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HIV and aging : age-associated chronic comorbidities among HIV-positive individuals on highly active… Gali, Brent James 2016

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   HIV AND AGING: AGE-ASSOCIATED CHRONIC COMORBIDITIES AMONG HIV-POSITIVE INDIVIDUALS ON HIGHLY ACTIVE ANTIRETROVIRAL THERAPY IN BRITISH COLUMBIA, CANADA   by   Brent James Gali B.Sc. (Hons), University of Winnipeg, 2012   A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF   MASTER OF SCIENCE   in   THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Population and Public Health)   THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)   February 2016   © Brent James Gali, 2016  ii Abstract Background: Highly active antiretroviral therapy (HAART) has transformed HIV from a once fatal condition into a treatable chronic disease. As people with HIV are living longer than in the past, understanding the effects of aging with HIV is of increasing importance. This dissertation aims to explore trends of several chronic diseases during the current HAART era, while also taking into consideration the impact of expanded access to HAART in British Columbia, Canada from 2000-2012.  Methods: The studies presented in this dissertation are based on administrative data collected from the Comparative Outcomes and Health Service Utilization Trends (COAST) study. Various analytical methods were used to assess trends of chronic disease incidence of six common chronic diseases: cardiovascular disease (CVD), chronic obstructive pulmonary disease (COPD)/asthma, diabetes mellitus (DM), hypertension (HTN), chronic kidney disease (CKD) and chronic liver disease (CLD). Both studies were retrospective population-based cohort studies of HIV-positive individuals whom accessed HAART and identified as HIV-positive in the COAST study database by validated algorithms. Several measures were employed to determine risks and trends of chronic disease incidence.  Results: The results of each study showed that trends and risks of chronic disease incidence were not all consistent. In the first study exploring trends of chronic diseases among 10,210 HIV-positive individuals whom had accessed HAART the adjusted incidence rate for HTN increased over time; CKD and CLD decreased over time; and no trend was observed for CVD, COPD/Asthma and DM. In the second study, among 4,840 HIV-positive individuals who initiated HAART during this period, the relative risk of CLD incidence was reduced in the post- (2006-2012) versus pre- (2000-2005) HAART expansion periods. The relative risk for CVD, DM, HTN, COPD/asthma and CKD were not statistically significant in the post expansion period.  Conclusions: Results from this dissertation provide insight on trends and risks of several comorbidities during the current HAART era. Specifically, the results of this dissertation highlight the trend towards increasing incidence of HTN and decreasing incidence of CLD among HIV-positive aging populations. Understanding how chronic comorbidities affect future disability and death among people aging with HIV is an important area of further research. iii Preface  This dissertation was based on data provided by the Comparative Outcomes and Health Service Utilization Trends (COAST) study based at the British Columbia-Centre for Excellence in HIV/AIDS (BC-CFE), led by principal investigator Dr. Robert S. Hogg (RH). All data from this study were prepared for data analysis by BC-CFE staff. This study has ethics approval from the University of British Columbia-Providence Health Care Human Research Ethics Board ((Ethics Certificate Number: H09-02905). With support from supervisors: Drs. David Moore (DM) and Kimberlyn McGrail (KM); committee member: Dr. Viviane Lima (VL); and co-authors of study manuscripts: RH, Oghenowede Eyawo (OE), Shahab Jabbari (SJ), Huiting Ma (HM), Wendy Zhang (WZ), William Chau (WC) and Hasina Samji (HS) all of the work presented in this dissertation was prepared and written by the candidate, Brent Gali (BG).   Chapters 1, 2 and 5 are unpublished original works by the author, BG. With the guidance and assistance from supervisors DM and KM; and committee member VL, BG independently conducted the literature review, conceptualized the study design and synthesized study results.  A version of Chapter 3 was presented in poster form at the 8th International AIDS Society Conference on HIV Pathogenesis, Treatment and Prevention. July 19-22, 2015. Vancouver, Canada. Additionally, a version of Chapter 3 was presented in oral form at the 6th International Meeting on HIV and Aging. October 5-6, 2015. Washington, D.C., USA. Currently, a version of the manuscript is being reviewed by co-authors OE, SJ, WC, WZ, HS, RH, VL, KM and DM, and will be submitted for future publication.  A version of Chapter 4 is currently being reviewed by co-authors OE, SJ, HM, RH, VL, KM and DM, and will be submitted for future publication.  All inferences, opinions, and conclusions drawn in this dissertation are those of the authors, and do not reflect the opinions or policies of the Population Data BC data stewards.   iv Table of contents Abstract .............................................................................................................................. ii Preface ............................................................................................................................... iii Table of contents .............................................................................................................. iv List of tables ...................................................................................................................... vi List of figures ................................................................................................................... vii List of abbreviations ...................................................................................................... viii Acknowledgements .......................................................................................................... ix Dedication .......................................................................................................................... x Chapter 1: Introduction ................................................................................................... 1 Overview ..................................................................................................................................... 1 Study justification ...................................................................................................................... 1 Study setting ................................................................................................................................ 2 Study objectives and hypotheses ............................................................................................... 3 Summary ..................................................................................................................................... 4 Chapter 2: Literature review ........................................................................................... 6 Overview ..................................................................................................................................... 6 History of HIV and HAART ..................................................................................................... 7 Epidemiology of HIV in Canada ............................................................................................... 9 Benefits of early HAART ......................................................................................................... 10 Aging and HIV .......................................................................................................................... 12 Diabetes mellitus and HIV ....................................................................................................... 14 Hypertension and HIV ............................................................................................................. 15 Cardiovascular disease and HIV ............................................................................................ 17 COPD/asthma and HIV ........................................................................................................... 18 Chronic kidney disease and HIV ............................................................................................ 20 Chronic liver disease and HIV ................................................................................................ 21 Future directions ...................................................................................................................... 23 Chapter 3: Trends of chronic comorbidities among HIV-positive individuals receiving HAART in BC from 2000-2012 ..................................................................... 24 Introduction .............................................................................................................................. 24 Methods ..................................................................................................................................... 26 Data Sources .......................................................................................................................... 26 Study Design .......................................................................................................................... 27 Study Variables ...................................................................................................................... 27 Statistical Analysis ................................................................................................................. 29 Results ....................................................................................................................................... 29 Discussion .................................................................................................................................. 33 Chapter 4: Impact of expanded access to HAART on chronic comorbidities among HIV-positive individuals initiating HAART in BC ...................................................... 44 Introduction .............................................................................................................................. 44 Methods ..................................................................................................................................... 47 Data Sources .......................................................................................................................... 47  v Study Design .......................................................................................................................... 48 Study Variables ...................................................................................................................... 49 Statistical Analysis ................................................................................................................. 50 Results ....................................................................................................................................... 52 Discussion .................................................................................................................................. 54 Chapter 5: Conclusion .................................................................................................... 65 Summary of findings ................................................................................................................ 65 Study strengths ......................................................................................................................... 68 Study limitations ....................................................................................................................... 70 Recommendations .................................................................................................................... 71 Future research ........................................................................................................................ 73 References ........................................................................................................................ 76 Appendix .......................................................................................................................... 93   vi List of tables  Table 3.1: Baseline cohort characteristics (n=10,210) ...................................................... 38	Table 3.2: Unadjusted and adjusted incidence rates (per 1000 person year) of six chronic diseases from 2000-2012 and associated p-value for Poisson regression test of trend ................................................................................................................................... 41	Table 4.1. Baseline cohort characteristics and investigation of relationship between chronic disease incidence and HAART initiation expansion  (n=4,840) .................. 60	Table 4.2. Unadjusted RR for disease incidence and various covariates with associated 95% CI, RR (95% CI) ............................................................................................... 61	Table 4.3: Relative Risks for chronic disease incidence of individuals initiating treatment after HAART expansion relative to before HAART expansion with associated 95% CI (adjusted by covariates: age, sex, first regimen drug class, baseline weighted CCI, log-10 pVL and CD4 cell count) .............................................................................. 62	Table 4.4: Adjusted risk rates of chronic disease incidence of all individuals actively on HAART during each time period with associated 95% CI and p-values (adjusted by covariates: age, sex, first regimen drug class, baseline weighted CCI, log-10 pVL and CD4 cell count) .................................................................................................. 63	   vii List of figures  Figure 3.1. Summary of sample size changes based on exclusion and inclusion criteria . 39	Figure 3.2. Baseline prevalence of six chronic diseases among HIV-positive BC residents on HAART (n=10,210) ............................................................................................. 40	Figure 3.3. Adjusted incidence rates (per 1000 person year) over time (adjusted by age, sex, baseline weighted CCI, CD4 and log-10 pVL) ................................................. 42	Figure 3.4. Age stratified adjusted incidence rates (per 1000 person year) over time (adjusted by sex, baseline weighted CCI, CD4 and log-10 pVL for six chronic diseases ..................................................................................................................... 43	Figure 4.1. Adjusted incidence rates (per 1000 person year) of each chronic disease from 2000-2012 before and after the specified HAART expansion period (adjusted by covariates: age, sex, first regimen drug class, baseline weighted CCI, log-10 pVL and CD4 cell count) .................................................................................................. 64	 viii List of abbreviations  3TC Lamivudine AIDS Acquired immunodeficiency syndrome ARV Antiretroviral AZT Zidovudine BC British Columbia BC-CFE British Columbia-Centre for Excellence in HIV/AIDS  BMI Body mass index CCI Charlson Comorbidity Index CD4 Cluster of differentiation 4 CDC Centre for Disease Control and Prevention CI Confidence interval CKD Chronic kidney disease CLD Chronic liver disease COAST Comparative Outcomes and Health Service Utilization Trends COPD Chronic obstructive pulmonary disease CVD Cardiovascular disease ESLD End-stage liver disease ESRD End-stage renal disease DAD Discharge abstract database DM Diabetes mellitus DTP Drug Treatment Program FDA Food and Drug Administration HAART Highly active antiretroviral therapy HBV Hepatitis B virus HCV Hepatitis C virus HIV Human immunodeficiency virus HTN Hypertension ICD-10 International Classification of Diseases, 10th Revision ICD-9 International Classification of Diseases, 9th Revision IQR Interquartile range MSM Men who have sex with men MSP Medical Service Plan NNRTI Non-nucleoside reverse-transcriptase inhibitor PI Protease inhibitor PLWH People living with HIV pVL Plasma viral load PWID People who inject drugs RR Relative risk START Strategic Timing of Antiretroviral Treatment TasP Treatment as Prevention TEN Tenofovir VA Veterans Aging  ix Acknowledgements  I would like to start by thanking my supervisors Drs. David Moore and Kim McGrail and thesis committee member, Dr. Viviane Lima. Thank you for your guidance, patience, support and for allowing me to absorb as much knowledge from you as I could during my graduate training. I am extremely grateful to be considered one of your students, and enjoyed getting to know each of you along the way. You have all contributed to shaping my research interests moving forward, and I am happy to have had such amazing mentors.  I would also like to thank the many of friendly staff at the BC-CFE for your endless support in helping me develop my research ideas by providing me with your expertise and knowledge in research methods, data preparation and statistical analysis. Specifically, I would like to thank Wendy, Shahab, Huiting, Guillaume, Ede and Bob for guiding me throughout this process and working tirelessly to help me make this thesis possible.   Over these past few years, I have met some amazing, bright and friendly people in the UBC-School of Population and Public Health program. I feel honored to be a part of such a great group of driven and enthusiastic people. I want to thank all my professors and colleagues that I have had the opportunity to get to know over these past few years. I have learned much more from these people than I would have ever anticipated. Specifically, I want to thank Beth Hensler for her endless support for all of us graduate students. Thank you Beth for making the administrative side of things so much easier for us.  I want to thank my family and friends for all their support during my time completing this thesis. To my parents, Bhoy and Cora; brother, Brenden and sister, Chelsie, you may have all been in another city, but I appreciate all that you’ve done for me to get me to where I am now. Lastly, I want to thank my partner though this all, Chantel. Thank you for putting up with my last-minute edit requests, and unconditional support. I could not have done this without you.  Data and research support for the COAST research project was provided by Population Data BC and the Canadian Observational Cohort Collaboration. Funding support for the COAST research project was provided by the Canadian Institutes for Health Research and support for this dissertation was provided by the Canadian Agency for Drugs and Technologies in Health (CADTH).  x Dedication To my parents, Bhoy and Cora Gali.  1 Chapter 1: Introduction Overview Highly Active Anti-retroviral Therapy, or HAART, has transformed HIV from a uniformly fatal condition into a largely treatable chronic disease and has allowed individuals to survive much longer relative to previous decades (1). Much of this reduced mortality is a result of decreased incidence of AIDS-defining illnesses and other conditions directly associated with HIV (2-4). As these conditions become less common, other chronic diseases more commonly related to aging, such as cardiovascular disease (CVD), diabetes mellitus (DM), hypertension (HTN), chronic obstructive pulmonary disease (COPD)/asthma, chronic kidney disease (CKD) and chronic liver disease (CLD), are becoming a greater threat to HIV-positive individuals (5-10). Clinical guidelines for the use of HAART now recommend treatment in earlier stages of HIV infection, resulting in expanded access to treatment (11, 12). In this current era of HAART, people are no longer just living with HIV—people are now aging with HIV (13-15). This dissertation aims to examine how HAART access expansion in British Columbia (BC), Canada, has affected the incidence trends of chronic comorbidities over a thirteen-year period.  Study justification Aging with HIV is an emerging field of research that until recently was never considered a priority. To date, many studies that have evaluated the effects of aging on PLWH have been clinical trials (6, 7). Many of these trials also involve recruitment methods and study design parameters that limit the generalizability of the results to   2 constrained populations or groups.  There have been few, if any studies, regarding risks and trends of chronic diseases among HIV-positive people in population-based cohorts. While there are a few cross-sectional studies that evaluate chronic disease prevalence among HIV-positive individuals in population-based studies, information regarding longitudinal population-based estimates are not readily available (16). The studies presented in this dissertation are unique because they evaluate longitudinal data of chronic disease incidence in a population-based cohort study design that fills a gap in the existing literature regarding chronic disease incidence among HIV-positive populations during the current era of expanded HIV treatment.  Study setting The studies presented in this dissertation are based on population-based data representing all HIV-positive patients during the current era of expanded HAART access in British Columbia, Canada. Data used in these studies were obtained from the COAST study database, and the data within COAST are from two major sources: BC-CFE DTP and Population Data BC. The BC-CFE DTP registry includes data on demographics, ARV use, as well as AIDS-defining, immunologic and virologic outcomes for all HIV-positive individuals receiving ART in BC. Population Data BC provides access to longitudinal health care services databases including Medical Service Plan (MSP) and Discharge Abstract Database (DAD), containing physician and hospital records for all BC residents.    3 The studies presented herein explore trends of chronic diseases from years 2000 to 2012. During the study period, a policy shift occurred with respect to BC’s guidelines for the use of ART, which resulted in increased access to HAART as recommendations for earlier treatment were implemented. Therefore, the study examined  two somewhat distinct time periods—the pre-HAART expansion period occurred before the shift in HAART policy (2000-2005) and the post-HAART expansion period, which occurred after the shift in HAART policy (2006-2012).   Study objectives and hypotheses This dissertation aims to explore trends and risks of six chronic diseases over a thirteen-year study period during the current HAART era. Specifically, the research objectives and associated hypotheses of each study are listed below:  1. To measure trends of chronic disease incidence by comparing incidence rates of six common chronic comorbidities (CVD, COPD/Asthma, DM, HTN, CKD and CLD) in HIV-positive individuals receiving HAART over the study period of  2000-2013. Chapter 3 will evaluate administrative data in the COAST database to assess thirteen years of follow up on individuals who initiated HAART during 2000-2013. Covariates will also be captured and adjusted to account for confounding in determining significance of trend. Given that HAART has resulted in increased life expectancy in PLWH who are now an aging population (17, 18), it is hypothesized that the study population will have increased incidence rate trends for all six chronic diseases over time.   4 2. To determine the impact of expanded HAART access by comparing risk of six common chronic comorbidities (CVD, COPD/Asthma, DM, HTN, CKD and CLD) in HIV-positive individuals during the pre-HAART expansion period (2000-2005) to the post-HAART expansion period (2006 – 2012). Chapter 4 will determine the impact of HAART access expansion by measuring the relative risk of individuals who initiate HAART in the post-HAART expansion period compared to the pre-HAART expansion period. In addition, this Chapter will assess differences between the two distinct time using Poisson regression models to compare risk rates of chronic disease incidence in each respective time period. Evidence regarding HAART suggests earlier HAART is beneficial in improving the health of PLWH(4, 19-21), so it is hypothesized that HIV-positive individuals in the post- HAART expansion period will have reduced risk for all six non-HIV chronic comorbidities relative to HIV-positive individuals in the pre-HAART expansion period.  Summary In summary, this dissertation is comprised of five chapters. This current chapter is meant to provide an overview of the research questions and study objectives regarding trends of chronic diseases and expansion of HAART access among HIV-positive individuals in BC, Canada. Chapter 2 presents a review of the current literature regarding the role of HAART in contributing to HIV and aging. This literature review will describe the history and evolution of HIV and HAART, and discuss current implications for PLWH. Chapters 3 and 4 describe empirical studies that evaluate the research objectives   5 of this dissertation. Chapter 3 explores trends of incidence rates for various chronic diseases from 2000-2012—a period of time during which HAART access expansion occurred. Chapter 4 continues from Chapter 3 by specifically highlighting the impact of HAART expansion, comparing individuals who initiated HAART in the post-HAART expansion period to individuals who started HAART in the pre-HAART expansion period. Together, these studies speak to the recent trends and risks of chronic diseases in an aging HIV population. Chapter 5 synthesizes the information from both studies to highlight key findings and offer recommendations for knowledge translation.     6 Chapter 2: Literature review  Overview	HIV is characterized by a viral infection transferred by blood or bodily fluids (22). Once infected, HIV affects the host’s immune system, ultimately resulting in a decrease in CD4 T cells. In untreated infected individuals this activity continues until eventual death. During this process, once CD4 cells drop below a certain point, opportunistic co-infections are enhanced—a condition referred to as AIDS. Treatment for HIV/AIDS was first called ARV (antiretroviral) therapy and included an NRTI, the first class of ARVs discovered. When given as a single drug it slowed replication of the HIV-infection, but ultimately only had limited effectiveness (23). It was not until triple combination ART—which became later known as HAART—was introduced that HIV/AIDS could be effectively treated. Initially, HAART involved a combination of nucleoside reverse transcriptase inhibitors (NRTI), non-nucleoside reverse transcriptase inhibitors (NNRTI) and protease inhibitors (PI) (most commonly two NRTIs and one of the other drug classes) to effectively manage and halt viral replication (22, 24).  Today, HAART regimens may contain components from several novel drug classes, beyond the three mentioned here.  HIV was once considered a uniformly fatal diagnosis, but over the past three decades, that notion has been modified (19). The evolution and advancement of HIV treatment and delivery has made living with HIV the norm, rather than a possibility. In   7 the current HAART era, people are now aging well with HIV (25). Looking ahead, the future for those with HIV is optimistic, and understanding and identifying the potential risks associated with aging among HIV-positive individuals will only strengthen those affected by this condition. This review will review the history and characteristics of HIV and aging, and HAART’s role in bridging these two themes together.  History	of	HIV	and	HAART	The beginning of the recognition of HIV/AIDS epidemic was in 1981—with the first ever diagnosis of AIDS in the United States (26). Though it was later evident that AIDS related deaths occurred prior to this date, this marked the first formal recognition of  what became many millions of HIV/AIDS-related cases. The epidemic—initially thought to be exclusively a result of men who have sex with men (MSM)—had a major toll on the global landscape, resulting in public controversy, high mortality rates, and scientific uncertainty about both causes and effective treatments (27). As the death toll rose towards the end of the 1980s, AZT—an NRTI and first available drug to treat HIV with any effectiveness —was approved by the U.S. FDA in 1987 (28). AZT functioned by reducing viral replication, and showed promise but was not very effective due to HIVs ability to rapidly develop resistance to the drug (23, 29).  The epidemic continued into the early 1990s, and AIDS became the leading cause of death for all Americans aged 25 to 44 by the mid 1990s (30).  At the same time, the 1990s marked an era of hope for the HIV/AIDS epidemic, when the U.S. FDA approved saquinavir—the first protease inhibitor, which proved more effective in reducing viral   8 replication than previous compounds (31). The approval of saquinavir marked the introduction to the HAART era for HIV treatment by introducing combination ART, involving a minimum of three active drugs (32-35). In 1996, the 11th International AIDS Society conference (“One World, One Hope”) in Vancouver, British Columbia, Canada, revealed the effectiveness of HAART on reducing HIV/AIDS morbidity and mortality (36, 37). Towards the end of the 1990s, success from HAART resulted in a 40% decline in AIDS-related deaths in several regions around the world, including BC (38-42). The transition of HAART into clinical practice continued to prove substantial benefit in the early 2000s—with reductions of AIDS-related deaths and hospitalizations by 60% to 80% (4, 38, 39). At the same time, reports of complications from HAART begin to surface, and more investment into research and development for additional safe and effective drugs continued (43-49).   The introduction of HAART in 1996, marked a breakthrough in the HIV/AIDS epidemic by  transforming  a once fatal infection into a treatable chronic condition and proved that the epidemic could be treated (50). The start of the HAART era was based on results of the effectiveness of multi-drug combination therapies on halting viral replication and preventing the CD4 cell count decline (51). Over the years drug combinations have been refined to reduce the number of side effects, while maintaining their clinical efficacy (52, 53). Despite the apparent benefit of HAART a number of issues such as short and long term drug toxicities, adherence, costs and access in lower- to middle-income settings and stigma remained as challenges for HIV infected individuals (54).    9  Moving into the early 2000s, HAART continued to prove beneficial in high-income countries (55-57). As increased efforts and funds continued to focus on combating the global burden of HIV/AIDS, new research was emerging showing the effectiveness of initiating HAART at earlier stages of disease progression (21). These findings contributed to the “Treatment as Prevention” (TasP) strategy developed at the BC Centre For Excellence in HIV/AIDS and pioneered by Dr. Julio Montaner (11). The expansion of access to HAART since 2006 resulted in further reductions in HIV/AIDS complications and death in BC (4). In 2010, the BC Ministry of Health formally adopted TasP as a strategy to further reduce HIV-related mortality and morbidity and to reduce HIV transmission. This approach has now been adopted in many different regions around the world (58).   Epidemiology	of	HIV	in	Canada	In the latest estimate, approximately 35 million people are living with HIV worldwide. Approximately two million of these cases are based on North American estimates (56), with almost five percent from Canada (55).   In Canada, among the 75,500 prevalent (based on estimates from 2014) individuals who have been diagnosed with HIV, the main HIV transmission risk groups are: men who have sex with men (50%) and people who inject drugs (PWID) (20%) (59). Approximately 21% of all PLWH in Canada are believed to not know their HIV status (59). In 2014, the prevalence of HIV was reported to be 212 per 100,000 people, with   10 regional variation and BC having the highest prevalence of 265.9 per 100,000 people (36). In this same year, incidence of HIV in Canada was 7.2 per 100,000 people and also varied by different regions and groups—where new cases of HIV-MSM were highest in BC, Ontario, Quebec and the Atlantic provinces; new cases of HIV-PWID were highest in Saskatchewan; and new cases of HIV in heterosexual sex were highest in Alberta and Manitoba (60).   Benefits	of	early	HAART	Widespread use of HAART continued to show effectiveness in treating HIV and AIDS, but for the past two decades there has been ongoing debate about clinical practice, specifically about the most cost- and clinically-effective timing of HAART (20, 61-63). Initially, there was a belief that earlier use of HAART could result in early development of drug resistance, as well as exposing patients  to drug toxicities (48, 64). Over the past 10 years, evidence of benefits from early HAART initiation were being seen in many different populations around the world. Early HAART initiation was effective in facilitating the effects of reduced plasma viral load and decreased morbidity relative to individuals who initiate HAART later in the course of their disease (4, 21). Many of the arguments against early HAART have become less relevant, as drug regimens are simpler and the drugs themselves are much better tolerated with lower propensity for resistance.   In addition to the clinical benefits of early use of HAART, recent research has suggested that population level benefits may also occur . Viral suppression from HAART has been shown to dramatically reduce HIV transmission in at-risk populations (4). The   11 once contentious debate about whether to start HAART or delay HAART is now over-shadowed by new conversations about how to facilitate earlier HAART initiation (11). With early HAART being accepted as the optimal strategy in treating patients with HIV, understanding the reasons why patients may not start treatment earlier is an important area of research. A few reasons that have been explored in the literature include high costs of HAART, people being unaware of their HIV status, political and structural barriers to testing and treatment (54, 62).  Until recently, limited evidence from clinical trials has been a major barrier in determining when the optimal timing of starting HAART should be. Results from the recent START trial are the first to provide unequivocal evidence for the benefits of earlier HAART treatment (21). The START trial was a multi-site, randomized, global trial that evaluated the effectiveness of early HAART (started HAART regardless of CD4 cell count) versus deferred HAART (started HAART when CD4 cell count was below 350 cells/µL). A total of 4,685 individuals were followed longitudinally with 2,326 individuals starting HAART early starters and 2,359 deferring  HAART. When comparing serious AIDS and non-AIDS related outcomes, the hazard ratio for the primary end-point was 0.43 (95%CI: 0.30, 0.62), and occurred in 42 individuals in the early HAART group compared to 96 individuals in the deferred HAART group. The results of this  trial demonstrated  that earlier initiation of HAART was proven to be most beneficial in preventing both AIDS and non-AIDS related outcomes (21).    12 Access to HAART in Canada is largely made possible by a public and universally funded health care system. Since health care policy is under provincial jurisdiction, the mechanisms by which individuals may access HIV treatment vary from province to province. In BC, anyone with a HIV diagnosis regardless of their CD4 cell count is eligible for HAART, but this is not the case in all provinces. Most other regions do not have HIV therapeutic guidelines and therefore defer to the World Health Organization’s latest recommendations, which only recently recommended initiating HAART among all HIV-positive individuals regardless of CD4 cell count (65).  Aging	and	HIV	Early HAART is a proven and successful strategy in increasing life expectancy and reducing AIDS-related morbidity and mortality in PLWH (25, 66). The once fatal infection is now widely considered a treatable chronic disease (1). Depending on the availability and access to HAART, HIV-positive populations are now able to live longer and healthier than ever before (67, 68). Moving into the next era of treating the HIV/AIDS pandemic, attention is shifting towards understanding how HIV and HIV treatment affect individuals as they age (69). With many of the North American HIV-positive populations now aging, understanding how HIV-positive populations age is important in determining what types of vulnerabilities HIV-positive patients may experience(70-72).   Since HAART has only been in existence for the past two decades, the effects of aging on HIV-positive populations are only in infancy. Almost one-fifth of the North American population is 50 years of age or older, and the population living with HIV is   13 aging as well (25). Within the next five to ten years, the proportion of older HIV patients is expected to comprise half of the entire HIV population. This makes it a pivotal time for understanding the trajectory for aging HIV positive populations as it related to chronic disease management and accelerated aging (14, 17, 73).   There are many factors that are considered to play a role in the HIV-aging relationship that differentiate this group from the standard experience of aging. For example, this population has exposure to toxic drugs from the late 1990s (74), exposure to other harmful substances (e.g. illicit drugs, smoking, alcohol, etc.) (75, 76), compromised immune systems from the HIV infection (70, 77, 78) and interactions between HIV treatment drugs and drugs from comorbidities unrelated to AIDS (69). Understanding how all of these factors interact with one another can help determine what direction policy makers and health professionals need to take to continue to support HIV/AIDS-affected individuals as they progress forward with the disease (78).  Many of the issues currently explored in the literature involve understanding the relationship between HIV and various comorbidities typically related to aging such as diabetes mellitus, hypertension, cardiovascular disease, chronic obstructive pulmonary disease, asthma, chronic kidney disease, and chronic liver disease (1, 45, 74, 79-88). Many of these conditions become more common as people age in the general population, and recent evidence suggests that the risks of these diseases are even greater in the HIV positive population (13, 89, 90). There are many overlapping risk factors for these chronic diseases and HIV, but one key risk factor that is involved in all the comorbidities   14 is cigarette smoking—an estimated 40-70% of all HIV-positive individuals are smokers (91).   Since aging with HIV is a relatively recent phenomenon, the effects of aging in this population have only recently begun to be studied and our  understanding of it is incomplete (71). The importance of identifying key areas for early prevention of other chronic diseases in HIV populations will allow changes to be made at a stage while the majority of the current HIV-positive population is still relatively early in their experience of aging. Before recommendations about what can be done to reduce the burden of comorbidities among aging PLWH, it is necessary to have a full understanding of the trends and patterns of these comorbidities.  Diabetes	mellitus	and	HIV	Diabetes Mellitus (DM) is a disease characterized by elevated concentrations of blood glucose, which leads to serious health complications such as blood vessel disease, nerve damage, edema, blindness, obesity, and kidney disease (92). There are two types of DM: type 1 diabetes and type 2 diabetes. The most common form, and the form associated with ageing,  type 2 diabetes, is caused by the inability to use insulin effectively, an important hormone involved in glucose transport from plasma into cells for metabolism (92). Type 1 diabetes is caused by the inability to produce insulin at all (92). In 2014, there were an estimated 387 million people living with DM globally—where type 2 diabetes made up for approximately 90% of all cases (93).  In North America, there are an estimated 39 million cases of DM (93); and in Canada, DM is   15 considered one of the most common chronic diseases where that latest reports indicate approximately 2.4 million people were living with DM in 2008 (94).  In recent years PLWH are living longer and experiencing aging-related morbidity, which has resulted in an increased incidence of DM among this population (95-97). DM is caused by disruptions in glucose transport and metabolism, and certain medications in HAART (e.g. NRTIs: didanosine, stavudine and zidovudine; and PIs: indinavir and lopinavir/ritonavir) are known to interfere with these functions, resulting in increased risk of DM (97). In addition to these medications, HCV co-infection, smoking and certain minority ethnic groups are common risk factors related to both HIV and DM (45, 91). Due to the complexity of having both HIV and DM, individuals with both these diseases are at even greater risk for other chronic diseases such as HTN, CVD and CKD (97-99).   Hypertension	and	HIV	Hypertension (HTN) is a disease characterized by elevated arterial blood pressure and expressed by measures of systolic and diastolic pressures (100). Normal systolic blood pressure ranges from 100-140mmHg and normal diastolic pressure ranges from 60-90mmHg. Diagnosis of HTN is based on blood pressure measurements persistently exceeding 140/90mmHg (100). Patients with hypertension are at greater risk for other organ diseases such as coronary artery disease, stroke, aortic aneurysms, peripheral artery disease, DM and CKD (100). HTN is one of the most common chronic diseases for adults over the age of 25. An estimated one billion cases of HTN were reported in 2008, which is almost double the number of cases reported in 1980 (93). In the United States 77.9   16 million people were estimated to have HTN in 2013 (93); and in Canada, six million in 2007, or 25% of all adults (101).   For individuals with HIV, HTN is a comorbidity of increasing concern—in a Veterans Administration (VA) cohort, 45% of all HIV-positive individuals are reported to also be comorbid with HTN (102, 103). The VA cohort is a U.S. based observational prospective study with a group of both HIV positive and negative veterans—this cohort is commonly used as a reference HIV-positive cohort in North America (102).   The cause and effect relationship between HTN and HIV is not completely clear, though a major risk factor associated with both HTN and HIV is smoking (approximately 40 to 70 percent of HIV positive patients are also smokers) (91). The evidence that being on HAART is a risk factor for HTN is mixed, where earlier studies suggest that HAART does result in elevated blood pressures, and more recent studies suggesting that this relationship is mediated by age, ethnicity and BMI (84, 104). A recent study, using the Multicenter AIDS Cohort Study, found that prolonged duration of HAART (2-5 years) is an independent risk factor for HTN, when compared to individuals on HAART for less than two years (104). Fortunately, HTN is considered a reversible chronic disease that can effectively be managed by lifestyle modifications and appropriate medications (100). Also, because HTN is a major risk factor in many other organ related chronic diseases , early identification and treatment is beneficial in reducing long-term health complications (84).    17 Cardiovascular	disease	and	HIV	Cardiovascular disease (CVD) is a broad class of diseases that affect the heart (105). These diseases include myocardial infarction, angina, stroke, atrial fibrillation, congenital heart disease, endocarditis, cardiomyopathy and congestive heart failure.  Each of these diseases varies in cause and physiology, but all are related and include similar risk factors such as: atherosclerosis, smoking, diabetes, hypertension, lack of physical activity, obesity, dyslipidemia, poor diet and excessive alcohol use (105). Despite 90% of all CVDs being preventable, CVD remains as one of the leading causes of death globally (104).   In 2013, 17.3 million deaths (31.5%) were a result of CVD (105). In high-income countries, incidence of CVD has been on a steady decline since the late 1970s (93). In the U.S., 26.6 million adults (11.3% of adult population) were reported to have diagnosed CVD in 2012—approximately 610,000 people incur CVD-related deaths (25% of all deaths in the U.S.) (93). In Canada, the burden is comparable to the U.S. with 1.4 million Canadians reported to have CVD in 2009, while also being the leading cause of deaths with 33,600 CVD-related deaths per year (106, 107).   Evidence of HIV infection as a risk factor for CVD incidence is an emerging clinical outcome—whether this is due to the increased life expectancy of PLWH or a physiological response to the HIV infection is poorly understood. However, similar to most other chronic comorbidities a major risk factor associated with both CVD and HIV is smoking (91). The exact benefits and risks associated with the use of  HAART with   18 respect to CVD have been difficult to discern. Evidence from the START trial, has shown that patients discontinuing HAART have increased risk of developing CVD, and other studies have shown that untreated HIV patients are at even greater risk for CVD due to greater inflammation and weakening of blood vessels (82, 108, 109). In the same way some HAART medications can contribute to DM incidence (e.g. ritonavir, efavirenz and stavudine), these same effects can also result in CVD. One example of how these medications may lead to CVD is by increasing serum triglycerides levels, which is a common risk factor in many CVD-based diseases (82). Studies examining various HAART medications that may increase  risk for CVD in an area of active ongoing research. (110).   COPD/asthma	and	HIV	Chronic obstructive pulmonary disease (COPD) and asthma are two different diseases that disrupt respiratory physiology. COPD is characterized by chronic poor air flow leading to shortness of breath, cough and sputum production (111). The major risk factors for COPD are smoking, exposure to air pollution and genetics—leading to emphysema, which is the degradation of small airways in the lungs due to inflammatory responses (111). Asthma shares similar characteristics as COPD, but is caused by airway hyper-responsiveness and airflow resistance from edema and inflammation (112). Because asthma is not a result of cell destruction as it is in COPD, the symptoms can be reversed by bronchodilator therapies. Additionally, asthma is more likely to occur at an earlier onset due to history of allergies such as hay fever (112).     19 COPD continues to be a growing concern in adult populations worldwide due to the increased popularity of smoking and tobacco in the late 1900s (111). There were an estimated 329 million cases of COPD in 2010 globally (93). In recent years rates of COPD have steadily decreased in high income countries, but continue to remain high in low and middle income countries (93). In 2012, COPD was considered the third leading cause of deaths in adults worldwide with rates of 3.1 million deaths per year (93). In the U.S., 15 million diagnosed cases (and another estimated 10 million undiagnosed cases) represent a prevalence of almost 10% of the entire U.S. adult population (93). In Canada, 1.3 million cases were reported in 2009-2011, and an estimated 4 million cases were believed to be indicative of COPD (113). Asthma is far less common than COPD in adult populations, and is more common in children, where an estimated 235 million cases of asthma were reported in 2011, leading to 250 thousand deaths per year (114).   COPD is a commonly associated comorbidity among PLWH. In the VA Cohort, HIV-positive patients were 50-60% more likely to have COPD than HIV-negative patients and HIV was found to be an independent predictor of COPD after adjusting for age, race, ethnicity, pack-years of smoking and alcohol/drug abuse (87). The prevalence of COPD among HIV-positive patients in the VA cohort was 11%, and for asthma, the prevalence was 6% (87). Some medications for COPD and asthma may interact with HAART medications which can result in serious clinical side effects. These medications  include: fluticasone, theophylline, long-acting beta-agonists, leukotriene receptor antagonists and inhaled corticosteroids (115). In addition to these drug interactions, COPD is one of the most under-diagnosed diseases, and progression of undiagnosed   20 COPD in aging HIV-positive patients may lead to serious long-term health complications (111). Thus, better clinical management of COPD and frequent screening for risk factors common in both diseases (i.e. smoking) in PLWH are important in caring for the future of HIV populations and preventing greater risks for COPD or asthma in the future.  Chronic	kidney	disease	and	HIV	Chronic kidney disease (CKD) is characterized by the gradual loss of renal function—resulting in an impaired ability effectively to excrete wastes from blood into urine through the kidneys (116). It is important to note that CKD represents an array of renal disorders, but in this context we will discuss impaired glomerular function. Diagnosis of CKD is based on persistent levels of higher than normal serum creatinine concentrations. Creatinine is broken down in muscle metabolism, and high concentrations in the blood are a result of the kidney’s inability to filter it into the urine due to glomerular function damage. Early identification of CKD is important in reducing the progression of glomerular function damage, and while progression can be slowed, complete reversibility is not possible (116). CKD can eventually progress to end-stage renal disease—requiring the use of artificial filtration (via dialysis) (95-97) or kidney transplantation (116).  In 2013, almost 1 million deaths were a result of CKD globally (93). In the U.S., an estimated 20 million people are living with CKD, almost 10% of the adult population in 2011, with an estimated 110,000 people per year starting end-stage renal disease treatment (93). In Canada, these estimates are similar with approximately 2 million   21 people living with CKD, and 22,000 prevalent cases of end-stage renal disease per year (117).  Approximately 30% of all PLWH also have some form of CKD (118). CKD is commonly formed in untreated HIV patients, through HIV-associated nephropathy (118). African-American males are at high risk for CKD through HIV-associated nephropathy, and even more so when CD4 cell counts fall below 200cells/mm3 (118).  However, nephropathy can be reversed through effective HIV treatment resulting in virologic suppression. Therefore, immediate HAART initiation has been recommended for several years in patients with HIV-associated nephropathy, irrespective of CD4 cell counts (119). Another form of developing CKD is through nephrotoxicity—meaning injury that harms the kidneys. In HIV-positive populations, nephrotoxicity can result from adverse effects from certain types of PIs and NRTIs—namely tenofovir in HAART (120). On balance, however, HAART has been shown to be the most effective preventative measure against CKD in HIV-positive populations, as it has proven benefit by reducing HIV-associated nephropathy (119).  Chronic	liver	disease	and	HIV	Chronic liver disease (CLD) refers to the persistent and progressive deterioration of the liver eventually leading to fibrosis and cirrhosis (121). Similar to CKD, CLD is caused by many different factors. Generally,  liver disease is considered chronic when the disease persists for greater than six months (121). Diseases that most commonly characterize CLD include: alcoholic hepatitis/cirrhosis, hepatitis C infection, hepatitis B infection and non-alcoholic fatty liver disease. Because of the variety of CLD types,   22 many different risk factors contribute to the development of CLD including: exposure to hepatitis infected blood and blood products (through needle sharing, blood transfusions or workplace exposures), excessive alcohol use, high levels of blood lipids, obesity and exposure to toxic chemicals in workplaces without proper safety equipment (121). In addition to these risk factors, CLD is also more commonly in the young adult populations (i.e. age 35-50) (121). CLD resulted in approximately 1 million deaths in 2010 worldwide, with non-alcoholic fatty liver disease being the most common form of CLD (93). When including liver-related cancers and acute liver disease, this estimate is doubled to 2 million deaths annually (93). In 2013, almost 37,000 deaths were a result of CLD in the U.S. (93). Similarly in Canada, 5,000 deaths annually are attributed to CLD (122, 123).   Of all the comorbidities discussed in this thesis, CLD is by far the most overrepresented in HIV positive individuals relative to the general population, and continues to be a frequent cause of mortality and morbidity in HIV-positive populations (124). In BC, approximately 30% of all HIV-positive patients are co-infected with HCV or other chronic liver-related conditions (86). Damage done to the liver through CLD is further accelerated in patients with an HIV infection (124). These issues if left untreated can progress to cirrhosis, end-stage liver  disease and hepatocellular carcinoma (125).   In the VA cohort, an estimated 42% of all HIV-positive patients have  some form of CLD (e.g. cirrhosis, decompensated liver, hepatocellular carcinoma, hepatitis C virus and hepatitis B virus) (126). Due to the many overlapping risk factors in HIV patients  (smoking, injection drug use and alcohol abuse), the risk of CLD  is vastly increased   23 (127). Though there are few HAART medications that have some risk of liver toxicity (e.g. Naphthylvinylpyridine, Darunavir, Tipranavir, Stavudine and Didanosine), untreated HIV infection is believed to be a much greater threat to CLD progression it is important that diligent monitoring of HIV patients for CLD is routinely employed to prevent progression of CLD and reduced mortality in HIV positive populations.   Future	directions	Understanding how all these various chronic diseases interact with one another as the HIV-positive population continues to grow older is important in order to determine optimal strategies for treating HIV infection. Understanding more completely the risk factors associated with these diseases and how they interact with HAART is also an important area of further research. Decisions about how to manage multimorbidity in PLWH need to be undertaken, and strategies for reducing the negative effects of aging in HIV patients explored. Understanding the rates of and trends of these diseases in real-world scenarios is an important contribution to this effort.    24 Chapter 3: Trends of chronic comorbidities among HIV-positive individuals receiving HAART in BC from 2000-2012  Introduction Since the advent of HAART in 1996, HIV treatment has been demonstrated to reduce HIV and AIDS-related morbidity and mortality (4). Similarly, HAART has also been shown to reduce the incidence of non-HIV/AIDS related illnesses such as cardiovascular disease, non-AIDS cancers, and renal disease (6, 7, 128). The cumulative effects of HAART on HIV-positive populations has been to dramatically increase life expectancy, and consequently, introduce the issue of aging with HIV as a chronic condition (129). Only recently have researchers begun to study the effects of patients getting older with HIV (15). Currently, research regarding aging and HIV is in the initial stages, but as the average age of individuals living with HIV  continues to increase, health care policy makers and professionals will face issues regarding how best to design health services to meet the unique challenges of this population (14).   In Canada, based on the most recent estimates (2007) approximately 13% of all PLWH were over 50 years of age (130, 131). In the United States, according to CDC estimates in 2006, approximately 25% of PLWH are greater than 50 years of age (132). We can expect these numbers to increase. Due to the complex medical history of HIV-positive patients (e.g. immunocompromised health from infection and potential drug toxicities from medications), they are at higher risk for a number of chronic conditions   25 that are typically associated with aging in HIV-negative individuals (133). As HIV-positive patients live longer, the associated relationships and patterns of these comorbidities with HIV will become more evident. Determining strategies that meet the health care needs of people aging with HIV are necessary to better prepare health care systems for moving into the next era of HIV treatment.   Since HIV as a chronic disease is a recently recognized issue, knowledge about the long-term effects of aging with HIV on the incidence of other chronic diseases is limited (17). Despite many clinical-based studies that suggest HIV-positive populations are at higher risk for chronic diseases (6, 7, 21), to our best knowledge, only one other study has characterized population-level chronic disease profiles of HIV-positive individuals; in this study HIV-positive Ontario residents characterized by number of and type of prevalent chronic diseases in a cross-sectional study (16). In this study 35% of HIV-positive Ontario residents were also diagnosed with at least one other chronic disease, with mental health conditions, hypertension and asthma being the most prevalent. A major strength  of this study was that it allowed for direct comparisons to the general population. We designed a study to characterize the trends of chronic disease incidence among HIV-positive residents of British Columbia, Canada receiving HAART over a thirteen-year period where HAART use increase substantially..     26 Methods Data Sources Data for this analysis were obtained from the COAST study dataset, which includes longitudinal health records of all HIV-positive BC residents who have had at least one viral load measurement from April 1st, 1996 to December 31st, 2012. The COAST dataset is based on a data linkage between the BC-CFE Drug Treatment Program (DTP) registry and Population Data BC. The BC-CfE DTP registry includes data on demographics, ART use, AIDS-defining illnesses, CD4 cell counts and viral load measurements for all HIV-positive individuals receiving ART in BC. Population Data BC provides access to longitudinal databases on health care services use, and specific to the COAST study include physician (MSP) and hospital (DAD) records for all BC residents (134-136). MSP records include physician billing diagnostic codes in outpatient and inpatient settings and DAD records include diagnostic codes used in hospitalization discharges. Data sources used to identify study subjects include: the BC-CFE DTP registry, laboratory testing datasets, DAD, MSP and PharmaNet databases. PharmaNet is a registry that includes information about prescription medications dispensed to all BC residents (137). Participants were excluded  from analyses criteria if they were 1) only dispensed lamiduvine or tenofovir, did not have an ARV start date and had a diagnosis of hepatitis B virus; or 2) did not meet Antoniou’s algorithm of 1 DAD or 3 MSP health records with an HIV diagnosis (138); or 3) individuals in the BC-CFE DTP cohort that did not have any HIV related record (pVL, hospitalization, MSP, first ADI date, first ARV date or AIDS/HIV related death). Those who met these exclusion criteria were considered unconfirmed cases of HIV diagnosis. All subjects included in this analysis   27 were identified as HIV-positive BC residents aged ≥ 19 from April 1st, 1996 to December 31st, 2012, by applying a validated case-finding algorithm (139).  Study Design We conducted a retrospective population-based cohort study of chronic disease incidence among HIV-positive individuals aged ≥ 19 in the COAST database. We assessed incidence of six chronic diseases among HIV-positive individuals who had accessed HAART from April 1, 1996 to December 31, 2012. Incidence rates were determined for each disease individually over a period of thirteen years, from January 1, 2000 to December 31, 2012. For each analysis, prevalent cases identified pre-baseline (April 1st, 1996 to December 31st, 1999) or cases that preceded their first HAART date were excluded from analyses (e.g. an individual identified as having prevalent DM in 1998 would be excluded from the DM incidence analysis). In order to truly account for disease incidence as it potentially relates to HAART, person-time was defined by HAART start date to incidence of disease or until the participant died or follow-up ended. Ethics approval for use of data was approved by the University of British Columbia-Providence Health Care Human Research Ethics Board (Ethics Certificate Number: H09-02905).   Study Variables The outcome variables in this analysis included six non-HIV related chronic diseases: cardiovascular disease (CVD), diabetes mellitus (DM), hypertension (HTN),   28 asthma/chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD) and chronic liver disease (CLD). Using codes from the ICD versions 9 and 10, identification of diseases were based on case finding algorithms using MSP and DAD health records in the COAST database (See Appendix 1.0).   Explanatory variables in this study include age at baseline, sex, ethnicity, baseline weighted Charlson Comorbidity Index (CCI), HIV risk group, HAART start date, and baseline CD4 cell count and pVL. The CCI, an index that identifies, categorizes and assigns weights to various comorbidities, was determined using a validated method developed at the Manitoba Centre for Health Policy; this adapted method takes into account comorbidities in both MSP and DAD databases (140). This tool takes into account the patient’s disease history and assigns patients an index (scores = 0-17, with 17 being the highest burden of disease) based on their medical diagnosis history. All patients in our study had a minimum weighted CCI equal to six because having an HIV diagnosis contributed to a weighted score of six. The baseline CCI algorithm used a four-year pre-HAART timeframe to construct the index; when four years of data were not available, a minimum of two years were required for the algorithm. Information about age, sex, ethnicity, death during study period, HIV risk group, HAART start date and baseline CD4 cell count and plasma viral load was obtained from the COAST database. Baseline CD4 cell count and pVL were based on last available record prior to HAART initiation; for cases where HAART initiation pre-exists April 1, 1996, the first available health record of CD4 cell count and plasma viral load was used.    29 Statistical Analysis Descriptive statistics were used to explore characteristics of the study population, and the distributions of the study variables. Poisson’s log-linear regression analysis was used to measure trends in incidence rates for each disease-specific analysis. Adjusted incidence rates were determined by controlling for variables: age at baseline, sex, baseline weighted CCI, CD4 cell count and log-10 pVL. Stratification of the incidence rates by age was conducted to explore patterns of incidence rate trends among increasing age categories (age categories: 19-35 years, 36-50 years and >50 years of age). Analyses were conducted using SAS 9.4 (SAS Institute Cary, North Carolina).  Results The case-finding algorithm yielded 28,061 individuals with at least one HIV-related health record (Figure 3.1). Information from the databases revealed that 13,097 individuals were confirmed cases of HIV (cases with Population Data BC and/or BC-CFE derived data satisfying the inclusion/exclusion criteria) (Figure 3.1). After application of the case-finding algorithm, 14,154 individuals were believed to be misclassified (i.e. not true HIV cases), yielding a total of 13,097 HIV-positive BC residents (Figure 3.1). Inclusion of all eligible study participants yielded a total of 10,203 HIV-positive BC residents age ≥ 19 that initiated HAART during the study time period (Figure 3.1).  The final analytic cohort was predominantly white (72%) males (83%) with a median age (IQR) of 37 (32-45) at treatment initiation (Table 3.1). Half of the population were known MSM (48.7%), one-third had known heterosexual risk (29.6%), 4.2% had a   30 known blood risk and 43.8% were known PWID (Table 3.1).The baseline median CD4 cell count and plasma viral load was 260 cells/µl and 4.85 log-10 copies/mL, respectively (Table 3.1). Distribution of baseline weighted CCI showed that 37.5% of the population had low comorbidity with HIV (one condition in addition to HIV) and 13.4% of the population had high comorbidity (greater than one condition in addition to HIV) (Table 3.1). A total of 76.4% of participants survived to the end of the study (Table 3.1). Based on the study population (n = 10,210) prevalence of the six outcomes prior to HAART initiation was 10% for DM (n = 1,067), 12% for CVD (n = 1,198), 13% for HTN (n = 1,327), 14% for COPD/Asthma (n = 1,438), 29% for CLD (n = 2,925) and 14% for CKD (n = 1,392) (Figure 3.3). Prevalent cases for each disease were not included in each respective analysis.   Diabetes Mellitus: Based on 1,067 prevalent cases of DM, 9,143 individuals were included in this analysis. The unadjusted incidence rates for DM showed a trend towards increasing rates later in the period (p=0.009), however, after adjustment, these trends were no longer statistically significant (p=0.114), (Table 3.2). Adjusted incidence rates fluctuated during the thirteen year follow-up period, where incidence rates in year 2000 was 3.34 (95% CI 1.6 - 6.96) per 1000 person years and 4.65 (3.07 - 7.05) per 1000 person years in 2012 (Figure 3.3). Age-specific stratified analysis showed that incidence rates were also stable in all three age categories (Figure 3.4).  Cardiovascular Disease: Based on 1,198 prevalent cases of CVD, 9,012 individuals were included in this analysis. We did not observe any significant trend in   31 incidence of CVD in either the unadjusted or adjusted models. For CVD incidence, rates in years 2000 and 2012 were 9.11 (5.87, 14.13) and 10.01 (7.55, 13.27) per 1000 person years respectively (p= 0.316 for trend test) (Figure 3.3). The Age stratified analysis also did not reveal any significant trends in CVD incidence rates for any of the age categories (Figure 3.4).   Hypertension: Based on 1,327 prevalent cases of HTN, 8,883 individuals were included in this analysis. Incidence rate trends were significant in both unadjusted model and adjusted Poisson’s regression (p < 0.001 for both models) (Table 3.2). HTN incidence rates increased over the thirteen year follow-up period, from 6.85 (4.2, 11.19) per 1000 person years in 2000 to 12.61 (9.59, 16.58) per 1000 person years in 2012, and was as high as 16.73 (12.84, 21.8) per 1000 person years in year 2008 (Figure 3.3). Age-specific stratified analyses showed that incidence rates significantly increased over time for individuals aged ≤35 from 3.1 per 1000 person-years in 2000 to 9.1 per 1000 person years in 2012 (p = <0.001).  Similarly, HTN incidence increased from 9.50 per 1000 person years to 16.9 1000 person years for individuals aged 36-50. However, we did not observe any change in HTN incidence for individuals aged  >50 years age. However, these individuals had the highest incidence, 21.9 per 1000 person years in 2012.    Chronic Obstructive Pulmonary Disease and Asthma: Based on 1,438 prevalent cases of COPD, 8,772 individuals were included in this analysis. There were no significant trends for COPD/Asthma, where incidence rates in years 2000 and 2012 were 17.24 (11.8 - 25.3) and 12.5 (9.3 - 16.8) per 1000 person years respectively (Figure 3.3).   32 Age-specific stratified analysis of the ≤35 years age category found decreased COPD/asthma incidence from 17.0 per 1000 person years in 2000 to 7.9 per 1000 person years in 2012 (p = 0.019). We did not observe any trends in COPD/Asthma incidence in the age-stratified analysis for categories 36-50 and >50 years of age (Figure 3.4).  Chronic Liver Disease: Based on 2,925 prevalent cases of CLD, 7,285 individuals were included in this analysis. (Table 3.2). In adjusted models CLD incidence rates decreased over the thirteen-year follow-up period, in and 2012 from  85.5 per 1000 person years (70.6, 103.5) in the year 2000 and to 26.91 (21.46, 33.74) per 1000 person years respectively (p<0.001) (Figure 3.3). We observed similar decrease in the incidence of CLD across all age groups (p<0.005 for all) (Figure 3.4).   Chronic Kidney Disease: Based on 1,392 prevalent cases of CKD, 8,818 individuals were included in this analysis. (Table 3.2). In adjusted models, CKD incidence rates increased over the thirteen-year follow up period, from 35.0 (26.8 - 45.7)  per 1000 person years in the year 2000 to  12.4 (9. 2 - 16.7) per 1000 person years in 2012 (Figure 3.3). Age-specific stratified analysis showed that incidence rates significantly decreased from 23.8 per 1000 person years in 2000 to 7.7 per 1000 person years in 2012 for the ≤35 age category (p < 0.001) and 47.8 per 1000 person years in 2000 to 12.5 per 1000 person years in 2012 for the 36-50 age category (p < 0.001). Incidence rates for individuals aged >50 years were stable over this period. (Figure 3.4). However, these individuals had the highest incidence, 30.9 per 1000 person years in 2012.  33 Discussion This study of over 10,000 HIV-positive individuals receiving HAART over a thirteen-year period in BC demonstrated decreasing rates of two chronic diseases, CLD and CKD, and increasing incidence rates of HTN. No changes were observed in incidence rates for COPD and CVD. Although no changes in trend were observed for both COPD and CVD, prevalence of all six chronic diseases were high at baseline (all ≥ 10%), consistent with past studies looking at chronic disease incidence among HIV-positive individuals (16, 21, 79). The magnitude of these changes varied by disease and persisted even after controlling for age. The incidence of HTN doubled to 16 per 1000 person years in 2012 compared to 8 per 1000 person years in 2000. Conversely, the incidence of CLD decreased from 61 per 1000 person years in 2000 to 38 per 1000 person years in 2012, a decrease of approximately 40%.  We observed less dramatic declines of approximately 20% for CKD rom 31 per 1000 person years in 2000 to 25 per 1000 person years in 2012. These shifts in trends paralleled shifts in BC’s HIV therapeutic guidelines which allowed more HIV positive individuals to access HIV treatment earlier in the course of their infection, however, we cannot be certain that this is what mediated the effects we have observed (11, 141).  Age-specific stratification revealed similar patterns in four of the six conditions—DM and CVD showing no trend for any of the three age categories nor for the whole group analyses. The only result that differed from the main analysis was that individuals in the ≤35 age group showed a significant decreasing trend in the incidence of COPD/asthma over time. In five of the six conditions, the >50 years of age group had much higher incidence rates and did not follow any trend over time—CLD being the  34 exception. For CLD, the >50 years of age category had lower incidence rates and followed a decreasing trend over time. The result that stood out most was the drastic CLD and CKD incidence rate decrease over time. These trends speak to the potential benefits of scaling up HAART on reducing liver- and renal-related morbidity, and though we cannot say for certain what the cause for these trend were, there are a number of reasons that could explain why they occurred. One potential explanation for the major decrease in CLD incidence is the result of reduced HCV infection from expansion  of harm reduction program. It is also possible that changes in  drug using behaviors among people who use drugs, may have affected the incidence of HCV in BC over this period. This decreasing trend of HCV is also consistent among HIV-negative individuals in BC (86). Reduced HIV/AIDS related morbidity and mortality resulted from these shifts in treatment guidelines, which also may have alleviated some renal-related complications that are commonly associated with HIV (142, 143).  An unsurprising result of this study was the increased trend of HTN during the study period. The incidence rates nearly doubled from 2000 to 2012, suggesting that over time PLWH were becoming at higher risk for developing HTN. This result could be explained by the aging HIV population—the increased life expectancy of PLWH allows them to live long enough to develop HTN. Moreover, high rates of HTN are also consistent with a population-based study of HIV-positive Ontario residents, where HTN was among the most prevalent comorbidities with a prevalence rate of 15% among PLWH (16).   35 The current study shows promising results on identifying decreased or no changes in trends for DM, CKD, COPD/asthma, CLD and CKD; however, considerations of the study limitations should be taken into account as they may influence the overall results. As with all studies using administrative databases, caution should be taken with generalizability to real-world applications. Information regarding disease incidence in administrative databases is limited to data that are entered by health care professionals in the DAD and through MSP billing—and not necessarily real-world diagnosis. In some instances, only one diagnosis code is recorded per medical visit, and in cases where patients have multi-morbidity, only one of those conditions may be recorded in the administrative database. Many studies have shown that misclassification and under-classification of diseases using administrative data is a major limitation (144). To mitigate this issue, we based case definitions on algorithms that accumulated diagnostic information rather than using single visits alone. This allowed us more accurately to capture incidence of chronic diseases, provided their diagnosis was documented at some point in MSP and DAD databases. Cases that were not billed by service providers or hospitalization discharge records would be impossible for us to include because of the unavailable information regarding their condition.  Another limitation to our study is the lack of detailed information on risk factors for chronic diseases such as smoking status, body-mass index, laboratory data and physical activity. None of this information is available through MSP and DAD, and without this information, it is difficult to control for the actual impact of HIV and aging separate form these other risk factors. Our best measure to control for chronic disease risk  36 was the weighted CCI, which is a proven tool for controlling for confounding using administrative data (140).  Lastly, our study did not include a comparison group. Understanding the trends of these six diseases in an HIV-positive group over time is still an important study, but determining how these trends relate to the general population using the same methods would uncover more information about how HIV status and HAART initiation affects chronic disease incidence. Fortunately, database linkages with our existing database to a sample of the general population are currently underway, and in future analyses we do plan on examining these relationships.  Despite the few limitations to our study, this study also presents many advantages that contribute to the understanding of the HIV and aging literature. This study is the first to examine population-based, longitudinal trends of chronic disease incidence of  HIV-positive individuals. The large sample size of all HIV-positive BC residents on HAART from 1996 to 2012 increases the external generalizability of the study to other similar populations in high-income countries in North America and Europe. Another strength of the study is the rich data available for analysis. There were many variables that were not available regarding chronic disease risk factors, but data related to HIV status was much more rich, which included information about HIV risk group, HIV treatment regimen, viral load, CD4 cell count as well as mortality. HIV and aging is an area of research that is only beginning to be explored. In the current study, we highlight the trends of six chronic conditions among HIV-positive individuals on HAART. Describing these trends allow us to understand the clinical characteristics of an aging HIV population and  37 provides us with information about the patterns exhibited by these various conditions over the past decade. Increasing trends of only one of these six conditions (HTN) suggests that among HIV-positive individuals on HAART, these other conditions are not of increasing concern.     38 Table 3.1: Baseline cohort characteristics (n=10,210) Characteristic Percent Age (n=10210)   ≤35 41.3% 36-50 47.1% >50 11.6% Median Age (IQR; n=10210)   2000 40 (35 - 46) 2003 42 (37 - 49) 2006 45 (39 - 51) 2009 46 (41 - 53) 2012 48 (41 - 55) Sex (n=10209)   Male 82.9% Female 17.1% Ethnicity (n=5945)   First Nation 22.1% Asian 5.7% Black 3.7% White 72.0% Hispanic 3.5% HIV Risk Group   Known MSM (n=7037) 48.7% Known Hetero Risk (n=7037) 29.6% Known Blood Risk (n=7037) 4.2% Known PWID (n=8170) 42.8% Death during study period 23.6% Median CD4 cell count (cells/µL; IQR; n=9981) 260 (140-400) Median pVL (copies/mL; IQR; n=7825) 4.85 (4.23 - 5.06) Weighted CCI categories (n=10210)   No comorbidity (CCI = 6) 49.2% Low comorbidity (CCI = 7-8) 37.5% High comorbidity (CCI ≥ 9) 13.4% MSM: Men who have sex with men; PWID: People who inject drugs; pVL: plasma viral load; IQR: inter-quartile range; CCI: Charlson Comorbidity Index   39  Figure 3.1. Summary of sample size changes based on exclusion and inclusion criteria  COAST: Comparative Outcomes and Health Service Utilization Trends; BC-CFE: British Columbia – Centre for Excellence in HIV/AIDS; Population Data BC: Population Data British Columbia; 3TC: lamivudine; TEN: tenofovir; HBV: hepatitis B virus; MSP: Medical Service Plan; ADI; AIDS defining illness; ARV: antiretroviral; HAART: highly active antiretroviral therapy   COAST population (HIV-positive) n = 13,907 Excluded Only dispensed 3TC or TEN and no first ARV date, then HBV n=43 Excluded No HIV related record from Viral Load, Hospitalization, MSP, first ADI date, first ARV date or death  n = 2,584 Excluded Only dispensed 3TC or TEN, then HBV n=26 Excluded Not confirmed with Antoniou's Algorithm (1 hospitalization record or 3 MSP records) n = 11,501 Included: Study 2 First ever HAART initiation between 2000-2012 n = 4,840 Considered for COAST population BC residents, age ≥19 years n = 28,061 BC-CFE DTP n =14,684  n =14,641  n = 12,057 n = 12,057 PopData BC n =13,377  n =13,351  n = 1,850 n = 1,850 Included: Study 1 Ever on HAART between 2000-2012 n = 10,210  40  Figure 3.2. Baseline prevalence of six chronic diseases among HIV-positive BC residents on HAART (n=10,210) DM: diabetes mellitus; HTN: hypertension; CVD: cardiovascular disease; COPD: chronic obstructive pulmonary disease / asthma; CLD: chronic liver disease; CKD: chronic kidney disease 0 500 1000 1500 2000 2500 3000 DM CVD HTN COPD CLD CKD 10% 12% 13% 14% 29% 14%  41  Table 3.2: Unadjusted and adjusted incidence rates (per 1000 person year) of six chronic diseases from 2000-2012 and associated p-value for Poisson regression test of trend  2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 p-value Unadjusted Incidence Rates (per 1000 person year) with 95% CI DM (N=9143)  6.25                (4.26, 9.50) 5.78                (3.90, 8.87) 8.16                (5.88, 11.65) 8.14                (5.87, 11.53) 8.32                (6.07, 11.68) 5.98                (4.12, 8.84) 8.02                (5.85, 11.18) 14.08                (11.1, 17.96) 13.73                (10.84, 17.43) 10.23                (7.75, 13.27) 9.46                (7.15, 12.31) 10.03                (7.91, 13.14) 7.26                (5.34, 9.64) 0.009 CVD (N=9012)  14.1                (11.08, 18.92) 9.36                (6.98, 13.3) 11.15                (8.58, 15.34) 11.25                (8.66, 15.32) 13.76                (10.91, 18.14) 14.28                (11.41, 18.65) 15.51                (12.23, 19.62) 13.74                (10.84, 17.70) 11.28                (8.56, 14.54) 13.06                (10.23, 16.49) 13.62                (10.84, 17.06) 11.85                (9.21, 14.85) 13.30                (10.34, 16.18) 0.858 HTN (N=8883)  13.81                (10.98, 18.73) 6.96                (5.01, 10.49) 16.15                (13.19, 21.29) 16.23                (13.23, 21.26) 16.07                (13.04, 20.94) 16.37                (13.35, 21.2) 20.96                (17.45, 26.22) 22.74                (19.06, 28.03) 23.38                (19.37, 28.25) 19.46                (15.81, 23.7) 18.26                (14.78, 22.21) 21.08                (17.07, 24.86) 17.24                (13.67, 20.59) <0.001 COPD (N=8772)  14.1                (10.90, 18.82) 10.16                (7.52, 14.18) 11.45                (8.63, 15.58) 11.06                (8.33, 15.04) 11.42                (8.69, 15.38) 13.51                (10.48, 17.63) 12.42                (9.53, 16.29) 12.55                (9.69, 16.34) 12.65                (9.76, 16.24) 14.80                (11.78, 18.54) 10.48                (7.98, 13.54) 13.15                (10.35, 16.39) 11.74                (9.06, 14.66) 0.917 CLD (N=7285)  69.01 (61.28, 80.36) 52.74 (45.91, 62.68) 48.11 (41.26, 57.21) 37.04 (30.91, 44.86) 47.57 (40.48, 56.01) 41.94 (34.92, 49.48) 40.08 (33.12, 47.22) 28.13 (22.75, 34.34) 26.48 (21.22, 32.13) 23.85 (18.54, 28.53) 25.41 (20.61, 30.6) 22.75 (18.45, 27.63) 22.52 (18.27, 27.15) <0.001 CKD (N=8818) 23.28                (19.24, 29.40) 17.02                (13.63, 22.20) 17.57                (14.14, 22.69) 22.42                (18.27, 27.70) 25.5                (21.35, 31.3) 32.61                (27.82, 38.97) 25.02                (20.80, 30.43) 21.98                (17.87, 26.74) 20.46                (16.41, 24.65) 17.11                (13.20, 20.44) 17.58                (14.12, 21.32) 14.45                (11.3, 17.65) 12.54                (9.67, 15.44) <0.001                Adjusted Incidence Rates (per 1000 person year) with 95% CI (adjusted for age, sex, baseline weighted CCI, CD4 and PVL (log-10)) DM (N=9143)  3.34                (1.6, 6.96) 3.63                (1.80, 7.31) 6.43                (3.85, 10.74) 6.35                (3.83, 10.52) 7.00                (4.40, 11.13) 4.81                (2.81, 8.24) 6.38                (4.04, 10.10) 12.11                (8.81, 16.66) 11.58                (8.47, 15.85) 7.08                (4.81, 10.42) 7.14                (4.88, 10.45) 7.50                (5.27, 10.67) 4.65                (3.07, 7.05) 0.114 CVD (N=9012)  9.11                (5.87, 14.13) 6.74                (4.15, 10.94) 6.46                (4.01, 10.41) 9.51                (6.45, 14.02) 11.56                (8.14, 16.41) 9.72                (6.78, 13.95) 9.48                (6.65, 13.51) 9.56                (6.76, 13.51) 10.19                (7.38, 14.09) 8.75                (6.25, 12.26) 11.65                (8.74, 15.52) 8.01                (5.80, 11.06) 10.01                (7.55, 13.27) 0.316 HTN (N=8883)  6.85 (4.2, 11.19) 6.90                (4.28, 11.14) 8.48                (5.61, 12.83) 9.70                (6.66, 14.13) 8.45                (5.65, 12.63) 9.30                (6.41, 13.49) 13.53                (10.00, 18.31) 15.87                (12.09, 20.83) 16.73                (12.84, 21.8) 12.72                (9.45, 17.12) 14.25                (10.95, 18.53) 14.80                (11.45, 19.13) 12.61                (9.59, 16.58) <0.001 COPD (N=8772)  17.24                (11.76, 25.25) 15.20                (10.3, 22.44) 13.22                (8.76, 19.94) 12.83                (8.63, 19.08) 14.91                (10.43, 21.32) 17.29                (12.5, 23.91) 15.28                (10.94, 21.35) 14.99                (10.84, 20.74) 16.45                (12.17, 22.24) 19.33                (14.83, 25.19) 14.14                (10.55, 18.95) 15.06                (11.35, 19.97) 12.49                (9.29, 16.79) 0.699 CLD (N=7285)  85.5                (70.6, 103.5) 79.91                (65.73, 97.13) 62.64                (50.56, 77.6) 46.12                (36.31, 58.57) 60.55                (49.46, 74.11) 48.52                (38.76, 60.74) 48.98                (39.35, 60.97) 37.76                (29.72, 47.97) 33.03                (25.79, 42.3) 27.84                (21.6, 35.89) 33.39                (26.73, 41.7) 30.41                (24.37, 37.95) 26.91                (21.46, 33.74) <0.001 CKD (N=8818) 35.02                (26.82, 45.72) 28.21                (21.12, 37.66) 20.23                (14.56, 28.12) 28.46                (21.68, 37.37) 31.09                (24.19, 39.96) 36.25                (28.88, 45.51) 28.15                (21.92, 36.15) 25.44                (19.66, 32.92) 22.23                (17.07, 28.96) 20.91                (16.14, 27.1) 21.47                (16.88, 27.30) 14.41                (10.81, 19.21) 12.39                (9.22, 16.65) <0.001 DM: diabetes mellitus; HTN: hypertension; CVD: cardiovascular disease; COPD: chronic obstructive pulmonary disease / asthma; CLD: chronic liver disease; CKD: chronic kidney disease; CCI: Charlson Comorbidity Index; pVL: plasma viral load; CI: confidence intervals  42     * p < 0.001 Figure 3.3. Adjusted incidence rates (per 1000 person year) over time (adjusted by age, sex, baseline weighted CCI, CD4 and log-10 pVL) HAART: highly active antiretroviral therapy; DM: diabetes mellitus; HTN: hypertension; CVD: cardiovascular disease; COPD: chronic obstructive pulmonary disease / asthma; CLD: chronic liver disease; CKD: chronic kidney disease; CCI: Charlson Comorbidity Index; pVL: plasma viral load  0 100 200 300 400 500 600 700 0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 100.00 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Number of individuals initiating HAART Adjusted Incidence Rate (per 1000 person year) DM CVD HTN* COPD CLD* CKD* HAART start  43       * p < 0.001  Figure 3.4. Age stratified adjusted incidence rates (per 1000 person year) over time (adjusted by sex, baseline weighted CCI, CD4 and log-10 pVL for six chronic diseases DM: diabetes mellitus; HTN: hypertension; CVD: cardiovascular disease; COPD: chronic obstructive pulmonary disease / asthma; CLD: chronic liver disease; CKD: chronic kidney disease; CCI: Charlson Comorbidity Index; pVL: plasma viral load 0.00 20.00 40.00 60.00 2000 2002 2004 2006 2008 2010 2012 DM ≤35 36-50 >50 0.00 20.00 40.00 2000 2002 2004 2006 2008 2010 2012 CVD ≤35 36-50 >50 0.00 20.00 40.00 60.00 2000 2002 2004 2006 2008 2010 2012 HTN ≤35* 36-50* >50 0.00 20.00 40.00 60.00 2000 2002 2004 2006 2008 2010 2012 COPD/Asthma ≤35* 36-50 >50 0.00 50.00 100.00 150.00 2000 2002 2004 2006 2008 2010 2012 CLD ≤35* 36-50* >50* 0.00 20.00 40.00 60.00 80.00 2000 2002 2004 2006 2008 2010 2012 CKD ≤35* 36-50* >50   44 Chapter 4: Impact of expanded access to HAART on chronic comorbidities among HIV-positive individuals initiating HAART in BC Introduction Since the introduction of HAART as treatment for HIV-positive patients in 1996, patients now have longer life expectancies and reduced HIV/AIDS-related morbidity and mortality (1, 4, 19). Although the reduced morbidity and mortality is viewed as one of the greatest achievements in HIV/AIDS research, the emerging issue of HIV with aging-related comorbidities is becoming problematic because little is known about the long term effects of living with HIV and taking HAART (9, 13, 17, 145, 146). To date, research on HAART has shown clear effectiveness in terms of  reducing the incidence of non-HIV/AIDS-related illnesses such as cardiovascular disease, renal disease, non-AIDS cancers and liver disease, but evaluations of the long-term effects of treatment have yet to be explored (6, 7, 128). Overall, the cumulative effects of HAART on HIV-positive populations has resulted in increased life expectancy, and consequently, has introduced the era of aging with HIV as a chronic condition (1). Currently, research regarding aging and HIV is in the initial stages, but as the HIV infected population  continues to grow older in Canada and other industrialized countries, health care policy makers and professionals will face issues how to most effectively care for PLWH (89, 147, 148). In Canada, based on the most recent estimates (2007) approximately 13% of all PLWH were over 50 years of age (130, 131). There is a great need to define strategies that accommodate the health care needs of this specific population (89, 149). Due to immunocompromised health, HIV-positive patients are at higher risk for a number of   45 chronic conditions that are typically associated with aging (97, 150-152). As HIV-positive patients are able to live longer, the likelihood of developing these aging-associated chronic comorbidities are increased (17, 74).  The benefits of HAART on  reducing the impact of chronic comorbidities are apparent. At the biological level, initiating HAART promotes viral suppression in patients and consequently results in recovered and restored immune function (51). The reduced depletion and inflammation caused by HIV/AIDS is beneficial in preventing other chronic diseases associated with an accelerated aging immune function (73). From a health care perspective, patients who initiate HAART are more likely to stay connected to care providers, and the constant interaction with the health care system can facilitate healthier lifestyle choices that prevent the development of other chronic diseases (e.g. quitting smoking or sticking with a healthier diet) (153). There is also evidence that HAART earlier in the course of HIV infection has greater benefit in reducing diseases such as CVD and CKD compared to initiating treatment after some degree of immune function has declined. (6, 7, 21).  Despite many clinical-based studies that suggest HIV-positive populations are at higher risk for chronic diseases (6, 7), to our knowledge, only one other study has characterized population-level chronic disease profiles of HIV-positive individuals. In that study HIV-positive Ontario residents were characterized by number and type of prevalent chronic diseases in a cross-sectional study (16). This study found that 35% of HIV-positive Ontario residents had been diagnosed with at least one other chronic disease and that mental health conditions, hypertension and asthma were the most prevalent. In another study, the INSIGHT START study group conducted a randomized trial following   46 4,685 patients for a mean of three years. This study found that patients who started HAART early enjoyed greater net health benefits (both serious AIDS and non-AIDS events) than patients who started deferred HAART (21).  The study setting of BC, Canada provides an opportunity to explore the relationship between the timing of HAART initiation and outcomes because of its provincial registry of all HIV-positive individuals receiving publically funded HAART.  Since 2006, BC has adopted increasingly liberal treatment guidelines and in 2011 formally adopted “Treatment as Prevention” as a Ministry of Health policy (11). This, in turn, allows us to study the effects of these policies through linkages with other provincial health service databases. Clinical guidelines regarding the use of HAART have shifted towards recommending treatment earlier in the course of HIV infection, resulting in increased numbers of people accessing treatment over time (2, 11, 18). This shift in policy gives us a window to evaluate the differences between HIV-positive people who start treatment later, often when they are already severely ill, and people who start treatment earlier in the course of their disease. We wish to examine the effect of HAART expansion in BC on incidence rates of six aging-related comorbidities, comparing the incidence of these diseases among individuals initiating HAART in the pre-expansion era from 2000-2005, with those initiating in the post-expansion era of 2006-2012. This study is unique because it is the first study that looks at the effect of policy intervention at the population level on incidence of chronic diseases.     47 Methods Data Sources Data for this analysis were obtained from the COAST study dataset, which includes longitudinal health records of all HIV-positive BC residents who have had at least one viral load measurement. The COAST dataset is based on a data linkage between the BC-CFE DTP registry and Population Data BC. The BC-CfE DTP registry includes data on demographics, HAART use, and AIDS-defining illnesses, CD4 cell counts and viral load measurements for all HIV-positive individuals receiving HAART in BC. Population Data BC is a provincial data holding and service provider that holds longitudinal databases such as those of the Medical Service Plan (MSP), the hospital Discharge Abstract Database (DAD) and PharmaNet, containing health records for all BC residents (134-137). MSP records are based on physician billing diagnostic codes in outpatient settings and DAD records are based on diagnostic codes used in hospitalization discharges. Data sources used to identify study subjects include: the BC-CFE DTP registry, DAD, MSP and PharmaNet databases. Exclusion criteria included individuals 1) to whom only dispensed lamivudine or tenofovir were dispensed, did not have an ARV start date and had a diagnosis of hepatitis B virus; 2)  did not meet Antoniou’s algorithm of 1 DAD or 3 MSP health records with a diagnosis of HIV (138); or 3) individuals in the BC-CFE DTP program that did not have any HIV related record (pVL, hospitalization, MSP, first ADI date, first ARV date or AIDS/HIV related death). Those who met these exclusion criteria were considered unconfirmed cases of HIV diagnosis. All individuals included in this analysis were identified as HIV-positive, aged ≥ 19 years, whom were   48 HAART naïve (initiated HAART without previous ARV exposure in BC) from January 1st, 2000 to December 31st, 2012, by applying a validated case-finding algorithm (139).   Study Design We conducted a retrospective population-based cohort study of non-HIV related chronic disease incidence from HIV-positive individuals aged ≥ 19 in the COAST database. We compared incidence of six chronic diseases among HIV-positive individuals in two time periods: the post-HAART expansion period (January 1, 2006 to December 31, 2012) and pre-HAART expansion period (January 1, 2000 to December 31, 2005). The justification for defining the periods this way was based on 2006 being the year in which the BC therapeutic guidelines were first liberalized to allow all individuals with CD4 cell counts ≤350 cells/µL to initiate HAART. This resulted in increasing number of individuals whom were accessing HAART compared to previous years. To account for different lengths of follow-up time between the pre- and post-HAART expansion groups, we limited the follow-up time of individuals in in the early HAART period to year 2006 which allowed both time periods to have a maximum follow up time of seven years. Incidence rates were calculated  for each disease individually for each time period (pre- and post- HAART expansion periods), from January 1, 2000 to December 31, 2012. These analyses utilized two modeling approaches to determine the impact of HAART expansion on chronic diseases incidence. In the first modeling approach, we modeled the relative risk of disease incidence for those whom initiated HAART in the post-HAART expansion period relative to those whom initiated HAART in the pre- HAART expansion period. This method was used to determine differences in   49 chronic disease incidence by individuals’ HAART initiation date. In the second modeling approach, we modeled the risk of disease incidence among all individuals actively on HAART during each time period. This approach was used to determine the trends of chronic disease incidence before and after the HAART access expansion (i.e. allowed us to observe trends of chronic disease incidence without including the impact of the intervention). We used Poisson regression analysis to conduct these models of chronic disease incidence in the post-HAART expansion period versus the pre-HAART expansion period. For each analysis, prevalent cases identified pre-baseline (April 1st, 1996 to December 31st, 1999) or for individuals who entered the cohort after the year 2000, cases that preceded their first HAART date, were excluded (e.g. an individual identified as having prevalent DM in 1998 would be excluded from the DM incidence analysis). In order to truly account for disease incidence as it relates to HAART, person-time was defined by HAART start date to incidence of disease and reported in 1000 person years. The study received ethics approval for use of data from the University of British Columbia-Providence Health Care Human Research Ethics Board (Ethics Certificate Number: H09-02905).  Study Variables The outcome variables in this analysis were incidence of six chronic diseases: CVD, DM, HTN, asthma/ COPD, CKD and CLD. Using codes from the ICD versions 9 and 10, identification of diseases was based on case-finding algorithms using MSP physician billing data for outpatient visits and DAD for hospitalizations health records in the COAST database (See Appendix 1.0. for definitions).    50 Individuals were assigned to two groups: those who initiated HAART before 2006 (pre-HAART expansion group) and those who initiated HAART after 2005 (post-HAART expansion group). Date of first HAART dispensing date was used to categorize the two groups. Other explanatory variables in this study include age at baseline, sex, baseline weighted Charlson Comorbidity Index (CCI), first HAART regimen, HAART start date, total follow-up time, baseline CD4 cell count, and log-10 pVL. The CCI was determined using a validated method developed at the Manitoba Centre for Health Policy; this adapted method takes into account comorbidities in both MSP and DAD databases (140). The CCI is based on a disease burden scoring algorithm that ranges from 0-17, with increasing numbers representing greater disease burden. For our study population, since all individuals are HIV positive, the minimum CCI score for all individuals is CCI=6.  The baseline CCI algorithm used a four-year pre-HAART timeframe to construct the index; when four years of data were not available, a minimum of two years was required for the algorithm. Information about age, sex, first HAART regimen, HAART start date, total follow-up time and baseline CD4 cell count and viral load was obtained from the COAST database.  Statistical Analysis Descriptive statistics were used to explore characteristics of the study sample and the distributions of the study variables. Bivariate comparisons of all of individuals from the two HAART expansion eras were also compared using a Student’s t-test. Two modeling approaches were used to address the objectives of this study: 1) Poisson regression analysis between individuals who initiated HAART in each period to   51 determine relative risk between disease incidence and 2) Poisson regression between individuals actively on HAART in each time period to determine differences in risk rate between time periods (i.e. in the second modeling approach HAART initiation date was not used to create groups as in the first modeling approach). Poisson regression analysis was used to determine the relative risk of disease incidence for the post- versus pre-HAART expansion period for each disease-specific analysis. By using Poisson regression analysis, we were able to control statistically for follow-up time when comparing incidence rates between individuals in the post- and pre-HAART expansion periods. Relative risks of all other covariates were also explored to determine associations between covariates and disease incidence. Adjusted relative risk were determined by controlling for the following variables: age at baseline, sex, baseline weighted CCI, first HAART regimen, HAART start date, baseline CD4 cell count, and log-10 pVL.  In the second approach, Poisson regression analysis was also used to compare differences between overall trend of all individuals actively on HAART before and after the policy intervention. This method measured the risk of chronic disease incidence during each time period (pre-HAART expansion period and post-HAART expansion period) regardless of individuals’ HAART initiation date. By including an interaction between current year and HAART expansion period, we were able to determine whether there was a significant change in risk for disease in the post-HAART expansion period relative to the pre-HAART expansion period. This method was used in a previous study to examine the impact of HIV transmission after a policy allowing free access to HAART (154). The main difference between the second approach and the first approach is that in the first approach, we compared chronic disease incidence between groups that started   52 HAART in the pre- and post-HAART expansion periods; and in the second approach we compared disease incidence among all individuals receiving HAART in the two time periods. Analyses were conducted using SAS 9.3 (SAS Institute Cary, North Carolina). Results The case-finding algorithm yielded 28,061 individuals with at least one HIV-related health record (Figure 3.1). Information from the databases revealed that 13,097 were confirmed cases of HIV (cases with information from Population Data BC and/or BC-CFE satisfying the inclusion/exclusion criteria) (Figure 3.1). After application of the case-finding algorithm, 14,154 individuals were removed from the dataset based on our exclusion criteria yielding a total of 13,097 HIV-positive BC residents (Figure 3.1). After applying an inclusion criterion of having a first-ever HAART initiation date between January 1st, 2000 and December 31st, 2012, we identified a total of 4,840 HIV-positive, HAART naïve BC residents age ≥ 19 within the study time period (Figure 3.1).  The final cohort was dominantly male (80%) with a median age (IQR) of 38 (31, 46) at the time of their first record (Table 4.1). Baseline median CD4 cell count and pVL were 220 cells/µl and 4.89 log-10 copies/mL, respectively (Table 4.1). Distribution of baseline weighted CCI showed that 41.6% had no comorbidity, 42% of the population had one condition in addition to HIV and 16.4% of the population had greater than one condition in addition to HIV (Table 4.1). Based on a total study population of 4,840 individuals, baseline prevalence of the six outcomes were 6.6% for CVD (n = 319), 9.4% for COPD/Asthma (n = 455), 4.8% for DM (n = 231), 8.5% for HTN (n = 411), 12.6% for CKD (n = 611) and 21.7% for CLD (n = 1,050) (Table 4.1). Individuals with prevalent diagnoses for each disease were not included in each respective disease-specific   53 analysis. There were several significant differences between those who initiated HAART in years 2000-2005 (pre-HAART expansion) versus those who initiated HAART in years 2006-2012 (post-HAART expansion), where: first regimen drug class and weighted CCI (p<0.001) showed differences for various treatment types (p=0.001); prevalent COPD (8.1% compared to 10.1%; p=0.018), DM (3.8% compared to 5.3%; p=0.017) and HTN (5.4% compared to 10.2%; p<0.001) and median baseline CD4 cell count (160 cells/µL compared to 260 cells/µL; p<0.001) were greater in the post-HAART expansion period; and prevalent CKD (16.2% compared to 10.6%; p<0.001) and log-10 pVL (5.00 copies/mL compared to 4.77 copies/mL; p<0.001) were greater in the pre-HAART expansion period (Table 4.1). In unadjusted Poisson regression, only CLD had a significant relative risk reduction as a result of HAART expansion of 0.63 (with 95% confidence intervals: 0.52 - 0.77) (Table 4.2). After adjusting for age, sex, first regimen drug class, baseline weighted CCI, log-10 pVL and CD4 cell count, CLD was the only disease with a significantly different RR of disease incidence in the post-expansion era (adjusted RR of 0.67; 95% CI 0.55 - 0.82) (Table 4.3). All other chronic diseases remained stable after adjusting for these covariates (Table 4.3). In the second modeling approach, comparison of adjusted risk rates between the two time periods: pre-HAART expansion (2000-2005) and post-HAART expansion (2006-2012) showed that five of the six diseases showed significantly different risk rates—CKD was the only disease that did not have show a significant difference in risk of disease incidence between the two time periods (p=0.1484) (Table 4.4). For both time periods all diseases had a risk rate below 1 indicating a reduction in disease incidence in   54 the post-expansion period (Table 4.4). All six diseases exhibited the same pattern, where disease incidence had a greater decrease in the post-HAART expansion periods relative to the pre-HAART expansion periods, suggesting a reduction in disease incidence in the post-HAART expansion period (Figure 4.1). The magnitude of these risk rate reductions were 0.93 (95% CI 0.88 - 0.98) in years 2000-2005 to 0.80 (0.76 - 0.83) in years 2006-2012 for CVD; 0.95 (0.90 - 1.01) in years 2000-2005 to 0.81 (0.78 - 0.84) in years 2006-2012 for COPD; 0.97 (0.91 - 1.04) in years 2000-2005 to 0.78 (0.74 - 0.82) in years 2006-2012 for DM; 0.97 (0.92 - 1.01) in years 2000-2005 to 0.81 (0.79 - 0.84) in years 2006-2012 for HTN; and 0.88 (0.84 - 0.92) in years 2000-2005 to 0.82 (0.79 - 0.84) in years 2006-2012 for CLD. The difference in magnitude for CKD was not significant.  Discussion The current study demonstrated the impact of changes to BC’s HIV therapeutic guidelines, which resulted in expansion of HAART accessibility to HIV-positive BC residents in the mid 2000s. Our study used two approaches to evaluate the impact of HAART expansion on chronic disease incidence—comparisons based on HAART initiation date, and comparisons which included all patients receiving HAART during each period.  In the first approach, we compared differences in risk for chronic disease incidence between individuals who initiated HAART between years 2000-2005 (pre-HAART expansion period) and individuals who initiated HAART between years 2006-2012 (post-HAART expansion period). We found that individuals in the post-expansion period had a reduced risk of CLD incidence relative to individuals in the pre-HAART   55 expansion period. However, there were no significant differences in the relative risks for CVD, COPD/Asthma, DM, HTN and CKD. In our second approach, we measured the risk rate of disease incidence of all individuals actively on HAART during each time period and modeled an interaction between current year and HAART expansion to determine differences between the two time periods. We found a significant reduction in disease incidence for all diseases, except for CKD. The results of the two approaches may suggest that over time there has been an overall reduction in incidence of CVD, COPD/Asthma, DM, HTN and CLD regardless of the HAART access expansion. Therefore, despite the trend of decreased incidence for CVD, DM, HTN, COPD/asthma and CLD for all participants receiving HAART, only CLD incidence seemed to be significantly affected by HAART expansion. However, the graphical results in Figure 1 show that majority of reduced incidence for CLD occurs much earlier than the HAART expansion period, which suggests that the reduced CLD incidence may not be a result of HAART access expansion, but rather due to other ecological factors that occurred much earlier than year 2005.  It is important to note that since this is an observational study evaluating the affect of a policy change over a period of time, and  there are many study limitations that should be considered. In this study, comparison of the pre-HAART expansion group to the post-HAART expansion group is being made during two different periods of time. The follow-up period for the pre-HAART expansion period is 2000-2006, and the follow-up period for the post-HAART expansion period occurs during years 2006-2012. This assumes that there are no other events that occur during these periods that may interfere with differences in chronic disease incidence. In this study the trends of CLD incidence were   56 much greater prior to the introduction of HAART expansion policies (Figure 4.1).  One consideration that would have a major impact on CLD incidence, specifically HCV incidence, is the introduction of many BC harm reduction programs, during the study period, as these programs have shown effectiveness in reducing HCV through altered drug using behaviors (86, 155). Thus, the significant reduction of CLD observed in our study may not be a result of HAART expansion, but rather a result of these other policies that were introduced during the same period of time.  Another consideration with this study is that this study is based on data taken from administrative databases. Using administrative data from sources such as MSP and DAD databases means that patients’ diagnoses are those recorded when they are  hospitalized or have an outpatient visit with a health care professional; these diagnoses may not truly be representative of their actual diagnosis. For example, physicians often record only one diagnosis per visit, even if the patient has a number of chronic conditions. Previous studies show that mis- and under-classification of diseases using administrative data is common (144). In our study, case definitions for diseases were based on multiple criteria that required multiple diagnostic records, allowing us to strengthen the accuracy of our case definitions and also mitigate the issues of mis- and under-classification of diseases.  In addition, since our study was based on information from administrative databases—mainly MSP and DAD—patient information that would typically be found in medical charts was not available to us (e.g. smoking status, body mass index, laboratory data, physical activity). Because we are modeling the impact of HAART expansion on chronic disease outcomes, having information on chronic disease risk factors is useful in   57 adjusting for confounding between the pre- and post- HAART expansion periods. Since this information was not available, we used the weighted CCI—a proven tool used to control for confounding with administrative data (140). By controlling for weighted CCI in the model, we were able account for differences in baseline multimorbidity between the pre- and post-HAART expansion periods.  Lastly, another limitation of this study was the inability to compare chronic disease incidence between those that were diagnosed with HIV  in the pre- versus the post-HAART expansion period over the entire study time period. Since baseline was defined by first HAART date, and not HIV diagnosis date, we had no record of seroconversion and were not able to distinguish HIV status prior to their first HAART date. Without knowledge of HIV-status, interpretations would be loosely based on the assumption that some individuals in the post-HAART expansion period were HIV-positive in years 2000-2005, and were just not accessing HAART during this time. These ‘potentially HIV-positive individuals’ may have developed chronic diseases prior to initiating HAART and would therefore be excluded from our analyses, resulting in a selection bias in this study.  Despite the few limitations of the current study, there are also a number of advantages that make this study an important and unique addition to the HIV and aging literature. The use of administrative databases to answer research questions with clinical implications is a valuable tool, and although there are many limitations in interpreting the data from these sources, there are also many strengths. A major strength of this study is the large cohort of all HAART-naïve HIV-positive BC residents with follow-up data over the course of a thirteen year period. This sample size and length of the current study   58 would be difficult to replicate without the use of administrative databases, which gives us the flexibility to conduct many different analytical methods. Conclusions drawn from this longitudinal study are more easily generalizable to other populations, as it is not drawn from a single clinic or group of clinics. In a similar study observing the impact of early versus deferred HIV treatment, the INSIGHT study group conducted the START trial. The START trial was a multi-site, randomized, global trial that evaluated the effectiveness of early HAART (started HAART regardless of CD4 cell count) versus deferred HAART (started HAART when CD4 cell count was below 350 cells/µL). A total of 4,685 individuals were followed longitudinally with 2,326 individuals starting HAART early starters and 2,359 deferring HAART. When comparing serious AIDS and non-AIDS related outcomes, the hazard ratio for the primary end-point was 0.43 (95%CI: 0.30, 0.62), and occurred in 42 individuals in the early HAART group compared to 96 individuals in the deferred HAART group. The results of this  trial demonstrated  that earlier initiation of HAART was proven to be most beneficial in preventing both AIDS and non-AIDS related outcomes (21). The conflicting results between our study and the START trial was the configuration of study arms/groups. In our study, our study arms were based on time period, and in the START trial study arms were based on HAART initiation data. This highlights an important consideration when implementing policy change, where the effect of implementing policies do not always have the same result of a research study. The expansion of increased access to HAART is becoming a global trend, and with much evidence supporting the benefits for early-HAART rather than deferred-HAART, this study explores the implications of early-HAART on aging-related chronic   59 disease incidence. The findings of this study suggest that the impact of a policy change that increased access to HAART resulted in decreased incidence of CLD—which are likely a result of other simultaneously occurring policies and not a result of HAART expansion. Understanding why these changes occurred is an important next step to determining whether HAART expansion had any impact on the shifts in incidence rates. As CLD incidence was the only significant observed change, further investigation about how these changes may also be reflected by changes to harm reduction policies over the study period are also necessary. As general acceptance for early-HAART being the standard for treating HIV and HAART expansion policies being implemented in many settings around the world, these results provide further insight into how HIV interacts with other chronic diseases. Further research that continues to evaluate how age-related chronic diseases affect PLWH are necessary to identifying how to better care for an aging HIV-positive population.      60 Table 4.1. Baseline cohort characteristics and investigation of relationship between chronic disease incidence and HAART initiation expansion  (n=4,840)     HAART initiation    Characteristic Overall (n=4,840) 2000-2005  (n=1,746) 2006-2012  (n=3,094) p-value Age at HAART initiation      0.199 ≤35 40.1% 38.5% 41.0%  36-50 46.2% 47.7% 45.3%  >50 13.7% 13.8% 13.6%  Median Age (years; IQR) 38 (31, 46) 38 (32, 46) 38 (31, 46) 0.223 Sex      0.051 Male 80.0% 78.5% 80.9%  Female 20.0% 21.5% 19.1%  First Regimen Drug Class      0.001 NNRTI 44.9% 45.1% 44.9%  PI 52.9% 53.8% 52.5%  Other 2.1% 1.1% 2.7%  Prevalence of Chronic Disease       CVD 6.6% 6.3% 6.8% 0.587 COPD 9.4% 8.1% 10.1% 0.018 DM 4.8% 3.8% 5.3% 0.017 HTN 8.5% 5.4% 10.2% <0.001 CKD 12.6% 16.2% 10.6% <0.001 CLD 21.7% 22.4% 21.3% 0.384 Follow-up Time       Median CD4 cell count (cells/µL; IQR) 220 (120, 350) 160 (70, 250) 260 (150, 390) <0.001 Median log-10 pVL  (copies/mL; IQR) 4.89 (4.32, 5.00) 5.00 (4.63, 5.00) 4.77 (4.21, 5.00) <0.001 Weighted CCI categories      <0.001 No comorbidity (CCI = 6) 41.6% 44.7% 39.8%  Low comorbidity (CCI = 7-8) 42.0% 41.9% 42.0%  High comorbidity (CCI ≥ 9) 16.4% 13.4% 18.2%   HAART: highly active antiretroviral therapy; CVD: cardiovascular disease; DM: diabetes mellitus; HTN: hypertension; COPD: chronic obstructive pulmonary disease; CLD: chronic liver disease; CKD: chronic kidney disease; NNRTI: non-nucleoside reverse-transcriptase inhibitor; PI: protease inhibitor; pVL: plasma HIV-1 RNA viral load; IQR: inter-quartile range; CCI: Charlson Comorbidity Index    61 Table 4.2. Unadjusted RR for disease incidence and various covariates with associated 95% CI, RR (95% CI)   CVD COPD DM HTN CKD CLD Covariate (n=4,521) (n=4,385) (n=4,609) (n=4,429) (n=4,229) (n=3,790) HAART Expansion              No Reference Reference Reference Reference Reference Reference  Yes 0.74 (0.54, 1.03) 0.96 (0.71, 1.29) 1.34 (0.9, 2) 1.35 (0.98, 1.87) 0.68 (0.36, 1.27) 0.63 (0.52, 0.77)               Sex at birth              Male Reference Reference Reference Reference Reference Reference  Female 0.49 (0.29, 0.82) 1.63 (1.17, 2.27) 0.77 (0.46, 1.27) 0.79 (0.52, 1.19) 0.37 (0.12, 1.21) 1.61 (1.28, 2.02)               Baseline age category             19-35 Reference Reference Reference Reference Reference Reference 36-50 2.29 (1.46, 3.59) 1.08 (0.77, 1.51) 2.50 (1.52, 4.1) 2.52 (1.66, 3.83) 4.45 (1.53, 12.96) 0.98 (0.79, 1.21) >50 6.76 (4.2, 10.87) 1.94 (1.28, 2.93) 4.60 (2.62, 8.06) 5.95 (3.76, 9.42) 11.55 (3.8, 35.09) 0.69 (0.49, 0.98)               First regimen drug class              NNRTI Reference Reference Reference Reference Reference Reference  PI 1.31 (0.93, 1.83) 1.17 (0.86, 1.59) 1.15 (0.78, 1.68) 0.98 (0.71, 1.34) 0.99 (0.53, 1.86) 0.78 (0.64, 0.95)  Other 1.17 (0.28, 4.78) 1.36 (0.43, 4.32) 1.27 (0.31, 5.24) 1.31 (0.41, 4.15) 0* 1.06 (0.5, 2.26)               Baseline log-10 pVL (copies/mL) 1.19 (1.1, 1.29) 1.16 (1.08, 1.25) 1.23 (1.12, 1.34) 1.12 (1.03, 1.23) 1.23 (1.06, 1.43) 1.05 (0.99, 1.12)               Baseline CD4 cell count (cells/µL) 1.39 (1.03, 1.87) 1.01 (0.83, 1.24) 1.24 (0.92, 1.68) 0.91 (0.75, 1.11) 1.00 (0.66, 1.53) 1.12 (0.96, 1.29)               Baseline Weighted CCI 0.86 (0.77, 0.96) 0.97 (0.89, 1.06) 0.92 (0.82, 1.03) 1.03 (0.95, 1.11) 0.86 (0.7, 1.05) 0.92 (0.87, 0.98) HAART: highly active antiretroviral therapy; CVD: cardiovascular disease; DM: diabetes mellitus; HTN: hypertension; COPD: chronic obstructive pulmonary disease; CLD: chronic liver disease; CKD: chronic kidney disease; NNRTI: non-nucleoside reverse-transcriptase inhibitor; PI: protease inhibitor; pVL: plasma HIV-1 RNA viral load; IQR: inter-quartile range; CCI: Charlson Comorbidity Index; CI: confidence interval; RR: relative risk * due to zero count   62 Table 4.3: Relative Risks for chronic disease incidence of individuals initiating treatment after HAART expansion relative to before HAART expansion with associated 95% CI (adjusted by covariates: age, sex, first regimen drug class, baseline weighted CCI, log-10 pVL and CD4 cell count)   Crude RR Adjusted RR Outcome     CVD 0.74 (0.54, 1.03) 0.77 (0.55, 1.08) COPD 0.96 (0.71, 1.30) 0.92 (0.68, 1.26) DM 1.34 (0.90, 2.00) 1.33 (0.89, 2.00) HTN 1.35 (0.98, 1.87) 1.36 (0.98, 1.90) CKD 0.68 (0.36, 1.27) 0.65 (0.34, 1.24) CLD 0.63 (0.52, 0.77) 0.67 (0.55, 0.82) RR: relative risk; HAART: highly active antiretroviral therapy; CVD: cardiovascular disease; DM: diabetes mellitus; HTN: hypertension; COPD: chronic obstructive pulmonary disease; CKD: chronic kidney disease; CLD: chronic liver disease; pVL: plasma viral load; CCI: Charlson Comorbidity Index; CI: confidence interval      63 Table 4.4: Adjusted risk rates of chronic disease incidence of all individuals actively on HAART during each time period with associated 95% CI and p-values (adjusted by covariates: age, sex, first regimen drug class, baseline weighted CCI, log-10 pVL and CD4 cell count)   Disease Incidence Risk Rate   Outcome 2000-2005 2006-2012 p-value CVD 0.93 (0.88, 0.98) 0.80 (0.76, 0.83) <.0001 COPD 0.95 (0.90, 1.01) 0.81 (0.78, 0.84) <.0001 DM 0.97 (0.91, 1.04) 0.78 (0.74, 0.82) <.0001 HTN 0.97 (0.92, 1.01) 0.81 (0.79, 0.84) <.0001 CKD* 0.92 (0.83, 1.00) 0.84 (0.78, 0.90) 0.1484 CLD 0.88 (0.84, 0.92) 0.82 (0.79, 0.84) 0.0111 HAART: highly active antiretroviral therapy; CVD: cardiovascular disease; DM: diabetes mellitus; HTN: hypertension; COPD: chronic obstructive pulmonary disease; CLD: chronic liver disease; CKD: chronic kidney disease; CCI: Charlson Comorbidity Index; CI: confidence interval *model did not include first regimen drug class due to zero cell counts   64   Figure 4.1. Adjusted incidence rates (per 1000 person year) of each chronic disease from 2000-2012 before and after the specified HAART expansion period (adjusted by covariates: age, sex, first regimen drug class, baseline weighted CCI, log-10 pVL and CD4 cell count) HAART: highly active antiretroviral therapy; CVD: cardiovascular disease; DM: diabetes mellitus; HTN: hypertension; COPD: chronic obstructive pulmonary disease; CLD: chronic liver disease; CKD: chronic kidney disease; CCI: Charlson Comorbidity Index  HAART Expansion 0 10 20 30 40 50 60 70 80 90 100 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Incidence Rate (per 1000 person years) CVD COPD DM HTN CKD CLD   65 Chapter 5: Conclusion  Summary of findings  The objective of this dissertation was to explore trends in chronic disease in an aging HIV-positive cohort during a period of time where changes to HAART access expansion policies were implemented. This was accomplished by conducting empirical studies that generally explored trends of six chronic diseases over a thirteen-year period, and evaluated the differences between post- and pre- HAART expansion periods. A summary describing the findings from each chapter is listed below.  The focus of Chapter 2 was to describe the current literature regarding HIV, aging and the role of HAART on increasing the life expectancy of PLWH. The review first described the history of HIV and how HAART shifted HIV from a once fatal infection to a now treatable chronic disease. Moreover, the review explored the current HIV and aging research, showing that aging-related complications are an emerging issue for PLWH. Finally, the review describes six diseases more commonly associated with aging, and how they may affect and relate to PLWH. In this Chapter, key features of HIV and aging are highlighted to provide context to the proceeding dissertation. In Chapters 3 and 4, two observational studies were presented that explored trends of chronic disease in an aging HIV population in BC, Canada. The purpose of each of these studies were to identify the incidence and prevalence of these diseases in a population-based cohort study and to determine if HAART access expansion policy changes had any impact on these trends.    66 Chapter 3 aimed to measure trends of incidence rates for six chronic diseases (CVD, COPD/Asthma, DM, HTN, CKD and CLD) from 2000 to 2012 in HIV-positive BC residents receiving HAART during the study period (in contrast to Chapter 4, where only individuals whom initiated HAART during the study period were included). The retrospective, population-based cohort study was based on administrative data from the COAST database. The results of the study found that only both CLD and CKD had decreasing trends; HTN had an increasing trend; and CVD and COPD/Asthma had no significant changes in trend over the thirteen-year study period. These findings highlight the need for further investigation of how these different diseases are being affected by an aging HIV population, while also identifying potential risks for diseases such as HTN. Chapter 4 employed similar methodological tools used in Chapter 3, and shifted the focus on HAART access expansion, rather than general trends over time as described in Chapter 3. In this study, only HAART naïve individuals (i.e. those who initiated HAART during the study period) were included in the analysis, whereas all patients who accessed HAART were included in the study in Chapter 3. All other inclusion and exclusion criteria were the same as the previous study, where major differences in sample size were largely due to Chapter 4 only interested in individuals who initiated triple combination ART after January 1st 2000 in contrast to the individuals in Chapter 3 who could have started ART with only one, two or three drugs in earlier time periods (i.e. those who initiated treatment after 1996). Chapter 4 aimed to measure differences of risk for incidence of six chronic diseases (same outcomes as in Chapter 3) in the post-HAART expansion period (2006-2012) relative to the pre-HAART expansion period (2000-2005). The results of this study found that there was a reduced risk for incidence of   67 CLD in the post- versus pre- HAART expansion periods for those initiating treatment, however these reductions occurred much earlier than the 2005 HAART expansion date and were likely due to other factors. We did not observe differences in the rates of CVD, HTN, DM, COPD/Asthma and CKD between the two time periods in this analysis. Despite the body of literature highlighting the enhanced risks and benefits associated with HAART on incidence of chronic comorbidities (68, 73, 156-158), in addition to the increased life expectancy of PLWH (131), our findings suggest that HAART expansion does not impact the incidence of comorbidities, in the context of an aging HIV population. This dissertation explored the patterns of chronic disease trends and the effect of HAART access expansion over a thirteen-year study period. Specifically, this dissertation explored two subgroups of PLWH in BC: 1) PLWH actively on HAART during the thirteen year period and 2) PLWH whom were HAART naïve during the thirteen year study period. The results of the former analyses showed that over time HTN incidence rates increased and CKD and CLD incidence rates decreased. The results of the latter analyses showed that in the years following the introduction of HAART (2000-2012), we observed reductions in CLD incidence and no changes for DM, HTN, CVD, COPD/asthma and CKD. Furthermore, reductions in CLD persisted in a model evaluating the impact of HAART access expansion. However, it is important to note that these reductions occurred predominantly earlier than the HAART access expansion date (mid-2000s). The two studies presented in this dissertation involved similar methodology, yet yielded quite distinct results. It is important to note that in the latter analyses, the total study population size was half the size of the former analyses due to more conservative inclusion criteria (i.e. being HAART naïve during the study period). The individuals that   68 were included in the first study and excluded from the second study would have had some exposure to ARV use in BC prior to year 2000, and exclusion of these individuals from the second study may have influenced the differing results in the two studies. Together, this dissertation provides scientific evidence that describes what chronic diseases are of highest risk for people aging with HIV—HTN in particular is of greater concern for PLWH and actively on HAART if the increasing trend projects into the future. Conversely, trends of CLD and CKD are decreasing for individuals actively on HAART since 1996, and persist for CLD in individuals initiating HAART from 2000-2012. Further understanding the causal effects of these relationships is necessary to determine strategies to care for an older HIV-positive population. Through use of administrative data in the COAST study database, this dissertation presents two empirical longitudinal cohort studies that contribute to the emerging research area of HIV and aging.   Study strengths  The strengths of each specific study are described in great detail in each respective Chapter, and common strengths of both studies are presented here. Together, these studies described population-level changes in trends of various chronic diseases in HIV-positive individuals on HAART. These studies offer empirical evidence for better understanding the risks of chronic disease incidence to the body of literature on HIV and aging. The relationship between many of these diseases and HIV are not well understood, and this current dissertation helps fill the gap in understanding how incidence rates for several of these diseases change over time.    69 Another major strength of this dissertation is the use of administrative data to address clinically-driven research questions. In this dissertation, the use of the COAST study database linked information from the BC-CFE DTP and Population Data BC to explore relationships between health care utilization data among HIV-positive individuals. Unlike prospective cohort studies, where researchers must expend time and resources collecting data, the studies presented in this dissertation were able to provide thirteen years of follow-up data on 10,000+ HIV-positive individuals on HAART. The length of the study period is made possible by retrospectively observing data, and the size of the study is based on actual population-level data collected from all HIV-positive patients in BC, Canada. The size of the sample and length of follow-up supported the use of robust analytical methods to address the research questions in this study.  Data presented in these studies were based on health records and information documented in the two major databases: BC-CFE DTP and Population Data BC, and although missing data can be considered an issue when using administrative databases, the data presented in this dissertation had very little missing data. In Chapter 3, few variables were missing data for variables HIV risk group and ethnicity (and were not included in the multivariable model), but all other variables used in the study were complete. In Chapter 4, there were no missing data for any of the variables.  Both studies included in this dissertation utilized longitudinal analytical methods to address each specific research objective. Because HIV and aging is a relatively novel research area, many of the studies currently describing risk of chronic disease in HIV-positive populations are either cross-sectional or recruited via prospective cohort studies.   70 This dissertation explores these research objectives at a population-level, which strengthens the generalizability of the study results.  Lastly, the results of this dissertation provide context to health care utilization through various chronic diseases that coincide with HAART access expansion. As described in Chapters 3 and 4, the risk of chronic diseases is not consistent for all diseases, and understanding what diseases are more common will only better prepare health care professionals and policy makers make decisions on what areas should be prioritized to better the care for people aging with HIV. Specifically, the increasing trend of HTN incidence is an important finding that could inform health care decision makers on determining what to expect from an aging HIV population. Empirical evidence from this dissertation can be used to advance the research field of HIV and aging, while also informing health care decision makers on how to prioritize a strategy that helps reduce the incidence of common diseases.   Study limitations  Considerations of limitations specific to each study are discussed in great detail in Chapters 3 and 4, and here presented are limitations common along both studies. First, as advantageous as using administrative data is, as described in the strengths section, caution should be used when interpreting these analyses. To ascertain disease incidence in this dissertation, case definitions that used information in the DAD and MSP databases were used to define disease incidence. Although these databases are mostly comprehensive and include all diagnostic information that is possibly available through health care systems, any health care information that is not documented will not be   71 captured in the administrative database. To help mitigate this issue, case definitions used multiple visit criteria to define disease incidence.  Second, the other issue with administrative databases, and with any retrospective study, was the lack of individual-level behavioural and clinical data that was available. For the studies presented in this dissertation, the outcome of interest was chronic disease incidence. In order to appropriately control for confounding, information regarding chronic disease risk factors is necessary. To address this issue, the baseline weighted CCI was used to account for disease medical history, as the best available way to control for unmeasured confounding.  Lastly, in Chapter 3 evaluating trends over the study period provided evidence for how various diseases were longitudinally affecting the HIV-positive population, however, without an appropriate control, we were unable to compare the trends to make inferences about whether HIV-positive individuals were at increased risk. In this study, the use of an HIV-negative cohort to act as a control group would be ideal to determine how trends differ between HIV-positive versus HIV-negative cohorts over time. Consequently, this study is only able to speak to the changes in trends, since the size of trends lack a comparison group.     Recommendations Recommendations specific to each study are made in Chapters 3 and 4, and in this section results from both studies together are considered to provide public health and policy-based recommendations moving forward.    72 The findings presented in this dissertation provide evidence that suggest chronic diseases—HTN specifically—are a growing concern for PLWH and actively on HAART. Chapter 2 provides context about how chronic diseases relate to HIV and specifically, how HAART has transformed the way HIV is managed in the health care setting. The findings specifically outline the impact of HAART access expansion on altering the trends of CLD, CVD, DM and HTN. Identifying changes in patterns in these diseases as a result of HAART expansion is important in determining optimal strategies to help manage people aging with HIV. Chapter 4 highlights these changes with respect to increased access to HAART in the mid 2000s, and consequently, these results could be used to inform health care decision-makers on what diseases are most affecting PLWH. Knowledge about reduced risks for CLD during this period is informative in understanding what diseases are of decreasing concern as people age with HIV. These diseases should not be ignored, but understanding that these diseases are decreasing in trend is helpful in providing context for health care providers on what HIV patients may expect as they age. Also, understanding that during the period of HAART access expansion, risks for these diseases decreased may also speak to the effectiveness of HAART in reducing non-AIDS related serious adverse events. These results are consistent with the START trial showing that early- versus deferred-HAART was effective in reducing both AIDS and non-AIDS related serious adverse events (21). Lastly, findings that showed there was no change in risk for DM, HTN, CVD, COPD/asthma and CKD in the post- versus pre-HAART expansion periods is also informative in explaining that HAART expansion did not negatively interfere with risk for these diseases. The results of this dissertation provide a descriptive understanding of   73 chronic disease incidence and risk in the era of HAART, and although these results do not provide explanations for these trends, they are useful in providing scientific empirical evidence to help guide health care policy makers as they determine strategies to better care for an aging HIV population.   Future research  This dissertation aimed to explore trends of chronic diseases in HIV-positive patients on HAART over a study period of thirteen years. The studies demonstrated that the trends of diseases and impact of HAART access expansion varied with each specific disease. While this dissertation was primarily interested in describing these trends, information regarding explanations for these trends will better inform decision making in public health policy related to HIV and aging. In this section, several directions for future research in this area are listed. The study presented in Chapter 3 evaluates the trends of chronic diseases in HIV-positive individuals on HAART over a period of thirteen years. These findings suggest that over the study period rates of several chronic diseases had changed, and whether this was due to HAART expansion or other events that may have occurred during this same time period was impossible to determine with the data available. A solution to this issue would be to replicate the study with an existing control group, with HIV-negative individuals for comparison. An HIV-negative control group would allow for comparisons of risk direction and risk size to be made in the HIV-positive group. For example, Chapter 3 showed that incidence of CLD decreased from 86 per 1,000 person years in year 2000, to 27 per 1,000 person years in 2012. A comparison of this decrease in rate to   74 a control group would be able to explain whether this change was specific to changes occurring within the HIV-positive population, or whether these changes were a result of other events that affected both HIV-positive and HIV-negative groups. In order to interpret results from such a study appropriately, it would be useful to identify an HIV-negative group—ideally, a matched sample of the general population would be the best comparison group for this study. The findings presented in Chapter 4 describe the impact of HAART access expansion by comparing individuals who initiate HAART in two distinct time periods (pre- and post-HAART expansion periods). The results showed that the risk for CLD decreased, while there was no change in risk for DM, HTN, CVD, COPD/asthma and CKD during the HAART access expansion period. To truly understand the impact of HAART, replication of this study in other regions would increase the generalizability of the study results. Demonstrating how trends of chronic diseases vary from region to region will add to the understanding of what trends are consistent among all HIV-positive populations, and might help explain areas researchers and decision-makers should focus on when considering people aging with HIV. Additionally, as a greater number of regions are adopting earlier HAART policies, it is important that considerations about what type of data may be important to answer questions regarding chronic disease risk. This study is unique because it explores a period of time where a change in policy occurred, allowing for comparisons before and after. Moving forward, prospective studies in regions that have not yet adopted HAART access expansion policies would be useful in determining the potential benefits of HAART on reducing incidence of chronic diseases.   75 Gathering information about chronic disease risk factors would provide adequate control for confounding that was not available in the current study. HIV and aging in the context of HAART is a growing area of research. Many of the issues and complications typically associated with aging have never been a priority for PLWH, and because HIV contributes to accelerated aging, these issues will become more readily apparent. As the life expectancy of HIV-positive people increases, the responsibility to determine optimal strategies for caring for these patients are of greater concern. Research that focuses on understanding the relationship between these diseases and HIV should shape the way decisions are made that involve people aging with HIV. 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Aging health. 2008;4(6):615-27.      93 Appendix  Appendix 1.1 List of Comorbidities, Case Definitions and ICD Codes Condition Disease Case definition ICD Codes COPD/Asthma COPD 1 hospitalization with a COPD diagnostic code   OR  2 medical visits during which the patient was aged 45 or older occurring within 365 days each with a COPD diagnostic code ICD-9: 491 Chronic bronchitis 492 Emphysema 496 Chronic airways obstruction, not elsewhere classified  ICD-10: J41 Simple and mucopurulent chronic bronchitis J42 Unspecified chronic bronchitis J43 Emphysema J44 Other chronic obstructive pulmonary disease ASTHMA 1 hospitalization with an asthma diagnostic code   OR   2 medical visits each with an asthma diagnostic code within 365 days ICD-9: 493 Asthma  ICD-10: J45 Asthma J46 Status asthmaticus DM DM 1 hospitalization with a diabetes diagnostic code   OR  2 medical visits in 365 days each with a diabetes diagnostic code ICD-9: 250 Diabetes Mellitus  ICD-10: E10 Insulin-dependent diabetes mellitus E11 Non-insulin-dependent diabetes mellitus E12 Malnutrition-related diabetes mellitus E13 Other specified diabetes mellitus E14 Unspecified diabetes mellitus HTN HTN 1 hospitalization with a hypertension diagnostic code   OR  2 medical visits during which the patient was aged 20 or older occurring within 365 days each ICD-9: 401 Essential hypertension 402 Hypertensive heart disease 403 Hypertensive renal disease 404 Hypertensive heart and renal disease 405 Secondary hypertension  ICD-10: I10 Essential (primary) hypertension I11 Hypertensive heart disease I12 Hypertensive renal disease I13 Hypertensive heart and renal disease I15 Secondary hypertension   94 Condition Disease Case definition ICD Codes with a hypertension diagnostic code. CVD AMI 1 hospitalization with an acute myocardial infarction diagnostic code. ICD-9: 410 Acute myocardial infarction  ICD-10: I21 Acute myocardial Infarction  CHF 1 hospitalization with a CHF diagnostic code   OR   2 medical visits each with a CHF diagnostic code within 365 days. ICD-9:  428 Heart Failure  ICD-10:  I50 Heart Failure IHD 1 hospitalization with a IHD diagnostic code   OR  2 medical visits each with a IHD diagnostic code within 365 days. ICD-9: 410 Acute Myocardial Infarction 411 Other Acute and Subacute Forms of Ischaemic Heart Disease 412 Old Myocardial Infarction 413 Angina Pectoris 414 Other Forms of Chronic Ischaemic Heart Disease 414.0 Coronary Atherosclerosis 414.1 Aneurysm of Heart 414.8 Other 414.9 Unspecified 428 Heart Failure   ICD-10: I20 Angina pectoris I21 ST elevation (STEMI) and non-ST elevation (NSTEMI) myocardial infarction I22 Subsequent ST elevation (STEMI) and non-ST elevation (NSTEMI) myocardial infarction I23 Certain current complications following ST elevation (STEMI) and non-ST elevation (NSTEMI) myocardial infarction (within the 28 day period) I24 Other acute ischemic heart diseases   95 Condition Disease Case definition ICD Codes I25 Chronic ischemic heart disease I50 Heart Failure CVA/TIA 1 hospitalization with a CVA/TIA diagnostic code   OR   2 medical visits each with a CVA/TIA diagnostic code within 365 days. ICD-9: 430 Subarachnoid Haemorrhage 431 Intracerebral Haemorrhage 434 Occlusion Of Cerebral Arteries 435 Transient Cerebral Ischaemia 436 Acute But Ill-Defined Cerebrovascular Disease 362.3 Retinal Vascular Occlusion  ICD-10: I60.x Nontraumatic subarachnoid hemorrhage I61.x Nontraumatic intracerebral hemorrhage I63.x (excluding I63.6 cerebral infarction due to central venous thrombosis) Cerebral infarction I64 Stroke, not specified as haemorrhage or infarction H34.1 Central retinal artery occlusion G45.x (excluding G45.4 transient global amnesia) Transient cerebral ischemic attacks and related syndromes H34.0 Transient retinal artery occlusion   96 Condition Disease Case definition ICD Codes CVS 1 hospitalization with a CVS diagnostic code   OR  2 medical visits each with a CVS diagnostic code within 365 days. ICD-9: 430 Subarachnoid hemorrhage 431 Intracerebral hemorrhage 433 Occlusion of pre-cerebral or cerebral arteries 434 Occlusion/stenosis of pre-cerebral or cerebral arteries 435 Transient cerebral ischemia 436 Acute cerebral ischemia 438 Late effects (hemiplegia etc)  ICD-10: I60 Nontraumatic subarachnoid hemorrhage I61 Nontraumatic intracerebral hemorrhage  I63 Cerebral infarction I66 Occlusion and stenosis of cerebral arteries, not resulting in cerebral infarction G45 Transient cerebral ischemic attacks and related syndromes G46 Vascular syndromes of brain in cerebrovascular diseases I69 Sequelae of cerebrovascular disease Renal Disease CKD 1 hospitalization with a CKD diagnostic code   OR  2 medical visits each with a CKD diagnostic code within 365 days  ICD-9: 581 Nephrotic Syndrome 582 Chronic glomerulonephritis 583 Nephritis and nephropathy, not specified as acute or chronic 585 Chronic Renal Failure 588 Disorders Resulting From Impaired Renal Function 593.71 Vesicoureteral Reflux With Reflux Nephropathy, Unilateral 593.72 Vesicoureteral Reflux With Reflux Nephropathy, Bilateral 593.73 Vesicoureteral Reflux With Reflux Nephropathy NOS 593.9 Unspecified Disorder FO Kidney And Ureter 403 Hypertensive Chronic Kidney Disease 405.01 Secondary Hypertension, Malignant, Renovascular 405.11 Secondary Hypertension, Benign, Renovascular 405.91 Secondary Hypertension, Unspecified, Renovascular 404 Hypertensive Heart And Chronic Kidney Disease 250.41 Diabetes With Renal Manifestations, Type I, Not Stated As Controlled 250.43 Diabetes With Renal Manifestations, Type I, Uncontrolled 250.40 Diabetes With Renal Manifestations, Type II Or Unspecified Type, Not Stated As Controlled 250.42 Diabetes With Renal Manifestations, Type II Or Unspecified Type, Uncontrolled   97 Condition Disease Case definition ICD Codes  ICD-10: N02.2 Recurrent and persistent hematuria with diffuse membranous glomerulonephritis N03 Chronic glomerulonephritis N04 Nephrotic syndrome N05 Unspecified nephritic syndrome N08 Glomerular disorders in diseases classified elsewhere N18 Chronic kidney disease  N25 Disorders resulting from impaired renal function N13.721 Vesicoureteral-reflux with reflux nephropathy without hydroureter unilateral N13.722 Vesicoureteral-reflux with reflux nephropathy without hydroureter bilateral N13.729 Vesicoureteral-reflux with reflux nephropathy without hydroureter unspecified I12 Hypertensive chronic kidney disease I13 Hypertensive heart and chronic kidney disease E10.29 Type 1 diabetes mellitus with other diabetic kidney complication E10.21 Type 1 diabetes mellitus with diabetic nephropathy E11.29 Type 2 diabetes mellitus with other diabetic kidney complication E11.21 Type 2 diabetes mellitus with diabetic nephropathy I15.0 Renovascular hypertension ESRD 1 hospital admission with a ESRD diagnosis code   OR   A kidney transplant code (any occurrence of the code in the DAD)   OR  1 medical visit with ESRD diagnosis code  OR  (MSP fee codes) 9 or more medical claims with any ICD-9: 585.6 End stage renal disease 792.5 Cloudy (hemodialysis) (peritoneal) dialysis effluent V45.1 Renal dialysis status V56 Encounter for dialysis and dialysis catheter care V56.0 Extracorporeal dialysis V56.1 Fitting and adjustment of extracorporeal dialysis catheter V56.2 Fitting and adjustment of peritoneal dialysis catheter V56.3 Encounter for adequacy testing for dialysis V56.31 Encounter for adequacy testing for hemodialysis V56.32 Encounter for adequacy testing for peritoneal dialysis V56.8 Other dialysis V42.0 Organ or tissue replaced by transplant Kidney  ICD-10: N18.6 End stage renal disease R88.0 Cloudy (hemodialysis) (peritoneal) dialysis effluent   98 Condition Disease Case definition ICD Codes combination of dialysis diagnostic codes within 90 days Z99.2 Dependence on renal dialysis Z91.15 Patient's noncompliance with renal dialysis Z49 Encounter for care involving renal dialysis Z49.31 Encounter for adequacy testing for hemodialysis Z49.01 Encounter for fitting and adjustment of extracorporeal dialysis catheter Z49.02 Encounter for fitting and adjustment of peritoneal dialysis catheter Z49.3 Encounter for adequacy testing for dialysis Z49.31 Encounter for adequacy testing for hemodialysis Z49.32 Encounter for adequacy testing for peritoneal dialysis Z49.32 Encounter for adequacy testing for peritoneal dialysis Z94.0 Kidney transplant status  Fee Codes: 308 Continuing care by consultant: Subsequent hospital visit 323 Dialysis peritoneal 350 Dialysis acute renal, hemodialysis 351 Dialysis blood, repeat 352 Dialysis vein dissection 355 Dialysis acute renal failure, peritoneal  356 Peritoneal dialysis subsequent 358 Dialysis chronic renal (hemodialysis)  359 Dialysis peritoneal 361 Dialysis home supervision 390 Care of renal transplant patient  33708 Visit-hospital-nephrology 33723 Dialysis peritoneal 33750 Dialysis acute renal, hemodialysis  33751 Dialysis acute renal, hemodialysis-repeat  33752 Dialysis vein dissection 33755 Dialysis acute renal failure, peritoneal  33756 Dialysis-reinsertion of peritoneal catheter  33758 Dialysis chronic renal hemodialysis  33759 Dialysis-chronic renal-peritoneal 33761 Dialysis home supervision 33790 Renal transplant patient-care   99 Condition Disease Case definition ICD Codes Liver Disease CLD 1 hospitalization with a CLD diagnostic code   OR  1 medical visit with a CLD diagnostic code ICD-9: 571.0 Alcoholic Fatty Liver 571.2 Alcoholic Cirrhosis Of Liver 571.3 Alcoholic Liver Damage, Unspecified 571.4 Chronic Hepatitis 571.5 Cirrhosis Of Liver Without Mention Of Alcohol 571.6 Biliary Cirrhosis 571.8 Other Chronic Nonalcoholic Liver Disease 571.9 Unspecified Chronic Liver Disease Without Mention Of Alcohol 070.3 Viral hepatitis B without mention of hepatic coma 070.30 Viral hepatitis B without mention of hepatic coma, acute or unspecified, without mention of hepatitis delta 070.31 Viral hepatitis B without mention of hepatic coma, acute or unspecified, with hepatitis delta 070.32 Viral hepatitis B without mention of hepatic coma, chronic, without mention of hepatitis delta 070.33 Viral hepatitis B without mention of hepatic coma, chronic, with hepatitis delta 070.52 Hepatitis delta without mention of active Hepatitis B disease or hepatic coma V02.61 Hepatitis B carrier 070.2 Viral hepatitis B with hepatic coma 070.20 Viral hepatitis B with hepatic coma, acute or unspecified, without mention of hepatitis delta 070.21 Viral hepatitis B with hepatic coma, acute or unspecified, with hepatitis delta 070.22 Viral hepatitis B with hepatic coma, chronic, without mention of hepatitis delta 070.23 Viral hepatitis B with hepatic coma, chronic, with hepatitis delta 070.42 Hepatitis delta without mention of active Hepatitis B disease with hepatic coma 070.54 Chronic hepatitis C without mention of  hepatic coma V02.6 Carrier or suspected carrier of viral hepatitis V02.62 Hepatitis C carrier 070.44 Chronic hepatitis C with hepatic coma  ICD-10: K70.0 Alcoholic fatty liver K70.10 Alcoholic hepatitis without ascites K70.30 Alcoholic cirrhosis of liver without ascites K70.9 Alcoholic liver disease unspecified K73.9 Chronic hepatitis unspecified K73.0 Chronic persistent hepatitis not elsewhere classified K75.4 Autoimmune hepatitis K73.2 Chronic active hepatitis not elsewhere   100 Condition Disease Case definition ICD Codes classified K73.8 Other chronic hepatitis not elsewhere classified K74.0 Hepatic fibrosis K74.60 Unspecified cirrhosis of liver K74.69 Other cirrhosis of liver K76.0 Fatty (change of) liver not elsewhere classified K76.89 Other specified diseases of liver K74.1 Hepatic sclerosis K76.9 Liver disease unspecified B19.10 Viral hepatitis b without mention of hepatic coma B19.10 Unspecified viral hepatitis B without hepatic coma B18.1 Chronic viral hepatitis B without delta-agent B18.0 Chronic viral hepatitis B with delta-agent Z22.51 Carrier of viral hepatitis B B19.11 Viral hepatitis b with hepatic coma B19.11 Unspecified viral hepatitis B with hepatic coma B18.1 Chronic viral hepatitis B without delta-agent B18.0 Chronic viral hepatitis B with delta-agent B18.2 Chronic viral hepatitis C Z22.52 Carrier of viral hepatitis C B18.2 Chronic viral hepatitis C ESLD/ Cirrhosis 1 hospitization with a diagnostic code  OR   2 medical visits each with a diagnostic code for ascites, spontaneous bacterial peritonitis, or variceal hemorrhage within 365 days. ICD-9: 789.5 Ascites 572.2 Hepatic encephalopathy 572.3 Portal hypertension 572.4 Hepatorenal syndrome 572.8 Other sequelae of chronic liver disease 567 Peritonitis in infectious diseases classified elsewhere 456 Esophageal varices with bleeding 070 Viral hepatitis A with hepatic coma 155 Hepatocellular carcinoma 570 Acute and subacute necrosis of liver 571.2 Alcoholic cirrhosis of liver 571.5 Cirrhosis of liver no alcohol 571.6 Biliary cirrhosis 571.8 Other chronic non?alcoholic liver disease 571.9 Unspecified chronic liver disease without mention of alcohol 782.4 Jaundice  ICD-10: R18.0 Malignant ascites R18.8 Other ascites K76.6 Portal hypertension K65 Peritonitis and retroperitoneal infections I86.4 Gastric varicies I85 Esophageal varices K72.90 Hepatic failure, unspecified without coma   101 Condition Disease Case definition ICD Codes K72.91 Hepatic failure, unspecified with coma B19 Viral hepatitis B18.1 Chronic viral hepatitis B without delta-agent B18.0 Chronic viral hepatitis B with delta-agent B18.2 Chronic viral hepatitis C C22.0 Liver cell carcinoma C22.2 Hepatoblastoma C22.7 Other specified carcinomas of liver C22.8 Malignant neoplasm of liver, primary, unspecified as to type C22.1 Intrahepatic bile duct carcinoma C22.9 Malignant neoplasm of liver, not specified as primary or secondary K76.2 Central hemorrhagic necrosis of liver K70.30 Alcoholic cirrhosis of liver without ascites K74.0 Hepatic fibrosis K74.60 Unspecified cirrhosis of liver K74.69 Other cirrhosis of liver K74.3 Primary biliary cirrhosis K74.4 Secondary biliary cirrhosis K74.5 Biliary cirrhosis, unspecified K76.0 Fatty (change of) liver, not elsewhere classified K76.89 Other specified diseases of liver K74.1 Hepatic sclerosis K76.9 Liver disease, unspecified K76.7 Hepatorenal syndrome K72.10 Chronic hepatic failure without coma K72.90 Hepatic failure, unspecified without coma R17 Unspecified jaundice  

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