in patient survival versus graft survival in elderly ESP versus U.S. recipients after five years of transplantation  ESP (N=1520) U.S. (N=446) Mean patient survival (years) 4.18 (0.04) 3.63 (0.09) Mean graft survival (years) 3.75 (0.04) 4.05 (0.08) Mean difference in patient and graft survival (years) 0.43 (5.2) 5.2 months -0.42 (-5.0) -5.0 months* * Negative value indicates mean graft survival exceeds mean patient survival  and on average patients will die with a functioning allograft  Table 7.5. Patient survival ten years after transplantation with a donor kidney <65 years stratified by kidney donor profile index and after transplantation from a donor kidney ≥ 65 years    Donor characteristics Patient survival  Area under survival curve in years** Mean (SE) Area under survival curve in months** Mean (SE) Recipient 60-64 years KDPI* 60-69 % KDPI 70-79 % KDPI 80-85 % KDPI ≥86 %  Donor ≥ 65 years 40 42 44 39 30 7.03 (0.09) 7.13 (0.09) 7.09 (0.11) 6.83 (0.08) 6.35 (0.12) 84.36 (1.08) 85.56 (1.08) 85.08 (1.32) 81.96 (0.96) 76.20 (1.44) Recipient  65-69 years  KDPI 60-69 % KDPI 70-79 % KDPI 80-85 % KDPI ≥86 %  Donor ≥ 65 years 35 29 29 32 27 6.68 (0.12) 6.67 (0.11) 6.46 (0.13) 6.43 (0.10) 6.07 (0.12) 80.16 (1.44) 80.04 (1.32) 77.52 (1.56) 77.16 (1.20) 72.84 (1.44) Recipient ≥ 70 years KDPI 60-69 % KDPI 70-79 % KDPI 80-85 % KDPI ≥86 %  Donor ≥ 65 years 21 24 37*** 22 21 6.23 (0.16) 6.20 (0.15) 6.59 (0.18) 5.82 (0.12) 5.62 (0.13) 74.76 (1.92) 74.40 (1.80) 79.08 (2.16) 69.84 (1.44) 67.44 (1.56) *KDPI= kidney donor profile index, in this analysis, this classification is limited to donors aged < 65 years **Area calculated from unadjusted survival curves generated using the Kaplan-Meier product limit method ***N=16 recipients remaining at risk after 10 years  137  8 Multiple wait-listing 8.1 Introduction In a publically funded health care system such as Canada, patients should have equitable access to health services based on need. With the exception of highly sensitized candidates, deceased donor kidneys are not shared between provinces in Canada, and access to transplantation is dependent on regional factors (i.e. the number of transplant candidates and the number of living and deceased organ donors, as well as biologic and immunologic characteristics of the candidate and donor populations differ between regions). There is a 4-fold difference in access to transplantation across Canadian provinces,116 and these geographic differences also exist in other countries such as the United States.117-120  Allocation policies in the United States differ from those in Canada - the U.S. allows the opportunity for parallel wait-listing at more than one transplant centre. In Canada, multiple listing is not permitted, and has resulted in patients gaming the system. For example, there are anecdotal notes of patients living in eastern Ontario, who have chosen to maintain mailing addresses in Quebec so they might be placed on the shorter transplant waiting list in Quebec rather than in their true province of residence, Ontario.  Multiple listing may be advantageous  to candidates with reduced access to transplantation (e.g. candidates who live in regions with long waiting time or those with biologic barriers to transplantation (e.g. Blood Type B)).45  Unfortunately, logistical barriers to multiple wait-listing exist. For example, candidates must undergo a complete transplant evaluation and  138  maintain their medical work up at each centre of listing.44  The costs associated with maintaining a candidate’s status, including travel, may be covered by a private insurer, but are ultimately the responsibility of the candidate.   The policy of multiple listing was last examined in the United States in 2004 publication from Merion et al45 (data until June 2000), a time when the waiting list for transplantation was approximately one third of the current wait-list. Socio-economically advantaged candidates were more likely to be multiply wait-listed,45 perhaps because of  increased ability to pay for the associated costs.  Candidates were more likely to be multiply-listed and transplanted in regions with shorter median waiting times.45 Therefore, the policy of multiple listing may reduce geographic inequities by allowing patients residing in regions with long wait times to access transplantation in regions with shorter wait times. While this policy may create a loophole through which geographic disparities for hard to match transplant candidates (i.e. blood type B) can be reduced, it may not be a fair policy if not accessible to all patients.  In the United States the decision to multiply list candidates for transplantation is at the discretion of the transplant centre.44 Based on OPTN policy 3.2.3, transplant centres are required to provide patients written information about multiple listing, but it is unknown whether individual centres equally support multiple listing. For example, multiple listing was banned by law within the state of New York in 1990, although it has since been reinstated.121 Whether the use and advantage of multiple wait-listing has changed over time as waiting lists for deceased donor kidney transplantation have ballooned in size is  139  uncertain. The objectives of this study were to determine factors associated with multiple wait-listing, as well as longitudinal changes in the utilization and impact of multiple wait-listing on access to transplantation in the United States, as a first step in exploring whether this policy should be considered in Canada.   8.2 Methods  8.2.1 Data source and study population We studied all patients who were actively wait-listed for deceased donor kidney transplantation in the Scientific Registry of Transplant Recipients (SRTR) from January 1, 1995 to December 31, 2010. For each candidate, only the events for the first wait-listing period were included. For example if a patient was wait-listed, underwent transplantation, suffered transplant failure and was wait-listed for a second time, only events from the first wait-listing were included.   This study used data from the Scientific Registry of Transplant Recipients (SRTR). The SRTR data system includes data on all donors, waitlisted candidates, and transplant recipients in the US, submitted by the members of the Organ Procurement and Transplantation Network (OPTN). The Health Resources and Services Administration (HRSA), US Department of Health and Human Services, provides oversight to the activities of the OPTN and SRTR contractors.     140  8.2.2 Statistical analyses Characteristics of candidates who were multiply versus singly listed were compared using the mean ± standard deviation or median (and quartiles) for continuous variables, and frequencies and proportions for categorical variables. Group comparisons were performed using the t-test, Kruskal Wallis test, or Chi-square test as appropriate. 8.2.2.1 Factors associated with multiple wait-listing For this analysis, multiple wait-listing was defined as per Merion et al as “concurrent listings with two or more transplant centres not associated with the same organ procurement organization (OPO)”. 45 An OPO is responsible for registering donors, and coordinating deceased donation in a defined geographic region.122   We determined factors associated with multiple wait-listing (i.e. two or more centres versus one centre) in a multivariate logistic regression model. The model included the following covariates: candidate demographics (i.e. age at wait-listing, sex, race, cause of end-stage renal disease, body mass index), biologic factors(i.e. peak panel reactive antibody titre, ABO blood group), socioeconomic factors (i.e. level of education, employment status, health insurance provider), year of candidate wait-listing (in four equal time periods 1995-1998, 1999-2002, 2003-2006, 2007-2010), and quintile of median waiting time for deceased donor transplantation in the candidate’s primary organ procurement organization of wait-listing. The quintile of waiting time was determined by ranking all 58 organ procurement organizations by the median time to actual deceased donor transplantation within each OPO. To determine factors that were associated with multiple wait-listing at more than two centres, we replicated the above multivariate logistic regression analysis, restricted to  141  multiply wait-listed candidates, and compared candidates wait-listed at three or more centres to candidates listed at only two centres. To describe geographic variation in the practice of multiple wait-listing, we compared the proportion of candidates that were multiply wait-listed in each organ procurement organization. 8.2.2.2 Association of multiple listing with access to deceased donor transplantation The time to first deceased donor transplantation among multiply versus singly wait-listed candidates was determined using the Kaplan-Meier product limit method; group differences were compared using the log-rank test. The time to deceased donor transplantation was censored at living donor transplantation, removal from the wait-list, death on the wait-list and end of follow-up (June 30, 2011). The independent association of multiple wait-listing with deceased donor transplantation in different time periods was determined using Cox multivariate proportional hazards regression analysis with an interaction for year of wait-listing (1995-1998, 1999-2002, 2003-2006, 2007-2010) and multiple wait-listing. All Cox multivariate models were adjusted for: candidate demographics (i.e. age at wait-listing, sex, race, cause of end-stage renal disease, body mass index), biologic factors(i.e. peak panel reactive antibody titre, ABO blood group), socioeconomic factors (i.e. level of education, employment status, health insurance provider), year of candidate wait-listing (1995-1998, 1999-2002, 2003-2006, 2007-2010), and quintile of median waiting time for deceased donor transplantation in the candidate’s primary (first) OPO of wait-listing. The proportional hazards assumptions were tested using log-negative-log plots. In addition, we calculated the median time to deceased donor transplantation between multiply versus singly wait-listed candidates across all  142  covariates above using the Kaplan-Meier product limit method, and also determined the proportion of multiply versus singly listed candidates who received deceased donor transplantation within 5 years of wait-listing.    All analyses were performed in SAS 9.4, Carey, NC. 8.3 Results Among 310,475 actively wait-listed candidates during the study period, only 24,945 (8%) were multiply listed: of these, N=22 245/24,945 (89%) candidates were listed at two centres; N=2,228 (9%) were listed at three centres; and N=472 (2%) were listed at more than three centres; maximum N=1 at nine centres. The proportion of candidates multiply wait-listed varied more than ten-fold across OPOs (2 to 35%) (Figure 8.1). The likelihood of being multiply wait-listed at two or more centres versus being singly listed increased over time: multivariate OR (95% CI): 1995-1998 (reference); 1.13 (1.09, 1.18) 1999-2002; 1.18 (1.12, 1.23) 2003-2006; 1.36 (1.29, 1.42) 2007-2010 (Figure 8.2). 8.3.1 Factors associated with multiple wait-listing Multiply listed patients were more likely to be younger, male, and of White or Asian race (Table 8.1) Candidates were also more likely to be multiply wait-listed if they did not have diabetes as their cause of renal disease, and if they had biologic barriers to transplantation (i.e. peak panel reactive antibody > 30%, or blood group O and B compared to A). Socioeconomic factors also impacted the likelihood of transplantation; candidates were more likely to be working full-time, have a high-school or higher level  143  of education, but were less likely to be insured by Medicaid and most likely insured by Medicare Fee For Service or other public insurers. Candidates unable to work due to a disability were less likely to be multiply listed. The likelihood of being multiply listed increased by 6% per increasing quintile of OPO waiting time.   Among candidates who were multiply listed, candidates who were listed at three or more centres compared to two centres were more likely to be older, White or Asian and not have diabetes as their cause of ESRD (Table ). Candidates wait-listed at more than two centres were also more likely to have biologic barriers to transplantation (i.e. peak panel reactive antibody > 30%, or blood group O and B compared to A). Candidates with higher education were also more likely to be multiply listed at three or more centres. The relative odds of being wait-listed at three or more centres relative to two centres did not increase over time.  8.3.2 Association of multiple wait-listing with access to deceased donor transplantation Nearly 50% (N=12,021) of multiply wait-listed candidates received deceased donor transplantation during an average follow-up time 6.1 (4.1) years, and of these 61% were transplanted in their primary listing OPO.  In comparison only 37 % of singly wait-listed candidates underwent deceased donor transplantation with an average follow-up time of 5.8 (4.2) years (p<0.0001).    144  The time to deceased donor transplantation was shorter for multiply versus singly wait-listed candidates [median (q1,q1): 2.43 years (1.15, 4.23) for patients listed at three or more centres; 3.08 years (1.43, 5.43) for patients  listed at two centres; and 3.86 years (1.68, 7.38) for patients listed at one centre]. The relative adjusted hazard of deceased donor transplantation among multiply wait-listed candidates versus singly listed candidates was 1.37 (1.34, 1.39) and this increased with wait-listing at more than two centres [HR (95% CI): 1.00 singly listed; 1.33 (1.30, 1.36) listed at two centres; 1.71 (1.63, 1.80) listed at three or more centres]. The advantage of multiple wait-listing for deceased donor transplantation increased over time [HR (95% CI): 1.09 (1.04, 1.13) 1995-1998; 1.26 (1.21, 1.31) 1999-2002; 1.48 (1.43, 1.54) 2003-2006; 1.99 (1.91, 2.07) 2007-2010]. (Figure 8.3)  In univariate analysis, every subgroup benefited from multiple wait-listing, with the exception of pediatric candidates and candidates in organ procurement organizations with the shortest waiting times for transplantation (Table). This translated into clinically and statistically significant differences in deceased donor transplantation among subgroups. For example the proportion of ABO blood group B patients (39% versus 29%); PRA> 30% (48% versus 34%); and candidates listed in organ procurement organizations with waiting time > 2 years (41% versus 22%) that were transplanted after five years of wait-listing was significantly higher in multiply listed patients (p<0.0001 for all comparisons) (Figure 8.4).   145  8.4 Discussion This national cohort study examined the longitudinal use and outcomes of the practice of multiple wait-listing for deceased donor transplantation.  The use of multiple wait-listing was infrequent (8% of all candidates wait-listed for deceased donor kidney transplantation were multiply listed), and increased over time. The practice of multiple wait-listing varied geographically; and the majority of multiply wait-listed candidates were listed at only one additional centre. Candidates were more likely to be multiply wait-listed if they had biologic barriers to transplantation or if they were socio-economically advantaged, and this was consistent over time.   Nearly 50% of multiply wait-listed candidates were transplanted during the study period, and 40% of these transplants occurred outside the OPO of primary wait-listing, emphasizing the advantage of the multiple wait-listing policy. Additional wait-listing, at more than two centres, increased the likelihood of deceased donor transplantation. All candidates benefited by multiple wait-listing except for pediatric candidates and those living in regions with the shortest waiting times. The advantage of multiple wait-listing on the likelihood of accessing deceased donor transplantation increased in more recent years.  These results extend the findings by Merion et al by examining the longitudinal increase in access to multiple listing, as well as the longitudinal increase in the benefit of multiple wait-listing. In addition, this study also describes the use of wait-listing at more than two  146  centres, the increased likelihood of transplantation with wait-listing at more than two centres, and which candidates were taking advantage of this policy.    The opportunity for multiple wait-listing may not be known or available to every candidate.  Multiple wait-listing may be more accessible to certain advantaged populations and may be restricted by financial and educational barriers.  The number of candidates on the waiting list for deceased donor kidney transplantation continues to increase over time (currently >100,000 patients), resulting in longer times to deceased donor transplantation for all candidates, and these times are exaggerated for candidates with biologic, and geographic barriers to transplantation. Given that there is a significant increase in deceased donor transplantation with multiple wait-listing across all candidate subgroups, it is surprising that only a small proportion of candidates are exploiting the opportunity to multiply wait-list, and concerning that there is great heterogeneity in candidates who are multiply listed compared to those who are not. It is possible that certain transplant centres encourage multiple listing of biologically difficult to transplant candidates, thereby decreasing inequity in access to transplantation in these patients; however the selective socio-economic and demographic characteristics of multiply listed patients suggests a disparity in access to multiple listing, enhancing an already existing advantage in accessing deceased donor transplantation in these groups.   The practice of multiple listing is advantageous to those who are multiply listed, but will naturally increase the time to transplantation for singly listed individuals in regions that allow multiple listing. If this practice was widely utilized by candidates in geographic  147  regions with inferior access to transplantation, this policy could reduce geographic inequities in access to transplantation. However, if transplant centres in regions with good or superior access to transplantation begin to exploit this policy, geographic disparities in access to transplantation could get larger.  This study has limitations. First, we did not have access to data on candidate income, therefore our analysis of economic factors influencing the decision to multiply wait-list may be limited. However, the strong association of increased education, non-Medicaid insurance, employment, and White race with the practice of multiple wait-listing suggests that certain population subgroups are advantaged in their access to this policy. Given the financial burden associated with the pre-transplant evaluation at each centre of wait-listing, and the logistics of traveling to another centre to maintain evaluation, or undergo transplantation, it is important that we fully understand the impact of cost as a barrier to multiple wait-listing so we can determine methods to mediate this deterrent for socio-economically disadvantaged populations.  Second, we were not able to identify the OPOs geographically (i.e. de-identified data), and were therefore unable to link them by proximity to one another.  However, the more than ten-fold variation in the proportion of multiply wait-listed candidates across OPOs suggests that geographic variation in the use of multiple wait-listing is ubiquitous across the U.S. It is not clear to what extent multiple wait-listing is an integral part of the medical practice in some transplant centres, or whether it is a practice sought out on occasion by keen patients, or physicians who are trying to help a very difficult to match candidate access transplantation. Because this  148  practice has the potential to mediate geographic disparities in access to transplantation, perhaps national regulations about the use of multiple wait-listing should be revisited. 8.4.1 Conclusion The policy of multiple wait-listing is associated with a higher likelihood of deceased donor transplantation and this advantage is increasing over time. In addition, it appears that the use of multiple wait-listing is reserved for a selected and advantaged population and may not be equally promoted as an option in all centers. Given the advantage, all patients should be made aware of this policy and mechanisms to minimize economic barriers to multiple listing (i.e. sharing of information between centers) and/or waiving of the listing fee for a limited group of patients with biological barriers might be appropriate.  Given the organ shortage, ensuring that all difficult to transplant candidates have an equal opportunity to take advantage of this policy irrespective of socio-economic barriers is essential. 8.4.2 Disclosure The data reported here have been supplied by the Minneapolis Medical Research Foundation (MMRF) as the contractor for the Scientific Registry of Transplant Recipients (SRTR). The interpretation and reporting of these data are the responsibility of the author(s) and in no way should be seen as an official policy of or interpretation by the SRTR or the U.S. Government.  149  Figure 8.1. The odds ratio of multiple listing by year of candidate wait-listing compared to candidates wait-listed between 1995 and 1998 (error bars represent 95% confidence intervals). The model included the following covariates: candidate demographics (i.e. age at wait-listing, sex, race, cause of end-stage renal disease, body mass index), biologic factors (i.e. peak panel reactive antibody titre, ABO blood group), socioeconomic factors (i.e. level of education, employment status, health insurance provider), and quintile of median waiting time for deceased donor transplantation in the candidate’s primary centre of wait-listing.  Figure 8.2. The proportion of candidates multiply listed by organ procurement organization of wait-listing     0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1995-1998 1999-2002 2003-2006 2007-2010 Odds                          ratio Year of candidate wait-listing 0 5 10 15 20 25 30 35 40 % Organ procurement organizations National percent= 8.0  150  Figure 8.3. The relative hazard of transplantation over time for multiply versus singly wait-listed candidates (reference=1.00 singly wait-listed) in different years of transplantation. The model was adjusted for: candidate demographics (i.e. age at wait-listing, sex, race, cause of end-stage renal disease, body mass index), biologic factors (i.e. peak panel reactive antibody titre, ABO blood group), socioeconomic factors (i.e. level of education, employment status, health insurance provider), and quintile of median waiting time for deceased donor transplantation in the candidate’s primary centre of wait-listing.   Figure 8.4. The proportion of patients who were transplanted at five years after wait-listing date.     0 0.5 1 1.5 2 2.5 1995-1998 1999-2002 2003-2006 2007-2010 Hazard  ratio Year of candidate wait-listing 0 10 20 30 40 50 60 PRA                        31-80 PRA>80 ABO         B ABO         O Black Hispanic Asian OPO Wait           > 2 y % Multiply Wait-listed Singly Wait-listed  151  Table 8.1. Characteristics of multiply versus singly listed wait-listed candidates (N=310,475)  Singly listed  N=285 530 Listed at two centers N= 22 245 Listed at more than 2 centers N=2 700 Univariate  p-value Age at listing (years) <18 18-39 40-59 ≥60  8,937 (3) 59,230 (21) 142,757 (50) 74,606 (26)  271 (1) 5420 (24) 11 351 (51) 5203 (24)  12 (0) 602 (22) 1337 (50) 749 (28)   <0.0001 Male sex 170,481 (60) 13 471 (61) 1634 (61) 0.0328 Race White Black Hispanic Asian Other  136,526 (48) 83,414 (29) 44,510 (16) 15,438 (5) 5,642 (2)  11 258 (51) 6 308 (28) 2 771 (12) 1 570 (7) 338 (2)  1 682 (62) 563 (21) 217 (8) 210 (8) 28 (1)  <0.0001 Diabetes as cause of ESRD 90,465 (32) 5 306 (24) 455 (17) <0.0001 BMI (kg/m2) <25 25-29.9 30-34.9 35-39.9 ≥ 40 Missing  90,360 (33) 91,544 (33) 58,278 (21) 25,396 (9) 8,291 (3) 11,661  6 970 (33) 7 442 (35) 4 646 (22) 1 865 (9) 417 (2) 905  892 (35) 875 (34) 566 (22) 188 (7) 43 (2) 136  <0.0001 PRA ≤ 30 31-79 ≤ 80 Missing*  197,226 (84) 22,258 (9) 16,588 (7) 49,458  15 242 (81) 1 833 (10) 1 701 (9) 3 469  1 782 (77) 269 (12) 277 (12) 372  <0.0001 Abbreviations: ESRD End-stage renal disease; BMI Body mass index; PRA panel reactive antibody; GED general educational development diploma. *Missing: BMI (4%);  PRA (17%);  Education Level (17%); Employment Status (11%); Deceased donor transplant centre waiting time (<0.0001 %); Health Insurance Provider (0.3%) **Other Public includes: Children’s Health Insurance Program, Department of Veteran Affairs, Other government, Medicare unspecified ***Other include: Self, Donation, Free care, Pending, Foreign government   152  Table 8.1. Characteristics of multiply versus singly listed wait-listed candidates (N=310,475)   Singly listed  N=285 530 Listed at two centers N= 22 245 Listed at more than 2 centers N=2 700 Univariate  p-value ABO blood group A B AB O  96,590 (34) 40,744 (14) 11,557 (4) 136,639 (48)  6 464 (29) 3 588 (16) 626 (3) 11 567 (52)  715 (26) 494 (18) 71 (3) 1420 (53)  <0.0001 Education level ≤ High school/ GED College/ technical school Bachelor degree Graduate degree Missing*  137,379 (58) 54,855 (23) 32,165 (13) 13,221 (6) 47,910 (17)  8 445 (45) 4 893 (26) 3 544 (19) 1 682 (9) 3 681  728 (32) 610 (27) 553 (24) 389 (17) 420  <0.0001 Employment status Working Retired Unemployed Disability/ Disease Missing*  91,467 (36) 16,862 (7) 100,977 (40) 44,717 (17) 31,507  8 041 (40) 1 142 (6) 7 965 (40) 2 925 (15) 2 172  1 097 (45) 158 (6) 869 (35) 325 (13) 251  <0.0001 Health insurance provider Private Medicaid Medicare Fee For Service Medicare + Choice Other Public** Other*** Missing*  128,421 (45) 24,863 (9) 44,618 (16) 18,969 (6) 64,637 (23) 3,304 (1) 718  10  329 (47) 1 053 (5) 4 241 (19) 1 304 (6) 4 962 (22) 273 (1) 83  1 328 (49) 52 (2) 481 (18) 134 (5) 640 (24) 53 (2) 12  <0.0001 Abbreviations: ESRD End-stage renal disease; BMI Body mass index; PRA panel reactive antibody; GED general educational development diploma. *Missing: BMI (4%);  PRA (17%);  Education Level (17%); Employment Status (11%); Deceased donor transplant centre waiting time (<0.0001 %); Health Insurance Provider (0.3%) **Other Public includes: Children’s Health Insurance Program, Department of Veteran Affairs, Other government, Medicare unspecified ***Other include: Self, Donation, Free care, Pending, Foreign government   153  Table 8.1. Characteristics of multiply versus singly listed wait-listed candidates (N=310,475)   Singly listed N=285 530 Listed at two centers N= 22 245 Listed at more than 2 centers N=2 700 Univariate  p-value Quintiles of median time to deceased donor transplantation in candidate’s primary organ procurement organization  ≤ 1.15 years 1.16-1.33 years 1.34-1.60 years 1.61-1.91 years ≥ 1.92 years Missing*      12,527 (5) 37,796 (13) 51,833 (18) 71,830 (25) 111,541 (39) 3      1 110 (5) 4 085 (18) 2 186 (10) 4 136 (19) 10 728 (48)       85 (3) 516 (19) 241 (9) 581 (22) 1 277 (47)      <0.0001 Year of wait-listing 1995-1998 1999-2002 2003-2006 2007-2010   54 886 (19) 61 867 (22) 75 853 (27) 92 924 (32)   3 738 (17) 4 628 (21) 6 130 (27) 7 749 (35)   499 (18) 629 (23) 663 (25) 909 (34)   <0.0001 Abbreviations: ESRD End-stage renal disease; BMI Body mass index; PRA panel reactive antibody; GED general educational development diploma. *Missing: BMI (4%);  PRA (17%);  Education Level (17%); Employment Status (11%); Deceased donor transplant centre waiting time (<0.0001 %); Health Insurance Provider (0.3%) **Other Public includes: Children’s Health Insurance Program, Department of Veteran Affairs, Other government, Medicare unspecified ***Other include: Self, Donation, Free care, Pending, Foreign government   154  Table 8.2. The multivariate odds ratio for a candidate being multiply (two or more centres) versus singly wait-listed for deceased donor transplantation.  Odds Ratio (95% CI) Age at wait-listing <18 18-39 40-59 ≥60  1.00 2.76 (2.44, 3.14) 2.38 (2.10, 2.70) 2.00 (1.76, 2.27) Male sex 1.06 (1.03, 1.09) Race White Black Hispanic Asian Other  1.18 (1.14, 1.21) 1.00 0.91 (0.87, 0.95) 1.29 (1.22, 1.37) 0.90 (0.81, 1.01) Diabetes as cause of ESRD Other cause of ESRD 1.00 1.52 (1.47, 1.57) BMI (kg/m2) <25 25-29.9 30-34.9 35-39.9 ≥ 40  1.00 1.07 (1.03, 1.10) 1.08 (1.04, 1.12) 0.97 (0.92, 1.03) 0.66 (0.60, 0.73) PRA ≤ 30 31-79 ≤ 80  1.00 1.11 (1.06, 1.17) 1.44 (1.37, 1.52) ABO blood group A B AB O  1.00 1.36 (1.30, 1.42) 0.80 (0.73, 0.86) 1.32 (1.28, 1.36) Abbreviations: ESRD End-stage renal disease; BMI Body mass index; PRA panel reactive antibody; GED general educational development diploma. *Missing: BMI (4%);  PRA (17%);  Education Level (17%); Employment Status (11%); Deceased donor transplant centre waiting time (<0.0001 %); Health Insurance Provider (0.3%) **Other Public includes: Children’s Health Insurance Program, Department of Veteran Affairs, Other government, Medicare unspecified ***Other include: Self, Donation, Free care, Pending, Foreign government  155  Table 8.2. The multivariate odds ratio for a candidate being multiply (two or more centres) versus singly wait-listed for deceased donor transplantation.  Odds Ratio (95% CI) Education ≤ High school/ GED College/ technical school Bachelor degree Graduate degree  1.00 1.40 (1.35, 1.45) 1.78 (1.70, 1.85) 2.18 (2.07, 2.30) Employment status Working Retired Unemployed Disability/ Disease  1.03 (1.00, 1.07) 0.98 (0.92, 1.06) 1.00 0.92 (0.88, 0.97) Health insurance provider Private Medicaid Medicare Fee For Service Medicare + Choice Other Public* Other**  1.67 (1.56, 1.78) 1.00 2.18 (2.04, 2.34) 1.57 (1.45, 1.71) 2.09 (1.95, 2.24) 1.85 (1.62, 2.11) Quintile of median time to deceased donor transplantation in candidate’s primary organ procurement organization  1.06 (1.05, 1.05) Year of wait-listing 1995-1998 1999-2002 2003-2006 2007-2010  1.00 1.13 (1.09, 1.18) 1.18 (1.12, 1.23) 1.36 (1.29, 1.42) Abbreviations: ESRD End-stage renal disease; BMI Body mass index; PRA panel reactive antibody; GED general educational development diploma. *Missing: BMI (4%); PRA (17%); Education Level (17%); Employment Status (11%); Deceased donor transplant centre waiting time (<0.0001 %); Health Insurance Provider (0.3%) **Other Public includes: Children’s Health Insurance Program, Department of Veteran Affairs, Other government, Medicare unspecified ***Other include: Self, Donation, Free care, Pending, Foreign government   156  Table 8.3.  Among candidates who are multiply wait-listed for deceased donor kidney transplantation, the multivariate odds ratio of being listed singly at more than two centres versus two centres.  Odds Ratio (95% CI) Age at listing <18 18-39 40-59 ≥60  1.00 2.06 (1.14, 3.74) 2.12 (1.17, 3.84) 2.56 (1.41, 4.64) Male sex 1.05 (0.96, 1.15) Race White Black Hispanic Asian Other  1.58 (1.42, 1.75) 1.00 1.02 (0.86, 1.21) 1.42 (1.19, 1.69) 1.00 (0.67, 1.49) Diabetes as cause of ESRD Other cause of ESRD 1.00 1.52 (1.36, 1.69) BMI (kg/m2) <25 25-29.9 30-34.9 35-39.9 ≥ 40  1.00 0.95 (0.86, 1.05) 1.05 (0.94, 1.18) 0.91 (0.77, 1.08) 0.98 (0.71, 1.36) PRA ≤ 30 31-79 ≤ 80  1.00 1.31 (1.13, 1.51) 1.49 (1.29, 1.73) Abbreviations: ESRD End-stage renal disease; BMI Body mass index; PRA panel reactive antibody; GED general educational development diploma. *Missing: BMI (4%);  PRA (17%);  Education Level (17%); Employment Status (11%); Deceased donor transplant centre waiting time (<0.0001 %); Health Insurance Provider (0.3%) **Other Public includes: Children’s Health Insurance Program, Department of Veteran Affairs, Other government, Medicare unspecified ***Other include: Self, Donation, Free care, Pending, Foreign government      157  Table 8.3. Among candidates who are multiply wait-listed for deceased donor kidney transplantation, the multivariate odds ratio of being listed singly at more than two centres versus two centres.  Odds Ratio (95% CI) ABO blood group A B AB O  1.00 1.33 (1.17, 1.51) 0.99 (0.76, 1.21) 1.18 (1.07, 1.30) Education ≤ High school/ GED College/ technical school Bachelor degree Graduate degree  1.00 1.39 (1.24, 1.56) 1.67 (1.48, 1.88) 2.35 (2.04, 2.71) Employment Status Working Retired Unemployed Disability/ Disease  1.00 (0.89, 1.12) 0.86 (0.70, 1.07) 1.00 0.94 (0.80, 1.11) Health Insurance Provider Private Medicaid Medicare Fee For Service Medicare + Choice Other Public* Other**  1.94 (1.45, 2.59) 1.00 1.94 (1.43, 2.62) 1.87 (1.33, 2.62) 2.10 (1.56, 2.84) 2.93 (1.94, 4.43) Quintile of median time to deceased donor transplantation in candidate’s primary organ procurement organization  1.04 (0.92, 1.19) Abbreviations: ESRD End-stage renal disease; BMI Body mass index; PRA panel reactive antibody; GED general educational development diploma. *Missing: BMI (4%);  PRA (17%);  Education Level (17%); Employment Status (11%); Deceased donor transplant centre waiting time (<0.0001 %); Health Insurance Provider (0.3%) **Other Public includes: Children’s Health Insurance Program, Department of Veteran Affairs, Other government, Medicare unspecified  ***Other include: Self, Donation, Free care, Pending, Foreign government       158   Table 8.3. Among candidates who are multiply wait-listed for deceased donor kidney transplantation, the multivariate odds ratio of being listed singly at more than two centres versus two centres.   Odds Ratio (95% CI) Year of wait-listing 1995-1998 1999-2002 2003-2006 2007-2010  1.00 1.05 (0.92, 1.19) 0.86 (0.75, 0.99) 0.95 (0.83, 1.10) Abbreviations: ESRD End-stage renal disease; BMI Body mass index; PRA panel reactive antibody; GED general educational development diploma. *Missing: BMI (4%);  PRA (17%);  Education Level (17%); Employment Status (11%); Deceased donor transplant centre waiting time (<0.0001 %); Health Insurance Provider (0.3%) **Other Public includes: Children’s Health Insurance Program, Department of Veteran Affairs, Other government, Medicare unspecified  ***Other include: Self, Donation, Free care, Pending, Foreign government     159  Table 8.4. Median time to deceased donor kidney transplantation among multiply versus singly wait-listed candidates. Table shows median (q1, q3) years.  Multiply Listed Singly Listed Log Rank P-value Overall  3.01 (1.39, 5.32) 3.86 (1.68, 7.38) <0.0001 Age at Listing <18 18-39 40-59 ≥60  1.58 (0.63, 2.82) 3.11 (1.44, 5.61) 3.11 (1.45, 5.43) 2.66 (1.26, 4.75)  1.01 (0.34, 1.89) 3.67 (1.67, 6.48) 4.02 (1.83, 7.71) 4.17 (1.85, 11.24)  <0.0001 Male  Female 2.87 (1.32, 4.95) 3.18 (1.50, 6.11) 3.69 (1.64, 6.83) 4.10 (1.74, 8.51) <0.0001 Race White Black Hispanic Asian Other  2.49 (1.15, 4.53) 3.60 (1.76, 6.06) 3.59 (1.73, 6.55) 3.40 (1.72, 5.52) 3.39 (2.06, 8.15)  3.00 (1.23, 6.07) 4.38 (2.14, 8.25) 4.78 (2.18, 8.77) 4.72 (2.52, 7.68) 4.46 (2.37, 9.13)  <0.0001 Diabetes as the cause of ESRD Other cause of ESRD 3.21 (1.39, 5.99) 2.94 (1.39, 5.19) 4.55 (2.02, 11.23) 3.58 (1.56, 6.75) <0.0001 BMI (kg/m2) <25 25-29.9 30-34.9 35-39.9 ≥ 40  2.86 (1.27, 5.17) 2.97 (1.40, 5.24) 3.05 (1.47, 5.24) 3.39 (1.67, 6.02) 4.44 (2.33, 8.26)  3.35 (1.33, 6.63) 3.74 (1.69, 7.19) 4.08 (1.94, 7.59) 4.74 (2.41, 10.15) 6.10 (3.17, .)  <0.0001 PRA ≤ 30 31-79 ≤ 80  2.67 (1.22, 4.69) 3.31 (1.59, 5.73) 5.57 (2.41, NA)  3.45 (1.47, 6.46) 4.79 (2.48, 8.50) 6.66 (2.73, NA)  <0.0001 Abbreviations: ESRD End-stage renal disease; BMI Body mass index; PRA panel reactive antibody; GED general educational development diploma. **Other Public includes: Children’s Health Insurance Program, Department of Veteran Affairs, Other government, Medicare unspecified ***Other include: Self, Donation, Free care, Pending, Foreign government       160  Table 8.4. Median time to deceased donor kidney transplantation among multiply versus singly wait-listed candidates. Table shows median (q1, q3) years.  Multiply Listed Singly Listed Log Rank P-value ABO blood group A B AB O  2.27 (0.98, 4.03) 3.68 (2.00, 6.36) 1.33 (0.50, 3.01) 3.31 (1.63, 5.68)  2.79 (1.17, 5.85) 4.77 (2.46, 9.03) 1.72 (0.61, 4.04) 4.49 (2.17, 7.99)  <0.0001 Quintiles of median time to deceased donor transplantation in candidate’s primary organ procurement organization (years) ≤ 1.15  1.16-1.33 1.34-1.60 1.61-1.91 ≥ 1.92     1.56 (0.62, 3.30) 2.18 (1.11, 3.66) 2.71 (1.45, 4.46) 2.88 (1.33, 5.00) 3.71 (1.69, 6.13)     1.22 (0.4, 2.72) 1.89 (0.82, 3.66) 2.72 (1.28, 5.11) 3.52 (1.80, 6.51) 5.60 (3.32, 10.38)   <0.0001 Era of Transplantation 1995-1998 1999-2002 2003-2006 2007-2010  2.68 (1.14, 4.97) 3.17 (1.47, 5.51) 3.00 (1.37, 5.37) 3.03 (1.53, NA)  2.61 (0.92, 5.41) 3.66 (1.56, 7.04) 4.10 (1.84, 8.04) NA  (2.44, NA)  <0.0001 Abbreviations: ESRD End-stage renal disease; BMI Body mass index; PRA panel reactive antibody; GED general educational development diploma. **Other Public includes: Children’s Health Insurance Program, Department of Veteran Affairs, Other government, Medicare unspecified ***Other include: Self, Donation, Free care, Pending, Foreign government  161  9 Conclusion 9.1 Summary  Kidney transplantation is the preferred treatment for patients with end-stage renal disease, but the need for transplantation exceeds the availability of transplantable organs. Multiple strategies to address the shortage of this scarce health resource are needed. One solution is to increase the number of deceased organ donors. Another solution is to optimize the allocation of the available deceased donor kidneys, such that waste of deceased donor kidneys is reduced, and outcomes for the transplant candidate population are improved. Specifically, allocating kidneys by matching the ages of a deceased donor kidney to that of a transplant candidate would reduce the need for return to dialysis or repeat transplantation. Matching candidate and deceased donor kidney ages has not been widely implemented due to the potential to introduce inequities in access to kidney transplantation for patients in different age groups.  Another challenge in deceased donation is geographic disparity in access to transplantation. Despite universal access to health care, there is more than a four-fold difference in access to deceased donor transplantation across Canadian provinces. Strategies to assess these inequities have been neither proposed nor implemented.   Therefore the objectives of this thesis were: 1) to develop an improved metric for deceased donation activity ; 2) to quantify inefficiency in allocation, and define age- 162  matching allocation cut-points; and 3) to examine a wait-listing policy that may reduce inequity in access to transplantation.   The research chapters of this thesis were written with the intent of publishing the results elsewhere. As such, the strengths and limitations as well as the conclusions of each chapter have been discussed throughout the text. The purpose of this concluding chapter is to synthesize and summarize the key findings and contributions, integrate the strengths and limitations, and put forth overall recommendations and implications for this research.  9.2 Key findings and contributions 9.2.1 Estimating the number of potential deceased donors The donor rate per million population is the most commonly reported metric for deceased donation, but is flawed because it does not account for regional differences in mortality. Chart audits are the gold standard, but are resource intensive, and infeasible in real-time. In Chapter 2, a practical and timely method to estimate the number of potential deceased donors among in-hospital patient deaths using existing administrative data was described. In addition, this method was assessed for accuracy in a subset of Manitobans, and was used to determine the conversion of potential donors to actual donors in different subgroups. Using the described method, we determined that fewer than 3% of patients who die in Canadian hospitals are eligible for solid organ donation, and the overall conversion ratio of potential donors to actual donors is only 15%. Our study method overestimated the number of potential donors from a Manitoba chart review by two-fold. After accounting for this overestimate we found there is significant potential to increase  163  deceased donation in Canada. The use of administrative data to estimate donor potential is an important advancement. Although the study method of identifying potential donors is not perfect it can be used in conjunction with chart audits to inform strategies to increase deceased donation.  This method is important because it provides a feasible and cost-effective measure for deceased donation that accounts for regional and secular variation in differences in characteristics of deaths. The study method will be used alongside the donor rate per million in future CORR annual data reports. The results from this study are valuable as they challenge previously reported data that there are no unaccounted for potential deceased donors in Canada, and suggest that a doubling of the number of potential donors may be possible.  9.2.2 Defining equitable utility-based cut-points for age matching The adoption of new strategies to increase the efficiency of deceased donor kidney allocation (i.e. minimizing the difference in recipient and donor kidney survival) depends primarily on balancing the principles of utility and justice. Chapter 3 lays out the considerations for deceased donor kidney allocation from the perspectives of the transplant candidate and the policy maker. In the following research chapters (Chapters 5, 6 and 7), allocation was discussed from the point-of-view of the policy maker (i.e. the decision maker responsible for allocating deceased donor kidneys for the maximal benefit of the pool of transplant candidates).    164  In response to the rapid growth of the deceased donor kidney waiting list relative to the supply of donor kidneys, there is consensus in the transplant community to reduce extreme mismatches in deceased donor kidney and recipient life expectancies through revised allocation strategies. In this thesis, deceased donor kidney age and candidate age were used as surrogates of deceased donor kidney and candidate life expectancies to examine allocation using donor-candidate age matching. Chapter 5 uses the area between survival curves to categorize the type and quantity of inefficiency in deceased donor kidney allocation. The application is novel in its description of organ waste and return to dialysis as measures of inefficiency (positive and negative area between survival curves), and importantly accounts for differences between recipient and graft survival that occurs across all age groups, not just at age extremes. The data as presented do not assume a given strategy for age matching, but allow for variation in deceased donor kidney allocation based on the importance of either reducing organ waste, or time back on dialysis. These measures of inefficiency can be created for different populations (e.g. countries, provinces) to compare allocation strategies over time.   In Chapter 6, the calculations of inefficiency from Chapter 5 were expanded, and used in combination with information on the number of candidates and deceased donor kidneys to define equitable utility-based age cut-points for allocation by age matching. The study in Chapter 6 provides the first nominal description of a young and an old donor with respect to the other. For example, a candidate can be considered to be young or old when compared to two different aged donor kidneys. This information also provides the first evidence-based definitions for young and old donor kidney ages in Canada.   165  There has been uptake of these recommendations across Canada, and age-matching has since been implemented in most provinces across Canada. Of note, the inclusion of age-matching in deceased donor kidney allocation varies slightly by province, taking into account regional variation in donor kidney and candidate ages.   9.2.3 Implications of not age-matching The allocation of ECD kidneys varies in different countries. By definition, ECD kidneys have inferior graft survival compared to younger and healthier donor kidneys. It has also been suggested that transplantation with ECD kidneys may be associated with reduced survival compared to transplantation with younger and healthier donor kidneys.70 The analysis in Chapter 7, describes the use, outcomes and allocation inefficiencies (i.e. area between recipient and graft survival curves) of ECD kidneys in two different allocation systems: the Eurotransplant Senior Program (ESP) which mandates the allocation of deceased donor kidneys aged ≥ 65 years to candidates aged ≥ 65 years, and the U.S. which allows transplantation of the same kidneys to any aged candidates. In addition, Chapter 7 further describes the allocation inefficiencies and outcomes for younger candidates in the U.S. who received transplantation from donor kidneys aged ≥ 65 years. The research findings show that ECD kidneys in ESP had similar graft survival to ECD kidneys in the U.S. These findings suggest that international collaboration may be very useful in understanding the key determinants of adverse outcomes after ECD transplantation in elderly patients.    166  The area between the curves was used in this chapter as a new method of describing the efficiencies and inefficiencies of allocating ECD kidneys to different aged candidates. This metric supports the use of ECD kidneys in older U.S. candidates, as ECD kidneys will provide a lifetime of graft survival for these patients. The reduction in survival associated with ECD transplantation relative to standard criteria donor transplantation in older candidates is 7-8 months, and this information can be used to help candidates decide whether to accept ECD transplantation. In contrast, ECD kidneys do not provide a lifetime of graft function to younger U.S. candidates. After ECD kidney failure, these young candidates return to dialysis, are now more highly sensitized (i.e. less likely to match to another donor kidney) and their likelihood of being wait-listed for repeat transplantation is restricted.   The results from this chapter challenge the practice of allowing ECD kidneys to be transplanted into younger candidates. In addition, some of the benefit of ECD kidney transplantation relative to standard criteria donor kidney transplantation, is a result of the expected reduced waiting time for these kidneys. Permitting the allocation of ECD kidneys in young candidates (with no obvious benefit to the alternate strategy of waiting for standard criteria donor kidney transplantation) will simultaneously deplete the supply of ECD kidneys available for transplantation in older candidates, and increase the waiting time for transplantation with these kidneys for all candidates. In addition, Chapter 7 provides robust evidence to encourage increased utilization and decreased discard of kidneys from deceased donors ≥ 65 years in elderly transplant candidates.    167  9.2.4 Multiple wait-listing  The ability for a transplant candidate to be wait-listed at more than one transplant centre exists in the U.S. but not in Canada. U.S. patients who are multiply wait-listed have an increased likelihood of transplantation. There is regional disparity in access to kidney transplantation across the provinces43; the implementation of a similar wait-listing policy in Canada may be a strategy to help reduce these geographic inequities. In Chapter 8, we examined the use and outcomes of multiple wait-listing for kidney transplantation in the U.S. over time. We found that the likelihood of multiple wait-listing increased over time. The practice of multiple listing at one additional centre was more frequent among socioeconomically and demographically advantaged populations, as well as in regions with poorer access to transplantation. Candidates who were listed at more than one additional centre were even more selected, especially by White race and increased education. Multiple wait-listing increased the relative hazard of transplantation by 37%; moreover, the transplantation advantage with multiple listing was highest in candidates listed at more than one additional centre, increased over time, and was evident across subgroups. Given the growing waiting lists and increased time to transplantation, ensuring that difficult to transplant patients have equitable access to transplantation is an important goal and multiple listing may be one strategy towards reducing geographic disparity. 9.3 Strengths and limitations The thesis analyses are based on national registry data. As such, these databases are inclusive, and study results may be generalizable at the patient level within the country of  168  origin. However, because transplant centres within Canada and the U.S. operate independently, the interpretation of analyses from the policy perspective may differ substantially between provinces and states. As such, until further validation has occurred, the study method may serve as a good comparator within provinces over time, but may not be ready for within region comparisons. For example, there is variation in the number and characteristics (i.e. age) of deceased donor kidneys available for transplantation and the number and age of candidates awaiting transplantation across province. In a small province like Manitoba, strictly following the age allocation guidelines we have put forth, may result in unintended inequity in access to transplantation by age, whereas in a larger province such as Ontario, donor and candidate age distributions may be more similar to the national means and as such the recommendations may be able to be follow more closely with more minimal impact on equity.     All Canadian analyses are limited by the inability to access data from Quebec. Thirty percent of deceased donor kidney transplantation occurs in this province alone. We are currently working to access the CORR data for Quebec patients, but this request has been ongoing since 2012. Although there is slow progress towards data access, the outlook for obtaining this data is uncertain, and this is a major concern for all future CORR registry analyses.   Sample sizes for donor and recipient age combinations in CORR restricted the refinement of age groups for calculating donor kidney and recipient survival, as well as areas between survival curves. In addition, this limitation made it impossible to examine the  169  difference between survival curves within comorbidity strata. For example, we know that diabetes is a strong predictor of patient mortality. As such, the age cut-points for maximal efficiency allocation may differ for patients with diabetes as a cause of ESRD compared to another cause, because the area under a diabetic survival curve for the same aged recipient will be less. The ability to include additional variables such as cause of ESRD into calculations of survival curves may help to tailor allocation strategies in the future.   One major strength of the age matching recommendations for allocation put forth in this thesis is the balanced focus between utility and justice. In contrast to other life expectancy matching proposals which evaluate the impact of utility based allocation improvements on equity post hoc, the approach for developing age matching cut-points in this thesis is novel because it aims to increase allocation utility while not changing who gets transplanted.  9.4 Study implications and future work  The use of an improved measure for deceased donation activity will help inform strategies to increase deceased donation both regionally and nationally. We are currently involved in validating the Chapter 2 study method to identify potential deceased donors in the DAD with the help of the Canadian Institute of Health Information and British Columbia Transplant in British Columbia. This is a first step towards developing a national standard for measuring deceased donation. Importantly, validation of the study method of identifying potential deceased donors needs to be validated in all regions across Canada, and also within population subsets (e.g. by age), to determine systematic  170  over- or under- identification of potential donors. For example, the study method more closely approximated the number of potential donors identified using chart audits in younger patients. Determining if this difference is due to ICD coding errors or omissions for older patient deaths (that might rule out patients as potential donors), is a next step that needs to be examined. Finally, once this study method has been validated, it can be reliably used to determine the reasons that potential deceased donors are not being converted to actual organ donors (e.g. lack of patient consent, lack of patient referral). The reasons for non-conversion of potential donors may differ across Canada, and the Chapter 2 study method can be used to learn from provinces that are performing well in different areas. The cost savings are close to $50 000 per year for transplantation relative to dialysis. Therefore, each additional potential deceased donor who is converted to an actual donor will reduce health system costs, and improve the length and quality of survival for transplant candidates.  Given the growing size of the candidate wait-list, the cost implications of extending survival with graft function via improvements in allocation efficiency are significant. The use of age matching in deceased donor kidney allocation is transparent and easy for health practitioners and patients to understand. Despite overall reductions in organ waste and return to dialysis among transplant recipients, it is not clear if the possibility of a small amount of decreased survival in the oldest patients that may result from transplantation with an ECD kidney will deter patients from buying into such a strategy. In many countries (e.g. Canada), patients do not have a choice about which kidneys they are offered. In contrast, in the U.S. patient choice is of ultimate importance and surveys  171  are needed to determine patient attitudes about restricting the choice of which kidneys older patients are able to receive.   In addition, any change in allocation will naturally result in a difference in individual patient likelihood of access to transplantation (including difference in time on the waiting list). Some patients will receive transplantation more rapidly while others will receive transplantation less rapidly. In younger candidates, less rapid transplantation may be acceptable if access to a higher quality kidney will provide the patient with a survival benefit. In older candidates, more rapid transplantation of lower quality donor kidneys may improve outcomes relative to slower transplantation with a healthier kidney, but less rapid transplantation with a lower quality kidney may introduce harm. Two study areas evolve from this issue. First, it is important to understand the impact of small increases in dialysis waiting time on outcomes in different candidate age groups. For example, an increase of one year in dialysis waiting time may have no negative impact on outcomes for a young candidate, but may be detrimental in an older candidate with a higher likelihood of death on the waiting list. Second, patient attitudes about increased dialysis waiting times need to be assessed through survey. Determining increased waiting time thresholds that are acceptable from an outcomes perspective, as well as to patients, will inform the need to modify age matching allocation in the future. Age matching based on the recommendations in this thesis has already been implemented across Canada. These policy changes need to be evaluated in each region, to determine whether equity in access to transplantation was maintained, and in the future to determine any impact on long term outcomes. Deceased donor kidney allocation using age- 172  matching as presented in this thesis relies on the distribution of donor kidney and candidate ages. Therefore, it is imperative to develop regional strategies to monitor these age distributions over time, and implement changes to age-matching allocation if warranted.  In Canada and Eurotransplant, ECD kidneys are no longer transplanted into young candidates. Despite case-mix differences in the U.S., Chapter 7 provides evidence that supports these practices. Although, the U.S. system advocates for patient choice, the continued practice of ECD kidney transplantation into younger candidates may prove to be a disservice to both: 1) young candidates who will receive fewer years of graft function and be less likely to access repeat transplantation, and 2) older candidates who already have reduced access to transplantation as a result of the new top 20% to top 20% allocation, and will have increased time to ECD transplantation as the pool of donor kidneys goes to younger candidates. These differences point to the need for international sharing of allocation practices and successes.  Geographic disparities in access to transplantation are ubiquitous across North America. In the U.S. strategies are needed to ensure that all hard to match transplant candidates have access to policy that may decrease their inequity in access to transplantation. A new national registry for Canadian highly sensitized patients is evolving. This practice is meant to improve access for these hard to match patients. However, there is also large geographic variation in the time to transplantation for easy to match patients across the country. Further study is needed to determine the barriers to introduce more regional  173  based strategies for deceased donor transplantation. Although it may not be feasible to transplant a Vancouver patient in Halifax, a Vancouver to Calgary transplantation may be more reasonable. Non-renal deceased donor organs in Canada are shared nationally, and the increasing geographic disparity in time to transplantation suggests the need to revisit the regional allocation boundaries for deceased donor kidneys.  9.5 Conclusion The number of candidates waiting for deceased donor transplantation is increasing rapidly. Strategies to secure more deceased organ donors, and allocate them for the greatest benefit of all are needed. The ability to accurately estimate the number of potential deceased donors, and identify reasons for non-donation are important steps to increase deceased donation. Once a deceased donor is secured for transplantation, the appropriate use (allocation) of their organs is important. Efforts are required that not only use the existing donor pool more efficiently, but also ensure that the available deceased donor kidneys are equitably accessible to all patients who would benefit. The implementation of age-matching allocation policies may decrease organ wastage and inform strategies to safely expand the use of older deceased donor kidneys and therefore reduce discard of these organs. Age matching is a first step to increasing utility in deceased donor kidney transplantation, and may be possible nationally without reducing equitable access to transplantation.  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Canadian Organ Replacement Register Annual Report: Treatment of End-Stage Organ Failure in Canada, 2003-2012. Canadian Institute of Health Information: Ottawa, ON, 2014.  58. Redelmeier DA, Markel F, Scales DC. Organ donation after death in Ontario: a population-based cohort study. CMAJ 2013; 185: E337-344.  59. Kramer AH, Zygun DA, Doig CJ, et al. Incidence of neurologic death among patients with brain injury: a cohort study in a Canadian health region. CMAJ 2013; 185: E838-845.  60. Scientific Regsitry of Transplant Recipients (SRTR). OPTN / SRTR 2011 Annual Data Report. Rockville, MD: Department of Health and Human Services, Health Resources and Services Administration, Healthcare Systems Bureau, Division of Transplantation, 2012.  61. Johnson RJ, Bradbury LL, Martin K, et al. Organ donation and transplantation in the UK-the last decade: a report from the UK national transplant registry. Transplantation 2014; 97 Suppl 1: S1-S27.   180  62. Zaltzman J (ed). Donation after circulatory death in Canada. Canadian Society of Transplantation Annual Meeting, Lake Louise, March 2013.  63. Freeman RB. Mortality risk, behavior, and pediatric liver allocation. Liver Transpl 2006; 12: 12-15.  64. Code of federal regulations. Organ Procurement and Transplantation Network. 42 (vol I), edited by Administration US National Archives and Records Administration, 1999  65. Culyer AJ, Wagstaff A. Equity and equality in health and health care. J Health Econ 1993; 12: 431-457.  66. Childress JF. Ethics and the allocation of organs for transplantation. Kennedy Inst Ethics J 1996; 6: 397-401.  67. Alexander S: They Decide Who Lives Who Dies. In Life (vol 53), 1962, pp 102-125  68. de Fijter JW. Kidney allocation: where utility and fairness meet. Nephrol Dial Transplant 2010; 25: 1746-1749.  69. Port FK, Bragg-Gresham JL, Metzger RA, et al. Donor characteristics associated with reduced graft survival: an approach to expanding the pool of kidney donors. Transplantation 2002; 74: 1281-1286.  70. Keith DS, Demattos A, Golconda M, et al. Effect of donor recipient age match on survival after first deceased donor renal transplantation. J Am Soc Nephrol 2004; 15: 1086-1091.  71. Plantinga LC, Fink NE, Bass EB, et al. Preferences for current health and their association with outcomes in patients with kidney disease. Med Care 2007; 45: 230-237.  72. Parfit D. Reasons and Persons. Clarendon Press: Oxford, 1984.  73. WHOQOL G. WHOQOL Measuring Quality of Life. Geneva, 1997.  74. Tonelli M, Wiebe N, Knoll G, et al. Systematic review: kidney transplantation compared with dialysis in clinically relevant outcomes. Am J Transplant 2011; 11: 2093-2109.  75. Cecka JM, Terasaki PI. Optimal use for older donor kidneys: older recipients. Transplant Proc 1995; 27: 801-802.   181  76. Frei U, Noeldeke J, Machold-Fabrizii V, et al. Prospective age-matching in elderly kidney transplant recipients--a 5-year analysis of the Eurotransplant Senior Program. Am J Transplant 2008; 8: 50-57.  77. Richie RE, Niblack GD, Johnson HK, et al. Factors influencing the outcome of kidney transplants. Ann Surg 1983; 197: 672-677.  78. Takemoto S, Terasaki PI, Cecka JM, et al. Survival of nationally shared, HLA-matched kidney transplants from cadaveric donors. The UNOS Scientific Renal Transplant Registry. N Engl J Med 1992; 327: 834-839.  79. Canadian Organ Replacement Register CIfHI. 2012 CORR Annual Report: Treatment of End-Stage Organ Failure in Canada 2001-2010. CIHI: Toronto, 2012.  80. Candian Institute for Health Information. Canadian Organ Replacement Resgister: CORR E-quarterly statistics 2010. 2012.  81. Data acquisition report. www.unos.org.Accessed June 20, 2014.  82. Eurotransplant. Eurotransplant International Foundation 2014 www.eurotransplant.org. Accessed June 15, 2014.  83. Smits JM, Persijn GG, van Houwelingen HC, et al. Evaluation of the Eurotransplant Senior Program. The results of the first year. Am J Transplant 2002; 2: 664-670.  84. Mayer G, Persijn GG. Eurotransplant kidney allocation system (ETKAS): rationale and implementation. Nephrol Dial Transplant 2006; 21: 2-3.  85. Metzger RA, Delmonico FL, Feng S, et al. Expanded criteria donors for kidney transplantation. Am J Transplant 2003; 3: 114-125.  86. Rao PS, Ojo A. The alphabet soup of kidney transplantation: SCD, DCD, ECD--fundamentals for the practicing nephrologist. Clin J Am Soc Nephrol 2009; 4: 1827-1831.  87. Organ Procurement and Transplantation Network: http://optn.transplant. hrsa.gov/ContentDocuments/OPTN_Policies.pdf#nameddest=Policy_08. Accessed April 2, 2014.  88. Data acquisition report. www.unos.org. Accessed May 7, 2014.  89. United Network for Organ Sharing, Organ Procurement and Transplantation Network: Concepts for Kidney Allocation. February 2011. Accessed October 7, 2012  182   90. Freeman RB, Matas AT, Henry M, et al. Moving kidney allocation forward: the ASTS perspective. 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Am J Kidney Dis 2010; 55: 717-725.  122. Organ Procurement Organization. U.S. Department of Health and Human Services (2014) http://organdonor.gov/materialsresources/materials opolist.html. Accessed June 15, 2014.  123. Organización Nacional de Trasplantes. International Figures on Organ Donation and Transplantation-2007. Madrid, Spain, 2008. http://www.ont.es/publicaciones/Documents/Newsletter2008.pdf. Accessed June 20, 2014.  124. Canadian Institute of Health Information: Data Quality Study on Canadian Organ Replacement Register. In, Ottawa, On, 2009  125. Canadian Institute for Health Information: CIHI Data Quality Study of the 2009-2010 Discharge Abstract Database. Ottawa, ON, 2012     185  Appendices Appendix A. Canadian Organ Replacement Register- Data description The Canadian Organ Replacement Register (CORR) is a national information system for renal dialysis and solid organ transplantation.  A Canadian register of patients with renal failure has existed in some form since the early 1970s. In 1987, the register was expanded to collect data on other organs. In 1973, the chronic renal failure registry was transferred to Statistics Canada, and then transferred again in 1995 to the Canadian Institute for Health Information (CIHI), where it is currently housed.3 The register collects, processes, analyzes and reports the level of activity and outcomes of solid organ transplantation and renal dialysis activities 5. CORR obtains patient- level data through voluntary data submission from hospital dialysis programs, regional transplant programs, organ procurement organizations and independent providers of dialysis.  Coverage, reliability and validity Despite voluntary data submission, 99% of all solid organ transplantations performed in Canada are captured by CORR.57 This coverage was validated by comparing transplant recipients in CORR with transplant recipients in the Discharge Abstract Database (DAD).124 The DAD, which is also housed at CIHI, collects national, mandatorily submitted information on hospital discharges in Canada.125 Another validation study comparing CORR data from 2005-2006 with a chart review of a geographic- and size-representative probability sample of dialysis units was conducted using medical charts as the gold standard.124 Agreement between CORR and the medical charts was high for age and sex (>97%), moderate for cause of ESKD (71%) and poor for race (58%). Comorbidity data had high specificity but only moderate sensitivity, suggesting that positively recorded comorbid conditions are accurate, but underreported in CORR. There are currently no data on accuracy of organ donor factors or outcomes.     186  Appendix B. Diagnostic inclusion codes for eligible causes of death. Diagnosis Description ICD-10-CA Diagnostic Codes  Head Injury  Intracranial injury  S06.2, S06.3, S06.4, S06.5, S06.6, S06.8, S06.9, S02.001, S02.101, S02.701, S02.891   Cerebrovascular Accident (CVA)  Subarachnoid haemorrhage I60 Intracerebral haemorrhage I61 Other intracranial haemorrhage I62 Occlusion or stenosis of precerebral/ cerebral arteries I63, I65, I66 Stroke, not specified as haemorrhage or infarction I64   Other  Central nervous system tumours C70, C71, C72 Anoxic brain damage G93.1 Compression of brain G93.5 Cerebral oedema G93.6, S06.1 Ventricular tachycardia I47.2 Ventricular fibrillation and flutter I49.00, I49.01 Cardiac arrest I46.0,  I46.1, I46.9 Status asthmaticus J45.01, J45.11, J45.81, J45.91 Asphyxia R09.0 Respiratory arrest R09.2 Asphyxiation and strangulation T71     187  Appendix C. Diagnostic exclusion codes for contraindications to organ donation Diagnosis Description  ICD-10-CA Diagnostic Codes  Death, unknown cause R96, R98, R99 Nervousness, Malaise and fatigue R45.0, R53 Cachexia R64 Other specified general symptoms and signs R68.8 Unknown and unspecified causes of morbidity R69 Tuberculosis A15-A19, O98.0 Sepsis A40-A41, A03.9, A20.7, A21.7, A24.1, A26.7, A28.0, A28.2, A32.7, A42.7, B37.7, O03.0, O03.5, O04.0, O04.5, O05.0, O05.5 O07.3, O08.0, T80.2, T81.4, T88.0, T82.6, T82.7, T83.5, T83.6, T84.5-, T84.6-, T85.7, R65.0, R65.1, R65.9, A22.7, A02.1, O85 Brucellosis/ Listeriosis A23/ A32 Other infection during labour O75.3 Acute and chronic meningococcaemia A39.2, A39.3 Meningococcaemia, unspecified A39.4 Human immunodeficiency virus [HIV] B24, Z20.6, Z21, R75, O98.7 Cytomegaloviral disease B25 Acute poliomyelitis A80 Jakob-Creutzfeldt disease A81.0, F02.1 Normal-pressure hydrocephalus A81.1 Subacute sclerosing panencephalitis G91.2 Other rickettsioses A79 Progressive multifocal leukoencephalopathy A81.2 Disseminated herpesviral disease B00.7 Viral encephalitis G04.0, G04.8, A85, A88.8, A86, A89, B00.0-4, A83, A84, A85.2, G05.1, G05.2, G04.9 Hepatitis B16, B17, B18, B19, O98.3, O98.4-9 Rabies A82-A89 Malaria B50-B54 Active Syphilis A50-A53, O98.1 Gonococcal infections A54, O98.2 Other and unspecified mycoses B48, B49 Malignant neoplasms C00-C96 Haemolytic anemias Aplastic and other anemias D55-D59 D61, D62, D64 Meningitis (bacterial/viral) G00, G01, G02, G03, G05.2, B45.1, B83.2, A87 Alzheimer’s disease G30 Parkinson’s disease Motor neuron disease Multiple sclerosis G20 G12.2 G35 Active endocarditis I33.0, I33.9, I01.1, I52.0 Mixed connective tissue disease M32, M33, M34, M35 Certain conditions with origin in perinatal period P00-P96 Radiotherapy or chemotherapy session  Z51.0,  Z51.1 Hypopituitarism E23.0 Transplanted organ and tissue status Z94 Presence of heart valve Z95.2, Z95.3, Z95.4 Severe acute respiratory syndrome U04.90, U04.91 West Nile virus/ Lyme disease A92.3/ A69.2 Resistance to antibiotics U82, U83  

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