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Physical determinants of physical activity in children who have completed treatment for acute lymphoblastic… Hung, Stanley Hughwa 2014

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PHYSICAL DETERMINANTS OF PHYSICAL ACTIVITY IN CHILDREN WHO HAVE COMPLETED TREATMENT FOR ACUTE LYMPHOBLASTIC LEUKEMIA   by Stanley Hughwa Hung  B.P.H.E., University of Toronto, 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 (Rehabilitation Sciences)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)   August 2014  © Stanley Hughwa Hung, 2014 ii  Abstract INTRODUCTION: Physical activity (PA) levels in children who have completed treatment for acute lymphoblastic leukemia (ALL) have been shown to be lower than their healthy peers. Obesity and related health concerns have been recognized as long-term side-effect of cancer treatment. Motor performance and physical function have been shown to be lower in these children compared with children who have not had a cancer diagnosis. Whether or not these two physical factors are related to PA levels in these children is unknown. PURPOSE: To determine if motor performance and physical function are associated with PA in children who have completed treatment for ALL. METHODS: PA was measured using the Physical Activity Questionnaire for Older Children (PAQ-C); motor performance was measured using the Bruininks-Oseretsky Test of Motor Proficiency, Second Edition, Short Form (BOT-2 SF); and physical function was measured using the Six-Minute Walk Test (6MWT). RESULTS: Thirteen participants were recruited. PAQ-C scores were not related to standardized scores from the BOT-2 SF (Spearman’s rho, rs = 0.282, p = 0.35) and 6-minute walk distance (6MWD) (rs = -0.429, p = 0.14) and 6MWD Standard Deviation Score (SDS) (rs = -0.094, p = 0.76). Only 1/13 participants performed below average in the BOT-2 SF, and 11/13 participants walked shorter distances compared with published data from healthy children in the 6MWT (mean 6MWD SDS: -1.62). Body mass index SDS were significantly associated with measured 6MWD (rs = 0.602, p = 0.03) and 6MWD SDS (rs = -0.691 p = 0.01). CONCLUSION: PA was not associated with motor performance or physical function. Physical function was poorer compared with healthy children in 11/13 participants. Healthcare professionals can focus on improving physical function and improving weight management to help reduce risk of obesity and associated health consequences in children who have completed treatment for ALL. Future research should iii  include a larger sample size and include psychosocial factors, such as self-efficacy and parental influence, in exploring factors related to PA childhood ALL survivors.   iv  Preface This thesis contains the work of a research study conducted by the candidate, Stanley H. Hung, under the supervision of Dr. Kristin L. Campbell with guidance from Anne Rankin, and Drs. Mark Beauchamp and Naznin Virji-Babul from the University of British Columbia, Vancouver, as well as Angela Pretula, Marion Nelson, and Drs. Sheila Pritchard and Christopher Fryer from the British Columbia Children’s Hospital. The study design, data collection and analysis, and writing of the manuscript were primarily the work of the candidate.  Sections of this thesis will be submitted for publication as manuscript in peer reviewed journals.  Ethical approval for this research study was provided by the Children’s and Women’s Research Ethics Board (H13 - 01823). v  Table of Contents Abstract .......................................................................................................................................... ii Preface ........................................................................................................................................... iv Table of Contents ...........................................................................................................................v List of Tables ................................................................................................................................ ix List of Figures .................................................................................................................................x List of Abbreviations ................................................................................................................... xi Acknowledgements ..................................................................................................................... xii Dedication ................................................................................................................................... xiv Chapter 1: Literature Review .......................................................................................................1 1.1 Introduction ..................................................................................................................... 1 1.2 ALL Biology and Epidemiology .................................................................................... 2 1.2.1 Physical Late Effects of Chemotherapy ...................................................................... 4 1.3 Physical Effects of Treatment on ALL Patients ............................................................. 4 1.3.1 Motor Performance ..................................................................................................... 5 1.3.2 Physical Function ........................................................................................................ 8 1.4 PA in ALL Patients and Survivors.................................................................................. 9 1.4.1 Potential Reasons for Reduced PA in ALL Patients and Survivors ......................... 11 1.5 Impact of Time During Treatment and Time After Treatment ..................................... 12 1.6 The Relationship between Late Effects and PA ........................................................... 14 1.6.1 Physiological Factors Associated with PA in ALL Survivors .................................. 14 1.6.2 Psychological Factors Associated with PA in ALL Survivors ................................. 17 1.7 The Importance of PA in Childhood Cancer Survivors ................................................ 19 vi  1.8 PA and Exercise is Safe for Childhood Cancer Patients and Survivors ....................... 19 Chapter 2: Research Study .........................................................................................................21 2.1 Introduction ................................................................................................................... 21 2.2 Purpose .......................................................................................................................... 22 2.3 Objectives and Hypothesis ............................................................................................ 22 2.4 Methods......................................................................................................................... 22 2.4.1 Ethical Approval ....................................................................................................... 22 2.4.2 Participants ................................................................................................................ 22 2.4.2.1 Population ......................................................................................................... 22 2.4.2.2 Recruitment ....................................................................................................... 23 2.4.2.3 Sample Size ....................................................................................................... 24 2.5 Procedures ..................................................................................................................... 24 2.5.1 Demographics Data ................................................................................................... 25 2.5.2 Outcome Measures.................................................................................................... 26 2.5.2.1 Questionnaires................................................................................................... 26 2.5.2.1.1 Physical Activity Questionnaire for Older Children (PAQ-C) ................... 26 2.5.2.1.2 PedsQL™ – Multidimensional Fatigue Scale ............................................. 26 2.5.2.2 Physical Assessments........................................................................................ 27 2.5.2.2.1 Bruininks-Oseretsky Test of Motor Proficiency, Second Edition – Short Form (BOT-2 SF) ......................................................................................................... 27 2.5.2.2.2 Six Minute Walk Test (6MWT) .................................................................. 29 2.5.3 Statistical Analysis .................................................................................................... 30 2.6 Results ........................................................................................................................... 31 vii  2.6.1 Participants ................................................................................................................ 31 2.6.2 Outcomes Measures .................................................................................................. 32 2.6.3 Relationship of PA with Motor Performance and Physical Function ....................... 33 2.6.4 Impact of Body Mass Index ...................................................................................... 33 2.6.5 Impact of ALL Risk Level ........................................................................................ 34 2.6.6 Impact of Anthracycline Dosage and Cardiotoxicity Risk Category ........................ 34 2.6.7 Impact of Time from Treatment Completion ............................................................ 35 Chapter 3: Conclusion .................................................................................................................42 3.1 Primary Objective and Hypothesis ............................................................................... 42 3.2 Effect of BMI on Outcome Measures ........................................................................... 42 3.3 Relationship of PA with Motor Performance and Physical Performance..................... 43 3.4 Comparison of Outcome Measures with Published and Normative Data .................... 44 3.4.1 Physical Activity ....................................................................................................... 44 3.4.2 Motor Performance ................................................................................................... 45 3.4.3 Physical Function ...................................................................................................... 47 3.5 Fatigue........................................................................................................................... 48 3.6 Study Strengths ............................................................................................................. 49 3.7 Study Limitations .......................................................................................................... 50 3.8 Future Studies ............................................................................................................... 53 3.9 Implications of Study Results ....................................................................................... 55 3.10 Conclusion .................................................................................................................... 57 Bibliography .................................................................................................................................59 Appendices ....................................................................................................................................75 viii  Appendix A - Letter of Invitation  ............................................................................................ 75 Appendix B - Parent Consent Form .......................................................................................... 76 Appendix C - Child Assent Form ............................................................................................. 83 Appendix D - Medical Data Collection Form........................................................................... 85 Appendix E - Physical Assessment Data Collection Form ....................................................... 86 Appendix F - End of Study Letter to Participants .................................................................... 87 Appendix G - Parking Reimbursement Form ........................................................................... 89  ix  List of Tables Table 1 - Summary of Outcome Measures and Time to Administer ............................................ 30 Table 2 - Participant Characteristics ............................................................................................. 36 Table 3 – Summary of Outcome Measures................................................................................... 37 Table 4 – Means and Mann-Whitney U Test statistics in Outcome Measures between Healthy Weight and Overweight/Obese Children ...................................................................................... 38 Table 5 – Means and Mann-Whitney U Test Statistics for Outcome Measures between ALL Risk Level Groups ................................................................................................................................. 38 Table 6 - Means and Mann-Whitney U Test Statistics for Outcome Measures between Anthracycline Cardiotoxicity Risk Groups ................................................................................... 39  x  List of Figures Figure 1 - Scatter Plot of PAQ-C Scores and BOT-2 SF Standardized Scores ............................ 40 Figure 2 - Scatter Plot of PAQ-C Scores and 6MWD SDS .......................................................... 41  xi  List of Abbreviations 6MWD Six Minute Walk Distance 6MWT Six Minute Walk Test ALL Acute Lymphoblastic Leukemia  ATS American Thoracic Society BCCH British Columbia Children’s Hospital BMI Body Mass Index BOT-2 SF Bruininks-Oseretsky Test of Motor Proficiency, 2nd Edition, Short Form BOTMP Bruininks-Oseretsky Test of Motor Proficiency, 1st Edition CF Cognitive Fatigue DMT Deutscher Motorik-Test GF General Fatigue GLTEQ Godin Leisure time Exercise Questionnaire HW Healthy Weight LTFU Long-Term Follow-Up clinic MOT Motoriktest  OWO Overweight and Obese PAQ-C Physical Activity Questionnaire for Older Children SDS Standard Deviation Score  SRF Sleep/Rest Fatigue U Mann-Whitney U Statistic xii  Acknowledgements First and foremost, I would like to acknowledge and thank my supervisor, Dr. Kristin Campbell, for her guidance, encouragement, and support throughout my studies over the last two years. She has given me countless opportunities and experiences to help enrich my interest and passion for exercise and cancer research, as well as preparing me for my future endeavours in the medical field. To my committee member Dr. Naznin Virji-Babul, thank you for your input and guidance on this project through your expertise in research with children and motor performance. To Dr. Mark Beauchamp, thank you for your input and guidance through your expertise in physical activity measurement in children, and enhancing my understanding of psychosocial factors associated with physical activity in children. To Anne Rankin, thank you for your input, time, and expertise in helping me design the protocol for the study, helping me organize and arrange the space and equipment for data collection at the British Columbia Children’s Hospital, sharing with me your experiences and inspiring me with your passion for rehabilitation in pediatric oncology patients.  I would like to acknowledge and thank individuals at the British Columbia Children’s Hospital. To Dr. Christopher Fryer, Dr. Sheila Pritchard, Marion Nelson, and Angela Pretula for sharing their expertise and passion for pediatric oncology and physical activity, and helping with study recruitment, data collection, and sharing the oncology Long-Term Follow-Up clinic space. Special thanks to Dr. Fryer for allowing me to observe him as he counselled patients at the follow-up clinic, and to Dr. Pritchard for her guidance and expertise in her role as the Clinical Principal Investigator for this study. To Colleen Fitzgerald, Ruth Milner, the oncologists, and administrative staff at the Oncology, Hematology, and Bone Marrow Transplant Program and xiii  Research Oversight Committee for their assistance and guidance throughout the ethics review and approval process. To Susan Harkins for helping us schedule the examination room for data collection, Maria Juricic for helping to supervise data collection, and to Patricia Mortenson and her family for helping us with data collection training.   To my fellow graduate students and lab mates, Sarah Neil, Amy Kirkham, Negin Niksirat, and Bolette Skjødt Rafn, thank you all for your help, advice and guidance throughout the two years of my project.  Thank you Tiffany Moore for helping me coordinate the initial planning stages of data collection, helping with study recruitment, and your guidance throughout my thesis.  Finally, I would like to thank all the parents and children who volunteered their time and energy to participate in this study. Thank you for sharing your experiences with me during our study sessions, and furthering my interest and passion for exercise and cancer research.    xiv  Dedication I would like to dedicate this thesis to my parents, Kenny and Ivy Hung, my older brother, Delbert Hung, and to the rest of my dearest family. Without you, my wonderful experience as a graduate student at the University of British Columbia would not have been possible. Thank you for your emotional support and inspiration throughout my life.1  Chapter 1: Literature Review 1.1 Introduction Acute lymphoblastic leukemia (ALL) is currently the most common childhood malignancy accounting for more than 25% of all childhood cancers1. With recent advances in treatment approaches, children diagnosed with ALL have significantly improved 5-year survival rates, which are currently above 85% in developed countries2, and 94% in Canada3.  As a result, research has now become more focused on treatment side effects. Potential late effects of therapeutic interventions for childhood cancers of any diagnosis include altered cardiovascular, pulmonary, liver, renal, bladder, endocrine, musculoskeletal, neurocognitive and nervous system function4.  Specific to children with ALL, impaired physical performance measures have been documented  in this population, including lower peak oxygen consumption5,6, reduced motor performance and physical function7, reduced quality of life, and reduced self-perception of adequacy and predilection for physical activity8.  Physical activity (PA) levels in children who are undergoing treatment or who have completed treatment for ALL, as well as adult long-term survivors of ALL, have been shown to be lower compared to their healthy counterparts9. However, the factors influencing PA levels are unclear9,10.  Both physical and psychosocial factors have been acknowledged as potential mechanisms for lowered PA levels11.  Few studies have investigated the physical factors related to PA levels in children who have completed treatment for ALL7,12-14.  The importance of understanding PA patterns in this population is due to the well-established benefits of PA in healthy children15.  A higher risk of obesity, diabetes mellitus, and cardiovascular disease are now recognized as potential late effects of treatment for ALL in children16,17, which may be linked to the lower levels of PA in this population.  This study aims to investigate two physical 2  factors potentially affecting PA levels in children who have completed treatment for ALL, specifically motor performance and physical function. 1.2 ALL Biology and Epidemiology According to the Canadian Cancer Society in 2014 for children diagnoses between the age of 0 – 14, leukemia accounted for 32% of the 4,600 new cases of childhood cancers reported from 2006 – 2010, 26% of the 640 deaths reported from 2005 – 2009, and had a 5-year observed survival proportion of 91% from 2004 – 20083. The remainder of this thesis will refer to patients who have completed primary treatment for ALL without recurrence as cancer survivors. ALL is characterized by an abnormal accumulation of malignant immature white blood cells (lymphoblast) in the bone marrow18. These abnormal lymphoblasts fail to differentiate into mature cells, preventing healthy development of healthy erythrocytes, lymphocytes and platelets, and ultimately leading to anemia and susceptibility to infection19.  In general, ALL can be classified as B-Lineage and T-Lineage. B-Lineage is a malignancy involving lymphoblasts committed to the B-cell lineage, while T-Lineage refers to lymphoblasts committed to the T-cell lineage. B-lineage ALL is generally associated with 85% survival, while T-lineage ALL is generally considered the more aggressive, high-risk disease but accounts for 15% of ALL cases in children18.  Subtypes of ALL can be further classified based on genetic characteristics to help profile a child’s susceptibility to developing ALL, their prognosis and response to treatment, disease severity, and their likelihood of relapse or recurrence20,21. These genetic profiles are often related to a patient’s abnormal immunological response to infection. The understanding of these genetic profiles is evolving and remains highly debated. However, this has led to the development of two hypotheses in explaining the etiology of ALL. 3  The first hypothesis is the Kinlen Population Mixing Hypothesis22 and suggests leukemia is a result of an influx in large numbers of people moving and mixing to create rare incidences of abnormal responses to specific viral infections. The second hypothesis is the Greaves Delayed Infection Hypothesis23, stating that children who have had an under stimulated immune system during childhood development will display an over-response to common infections later in childhood, and subsequently induce leukemia in children with genetic mutations making them susceptible to leukemia. Epidemiological evidence has also suggested that electromagnetic radiation may be related to a slightly increased risk of ALL, though the reliability of this data remains uncertain24. Upon diagnosis, ALL patients are typically started on a two to two-and-a-half year chemotherapy treatment plan comprising of four therapy phases: induction of remission, consolidation, delayed intensification, and maintenance therapy20. Induction of remission therapy phase is generally four to six weeks with the goal of eliminating all initial leukemic cells and restoring normal blood cell production, allowing the patient to be in a remission, cancer-free, status. Chemotherapy during this phase of treatment generally includes using glucocorticoids, vincristine, and asparaginase, and potentially involving the use of anthracyclines. The consolidation and delayed intensification therapy phases together are approximately 20 – 30 weeks of chemotherapy to help eliminate residual leukemic cells, and generally includes high doses of methotrexate and mercaptopurine with pulses of vincristine and glucocorticoids. Finally, the maintenance therapy phase lasts approximately two or more years and aims to keep the patient in remission and prevent relapse.  This phase mainly uses mercaptopurine, methotrexate, with or without pulse of vincristine and dexamethasone. Each of the drugs used during the course of chemotherapy are associated with potential adverse late effects.  4  1.2.1 Physical Late Effects of Chemotherapy With improvements in survival rate, research has increasingly been focused on the adverse effects of chemotherapy in those who have been diagnosed with childhood ALL and have completed primary adjuvant treatment. Anthracyclines, glucocorticoids, and vincristine are common agents used to treat children with ALL, and each has been reported to have adverse late effects. Exposure to anthracyclines during ALL treatment has been associated with cardiotoxic effects, which can potentially result in cardiomyopathy and congestive heart failure, both of which may be irreversible, and manifests as reduced left ventricular mass and thickness, and depressed left ventricular contractility in long-term survivors of childhood cancers25. Corticosteroids, such as dexamethasone, have been associated chronic fatigue26 and osteonecrosis, the general term used to describe cell death of segments of cortical bone tissue27. Vincristine, an alkaloid agent used in chemotherapy regimens to treat many types of cancers, has been associated with peripheral neuropathy in children treated for ALL28. 1.3 Physical Effects of Treatment on ALL Patients San Juan et al.4 have reported on the potential late effects of therapeutic interventions for childhood cancers of any diagnosis, specifically cardiovascular, pulmonary, liver, renal, bladder, endocrine, musculoskeletal, neurocognitive and nervous system function. Specific to ALL, observational studies investigating the post-treatment effects for children with ALL have found lower peak oxygen consumption compared to controls5,6,29,30; reduced muscle strength and mobility as measured by the Timed Up and Go and 2-minute walk test31; lower self-perception of adequacy and predilection for PA than healthy controls8; and lower overall quality of life compared with healthy controls6,8. Since the outcome measures of the current thesis focuses on 5  motor performance and physical function in childhood ALL survivors, we will focus on reviewing studies who have investigated these outcomes. 1.3.1 Motor Performance Previous studies investigating the motor performance in childhood cancer patients have found mixed results. Green et al.32 conducted a systematic review and found 28 peer-reviewed studies investigating motor performance in children diagnosed with ALL, both during and following treatment. Articles were included if studies assessed motor performance in children who were 0 – 18 years old, have been or were being treated with chemotherapy without radiation, used standardized motor measurement tools, and included a sample of greater than 10 participants who were diagnosed with ALL. Motor performance was categorized as gross and fine motor performance, where gross motor performance included measurement tools testing muscle strength, maintaining balance, ball skills, and agility, and fine motor performance included measurement tools testing manual dexterity, handwriting, and drawing skills.  Their review included seven studies that assessed gross motor performance; two during treatment33,34, four studies after treatment 29,35-37, and one both before and after treatment38. Three studies were longitudinal33,34,38 and four were cross-sectional 29,35-37. The age for the children in these studies ranged between 5.3 – 15.5 years and the time after treatment range of 0 – 7.4 years. The most frequently used motor performance measurement tool was the Movement Assessment Battery in Children (MABC), which was used by five studies. One study used the Bruininks-Oseretsky Test of Motor Performance, 2nd Edition (BOT-2).  Specific to gross motor performance, two studies found gross motor impairments in children at diagnosis34,38. In the four off-treatment cross-sectional studies, gross or general motor 6  impairment was noted in 25 – 54% of patients using the MABC29,35,36, while one study37 found 2/37 patients performed below average on the BOT-2. Fine motor skills were assessed by 15 studies. The common measurement tools were the Purdue Pegboard task (five studies), the MABC (four studies), Finger Tapping task (four studies), and writing tasks (two studies).  Participants were children within the age range of 3.1 – 17.7 years at the time of assessment and 0 – 10 years since the time of treatment. Six studies examined fine motor skills after treatment29,35,39-42, five during treatment33,34,42-44, and four both before and after45-48. In studies during treatment, two studies found reduced manual dexterity scores34,46, and one study showed greater handwriting difficulties in terms of slower drawing speed, longer pause duration, and greater pen pressure compared with controls34. Inconsistent data for fine motor skills after diagnosis were found in five studies; three studies showed increasing fine motor performance issues after treatment 34,45,47; and two studies39,40 showed no significant difference in fine motor skills (dexterity scores and writing speed and quality) approximately four years after treatment compared to controls.  Recent studies in children with ALL that were not included in the systematic review by Green et al.32 reported similar findings in motor performance. Hartman et al.7 studied motor performance using the MABC-2 in 34 children treated for ALL (average age of 12.3 years) and measured motor performance at the end of treatment and at a follow-up session at least five years after treatment (mean of 5.2 years). Twenty-six children completed the motor performance tests at both time points; 58% of children achieved normal scores for both time points; 38% were “at risk for impairment” at end of treatment, but achieved normal scores at follow-up; and 4% (one participant) were “at risk” at both time points.  7  Leone et al.49 assessed the gross motor skills of 20 childhood survivors of ALL between the ages of 9 – 11 (mean age of 10.6) and who have been off treatment for at least one year. The authors used the University of Quebec in Chicoutimi and University of Quebec in Montreal (UQAC-UQAM) norm-referenced, gross motor skills test battery, and found ALL patients had poorer performance than healthy controls in ten of the 11 motor tasks with 48.2% of ALL patients performing below the 15th percentile.  De Luca et al.50 studied gross and fine motor skills in 37 ALL patients who had completed treatment within the past five years (mean age 100.0 months) using the MABC-2 and the BOT-2 Short Form (BOT-2 SF). No statistically significant difference between patient and population norm scores was found with either motor tests. The children were also stratified into three groups based on their time since treatment completion, and time off treatment did not affect motor performance using either measurement tool. However, they found that 16.2% of patients within the sample were considered impaired using the BOT-2, which was comparable to the 17% of patients with impaired performance observed in the normal population.   Beulertz et al.51 used specific deficit analysis to study the motor performance and quality of life of 26 children (average age of 9.1 years) of mixed pediatric cancer diagnoses (n = 11 were ALL) at different stages during and after treatment. The study used two German standardized motor test batteries for children ages 4 – 6 years and 6 – 18 years called the Motoriktest (MOT) 4 – 6 and Deutscher Motorik-Test (DMT) 6 –18, respectively. The authors found more than 27% of patients performed below the average norm-reference scores. Specifically for each age group, children ages 4 – 6 years old did not have a lower global motor performance, but had specific deficits in motor speed and control. In contrast, children ages 6 – 17 years had a lower global motor score, with 34% scoring below the average norm-reference, and had specific deficits in 8  endurance, strength, flexibility, and coordination under pressure. ALL patients were not reported to have significant differences in motor performance than other cancer diagnoses, nor did patients with and without vincristine treatment perform differently. 1.3.2 Physical Function The Six-Minute Walk Test (6MWT) is an objective measure representing submaximal exercise functional capacity and cardiopulmontary fitness52. For the purpose of the current study, submaximal exercise functional capacity will now be referred to as physical function. In addition to the 6MWT, a recent Cochrane Review done by Braam et al.53, which included randomized and clinical controlled trials of exercise training interventions for people who were within the first five years of diagnosis of ALL, physical function was also measured using the 9-minute run-walk test, timed up-and-down stairs test, and 20-m shuttle run test. Four recent studies investigated physical function in childhood cancer survivors using the 6MWT. Hartman et al.7 studied physical function five years after treatment using the 6MWT, and all 34 participants performed significantly lower than healthy children of similar age and height by a mean of -2.05 standard deviation score. Hoffman et al.13 studied physical function using the 6MWT, timed up-and-go (TUG), hand grip strength, lower-extremity strength in 183 childhood cancer survivors of mixed cancer diagnoses (average age 13.5 years) with an average of 9.3 years post-treatment and 147 sibling as controls. The mean 6-minute walk distance (6MWD) for children of mixed cancer diagnoses was 567.8 m, and children with a leukemia or lymphoma diagnosis walked a mean 6MWD of 572.2 m. Both mixed cancer and leukemia or lymphoma patient groups walked a shorter distance compared to their siblings (594.1 m), but this relationship was only significant with the entire sample of children of mixed cancer diagnoses. Hooke et al.54 studied physical function, using the TUG and 6MWT in 16 children (6 – 12 years) 9  and 14 adolescents (13 – 17 years) receiving chemotherapy for childhood cancers.  Although not statistically significant, 6MWD improved from the first (359.05 m) to the third (406.4 m) cycle of treatment for children, but not for adolescents. Children with ALL had greater improvements than those with lymphoma and solid tumour groups. Fatigue, measured using the Childhood Fatigue Scale, was also found to be negatively associated with 6MWD. Hooke et al.55 studied physical function using the 6MWT in 29 children ages 6 – 17 years old receiving treatment for cancer of mixed diagnosis, and found no change in the mean distance walked from the first (414.71 m) to third (447.23 m) cycle of chemotherapy, but 93% of patients performed one or more standard deviations below the norm for the 6MWT. 1.4 PA in ALL Patients and Survivors PA levels of children with ALL have been well studied. Winter et al.9 conducted a systematic review on PA levels in children of any cancer diagnosis, both during and after treatment. The review included 12 studies investigating PA levels in childhood leukemia patients. All studies were cross-sectional, and three studies involving PA during treatment10,56,57, six studies investigating PA during the first ten years of treatment completion58-63, and three studies involving long-term adult survivors of childhood cancer64-66. Four studies included child and adolescent cancer survivors with any leukemia diagnosis, with the majority of subjects being ALL, and reported lower levels of PA compared with healthy controls using accelerometers62, heart rate monitors59, or self-report questionnaires61,63. These studies included ALL survivors who were between 1.5 years after treatment to 23.1 years after diagnosis with a mean age between 4.0 – 14.6 years old.  Three studies reported PA levels during different phases of treatment. One study was conducted during induction and consolation treatment56 and the other was conducted during 10  maintenance10, and found significantly reduced time spent in moderate-to-high levels of PA using accelerometers. One study58 used doubly labeled water, a gold standard measure of total energy expenditure during a period of time67, found lower energy expenditure from PA compared with controls in children with an average of 2.9 years after diagnosis for ALL.   A number of recent studies not included in the review by Winter et al.9  focused on the effect of treatment on PA levels, and have found similar trends in PA levels for children with ALL to the review. Fuemmeler et al.68 studied the relationship between PA, diet, and body composition changes in children during the first year of treatment for childhood ALL and lymphoma (n = 15) compared to age, race, and sex-matched healthy controls (n = 15; average age not reported).  The average age of cancer patients was 10.3 years at study enrolment and the majority (n = 12) of children had a diagnosis of ALL. The study measured PA using accelerometers. Children with cancer performed significantly less moderate-to-vigorous PA at six month and 12 month after starting treatment compared with healthy controls (p < 0.01).  Götte et al.69 used self-report questionnaires to study PA in 130 children and adolescents (average age of 12.2 years) before and during cancer treatment, with the majority of children being children with leukemia (n = 44). Using reference values from the PA questionnaire from the German Health Interview and Examination Survey for Children and Adolescents, the study found patients reported normal PA level before diagnosis, but at an average of three months after diagnosis patients reported a 91% reduction in minutes/week of physical exercise (baseline, 209 minutes/week vs. during treatment, 18 minutes/week; p < 0.001). Patients also reported being less interested in sports during treatment, and a lower percentage of children met PA recommendations and did not walk as much during in-patient stays.  11  Orsey et al.70 studied PA and sleep using accelerometers in 23 children and 13 adolescents (average age not published) who were actively receiving chemotherapy and/or radiation, and found they were less physically active and had poorer sleep quality than healthy children. Tan et al.71 used accelerometers to measured PA levels in 38 healthy children and compared them with 38 children with ALL undergoing induction or consolidation chemotherapy, and found leukemia patients to have lower PA levels compared to healthy children (p < 0.01). Studies investigating PA levels in children during treatment for ALL have consistently shown reduced PA compared with healthy controls. It has been suggested that these reduced PA levels during treatment remain the same after treatment completion17. However, well-defined reasons for reduced levels of PA in children receiving treatment or children who have completed treatment for ALL remain unclear9,10.  1.4.1 Potential Reasons for Reduced PA in ALL Patients and Survivors The reason for reduced levels of PA in childhood cancer patients and survivors has been discussed in the literature. Götte et al.69 suggested that the lower PA levels during treatment were a result of permanent restriction by treatment related equipment, such as the infusion stand, wheel chairs, or forearm crutches. Winter et al.56, with similar reasoning, suggested these significantly reduced PA levels of patients undergoing treatment were due to patients being connected to medical devices, which inherently restricted them to the wards and reduced their mobility. The opinion of Tan et al.71 as to why patients undergoing treatment were less active was because patients rarely leave their beds during their stay in the ward due to fatigue or experience unpleasant treatment side effects, and also spend a large amount of time in bed resting, watching television, or playing computer games for leisure entertainment. Accelerometer data from Tan et al.71 also found patients undergoing consolidation therapy to be more physically 12  active than patients undergoing induction therapy, and reasoned that consolidation may be a less intense therapy phase compared with induction therapy. Tan et al.71 also suggested the difference in PA levels by phase of treatment may be that by the time of consolidation therapy, patients have become better at coping with the disease and treatment over time, allowing them to better manage the side effects and to spend less time in bed, or that patients in consolidation may have familiarized themselves with the hospital environment and medical devices throughout the course of receiving treatment, making them less afraid to move around within the ward71.  Aznar et al.10 found patients in maintenance therapy had comparable PA levels to healthy controls because maintenance therapy patients were treated as outpatients, and therefore were not confined to inpatient ward settings, and reintegrated back into homes and schools with exposure to common forms of leisure activity. Based on these findings, experts have hypothesized that patients with an inactive lifestyle during treatment may allow inactivity to persist throughout maintenance therapy or after treatment completion; therefore these time points have been suggested as suitable times to reintroduce habitual PA in these children9,10. 1.5 Impact of Time During Treatment and Time After Treatment Previous longitudinal studies have investigated changes in motor performance, physical function, and PA during the course of treatment and/or after treatment. Vainionpaa72 evaluated motor abilities in childhood ALL patients at diagnosis and four time points during treatment, and found impairments in fine and gross motor performance in 18% and 30% of participants, respectively after 2 – 3 years of therapy compared to diagnosis.  Hockenberry et al.46 longitudinally assessed fine motor performance within six months of diagnosis, and one and two years after diagnosis, and found mean visual-motor integration scores for low and high-risk ALL children to decrease from within six months of diagnosis to one and two years follow-up. 13  Hartman et al.38 conducted a longitudinal study following ALL patients for two years from diagnosis, and found an improvement in motor performance from diagnosis to end of treatment based on mean standard deviation scores. Hartman et al.7 assessed motor performance at two time points, end of treatment and 5-year follow-up, and found 38% of participants who had been “at risk for impairment” at the end of treatment improved to normal scores at follow-up..  Two longitudinal studies assessed physical function, specifically using the 6MWT, during treatment at multiple time-points54,55. One of the studies55 hypothesized physical function would decrease with treatment and that the related adverse side-effects would be exacerbated over time. Instead, the study found that distance walked on the 6MWT did not change significantly from the first to third cycle of chemotherapy. The other study54, in contrast, found children ages 6 – 12 years old improved in 6MWT performance from the first to third cycle of chemotherapy, but did not see any change in adolescents ages 13 – 18 years old.  Three studies measured PA longitudinally during treatment68,69,71, but only two had baseline measures, with one having accelerometer data of PA within 5 months of diagnosis68, and the other having self-report retrospective PA of a typical week prior to diagnosis69.  Tan et al.71 used accelerometers and found patients undergoing consolidation therapy had higher levels of PA compared to patients in induction therapy. Götte et al.69 found a significant reduction in self-report daily PA and minutes of exercise per week from before treatment to three months after treatment.  Fuemmeler et al.68 used accelerometers and found patients had greater levels of moderate-to-vigorous PA from within five months after diagnosis to 12 months after diagnosis (while still on treatment), but ALL patients were still less physically active compared with healthy controls.   14  1.6 The Relationship between Late Effects and PA  While research investigating the factors influencing PA levels in ALL survivors is beginning to emerge, the factors influencing PA levels remain unclear9,10.  The two suggested points of view are physiological and socio-environmental factors11. Socio-environmental factors will be referred to as psychosocial factors in this document.  As discussed above, the physiological factors refer to the adverse physical outcomes of cancer and cancer treatment that reduce the child’s physical capacity to perform PA. Psychosocial factors refer to lower self-reported comfort with emotional and physical symptoms and limitations, and lower resilience with positive activities promoting health10. The result of this is suggested to be a “spectrum of disuse” encouraged by parents and physicians to protect the child’s health after a life threatening disease11; and overprotection by parents potentially changing the child’s perception of their actual capacity for PA, and thus creating a fear of overexertion and low self-efficacy10. 1.6.1 Physiological Factors Associated with PA in ALL Survivors Few studies have directly investigated the physiological factors associated with PA in childhood ALL survivors. Hartman et al.7 was one of the first to study the measure motor performance, physical function, and PA, and to analyze the association between physical function and PA. PA was measured in 34 survivors who have been more than five years off treatment using a semi-structured interview asking the child and parents about their physical education and sporting participation. Twenty-nine children attended physical education classes and twenty-two children played sports at club level after school. The standard deviation scores for 6MWT were not different between children who did or did not participate in sports. This study did not analyze if motor performance was different between those who did or did not 15  participate in sports, but found a weak positive correlation between the 6MWT and motor performance.  Taskinen et al.14 measured muscle performance of 45 childhood ALL survivors who did not receive a stem cell transplant (median age of 13.3 years), and who have been at least three years off treatment (median time off treatment 6.8 years), and compared them to age-specific healthy controls (n = 522) and non-cancer patients who had received a stem cell transplant (n = 94, median age of 12.0 years, and median time after therapy of 5.2 years). Muscle performance was assessed using a battery of tests focusing on muscular endurance, strength, flexibility, and speed. PA levels were measured using a personal interview asking about their exercise routine and sports club membership. Individual muscle performance tests and overall scores for the muscle performance battery in ALL patients who did not receive stem cell transplants were not significantly different from healthy controls. However, ALL patients who did not receive stem cell transplant performed significantly better than patients who did receive a stem cell transplant in sit-ups, sit-and-reach, back-extension, shuttle-run, and overall score. Twenty-nine ALL patients had sports club memberships, but only 19 patients (42%) exercised regularly at least once a week, while ten patients exercised more than three times per week. When investigating the relationship between the muscle performance tests and PA levels, compared to study participants who exercised less than three times per week, study patients who exercised more than three times per week had better overall scores for muscular performance and scores for individual muscular endurance, strength, flexibility and speed tests, with the exception of the leg lifts.  Hoffman et al.13 measured PA using the Past-Year Leisure-Time Physical Activity section of the Modifiable Activity Questionnaire to quantify minutes of PA per week and studied 16  its association with physical function using the 6MWT within five years after diagnosis. PA was not significantly different between survivors and siblings, but was related to physical function measures, including the 6MWT. Greater reported minutes of week per PA was associated with longer 6MWD (correlation coefficient and p-value statistics not reported).  Chung et al.12 studied the impact of cancer and its treatment on PA levels and behaviour in Hong Kong Chinese childhood cancer survivors ages 9 – 16 years old who have completed treatment for at least six months. The study used self-report PA questionnaires, the Chinese University of Hong Kong: PA Rating for Children and Youth (modified from the Jackson Activity Coding and Godin-Shephard Activity Questionnaire Modified for Adolescents), to retrospectively measure their PA levels before diagnosis and PA levels at the time of participation in the study. A self-reported, open-ended qualitative question was included to explore the factors affecting PA levels, namely asking the children, “Can you tell me what the factors are that influence your PA level or behavior?” The study included 128 childhood cancer survivors (mean age not reported) and 64.1% of survivors had been diagnosed with leukemia. The majority had completed treatment in the past 24 months (64.8%). PA levels at the time of study assessment were significantly decreased from the PA levels retrospectively reported for the prior to diagnosis time point. The study found that 37.5% of children were not regularly active. While 58.6% were physically active, the children were not regularly active three to five times a week. In the open-ended questions, 35.2% of participants reported that physical factors such as fatigue and decrease in self-reported physical strength and endurance prevented them from engaging in PA. Furthermore, 41.4% of children reported concerns that academic performance interfered with PA engagement, such as: “Too much homework and not enough time for PA”; 17  “Need to make extra efforts to catch up with peers after remission”; and “Pressure to attend academic-related classes or extracurricular activities during the weekend”.   1.6.2 Psychological Factors Associated with PA in ALL Survivors Regarding psychological factors affecting PA in children treated for ALL, self-efficacy and parental influence are the two main factors discussed in the research literature73. Although the focus on this thesis is not on psychological factors, such factors are important when studying PA in childhood cancer patients and survivors and will be acknowledged in the current thesis by including some relevant information from the current literature.  Self-efficacy is defined as the belief in one’s ability to organize and execute the course of action required to produce a given attainment74. Self-efficacy beliefs are one of the most significant predictors of success in individuals and are thought to be the primary motivator and determinant of human behaviour10,75. The perceptions of self-efficacy are shaped by four principle sources: verbal persuasion from significant others; past performance; modeling or vicarious experiences; and physiological or physical state. PA self-efficacy refers to a person’s beliefs in their own ability to perform PA74. PA self-efficacy can include three different components: ability for someone to overcome barriers to PA, ability to ask someone for help to be physically active, and perception of self-competence and capacity to be physically active74. PA self-efficacy is a significant predictor of being physically active, and can significantly influence PA behaviours in healthy populations76. Few studies have investigated psychological factors influencing PA levels in children treated for childhood cancers. Finnegan et al.64 studied correlates of PA in 117 young adult childhood cancer survivors (mean age 24 years old with an average time off treatment of 11 years), including self-efficacy for PA measured with an 18-item questionnaire capturing six-18  subscales of self-efficacy, and PA was measured using a single-item question asking how long participants have been engaging in regular moderate or vigorous PA. The study found participants who were physically active within the last six months or for more than six months had higher PA self-efficacy than survivors who were considered inactive.  Keats et al.77 studied PA behaviours in 59 adolescent cancer survivors of mixed diagnosis. The Godin Leisure Time Exercise Questionnaire (GLTEQ) was used to collect self-report information on usual PA, and self-efficacy was assessed using self-report questionnaires. Self- report PA behaviour was significantly correlated with PA self-efficacy. Wright et al.61 used the Children’s Self-perceptions of Adequacy in and Predilection of Physical Activity Scale, a questionnaire not based on self-efficacy constructs, to ask 99 children, who have completed treatment for ALL for at least one year, about PA. The children reported lower self-perception of adequacy to be physically active and had a lower preference (predilection) for participating in PA compared with their healthy counterparts.  A recent study by Gilliam et al.73 investigated cognitive influences of family and peer support on PA in 105 cancer survivors of mixed diagnosis who were at least one year off treatment (average age of 12.3 years; average time off treatment 4.9 years). PA was measured using the GLTEQ, while cognitive variables, such as family and peer support for PA, perceived benefits and barriers to PA, and PA self-efficacy, were measured using questionnaires. The study found peer and family support for PA to be correlated with self-report PA, which was partially mediated by self-efficacy for PA. In addition, survivors with greater PA self-efficacy were more active, and survivors who had more family and peer support for PA were likely to feel more confident in their ability to engage in PA, despite the physical and psychological effects of cancer. 19  1.7 The Importance of PA in Childhood Cancer Survivors The well-established physical and psychological benefits of exercise and PA seen in healthy children with higher PA levels raises health concerns for childhood survivors of ALL78. Decreased PA in healthy youths contributes to obesity, which can subsequently lead to other chronic diseases, such as type 2 diabetes, cardiovascular disease, and metabolic syndrome15. Obesity has been shown to be related to poor academic performance, poor self-esteem, and negative social outcomes, such bullying and teasing by peers15. PA in healthy children have also been shown to be directly related to better academic performance and overall cognition79, and sports participation in healthy children have been shown to be related to better psychological and social well-being, such as better self-esteem, self-concept, connectedness to friends, and mental health80. PA also provides opportunities for movement, which is essential to a child’s motor and cognitive skills development and learning, such as integrating sensory, perception, actions and external feedback, and self-image15,81,82. Obesity, and subsequent development of diabetes mellitus and cardiovascular disease, have been identified as a potential late effect of chemotherapy in ALL childhood17 and adult survivors16. Children with ALL are also at increased risk for low bone mineral density83  and may not reach peak bone mass84. Based on the benefits of PA documented in healthy children, PA can potentially play a role in attenuating the risk of developing obesity and osteoporosis in children who have completed treatment for ALL78.  1.8 PA and Exercise is Safe for Childhood Cancer Patients and Survivors A systematic review by Huang and Ness85 reported fifteen studies using exercise interventions during or after treatment for any childhood cancer diagnosis; nine studies used supervised anaerobic, resistance and/or flexibility training with or without home-based 20  exercise38,86-95, five used enhanced PA interventions96-100, and one used an individualized home-based exercise program101. Early evidence from these small exercise intervention studies showed improvements in cardiopulmonary fitness6,86,98, muscle strength and flexibility6,38,95,97, general physical functioning6,94, health related quality of life6,94,97,99,and reduced fatigue96,97, and showed that exercise interventions did not have deleterious effects to the patients’ immune function87,90,93.  Although these exercise interventions have been deemed safe and feasible, limitations within the existing literature do not allow for confident statements to be made about the specific benefits of exercise interventions during and after treatment for childhood cancers102. These limitations include85: a lack of data from randomized controlled trials with only four38,95,98,100 trials reported in the literature to date, small sample sizes (generally six to 38), limited diversity of cancer diagnosis (majority are ALL), and inconsistencies with exercise prescription parameters used (type, duration, frequency, and outcome measurements).  21  Chapter 2: Research Study 2.1 Introduction Understanding the factors affecting PA for childhood cancer survivors will help healthcare providers provide quality care and may help lessen the severity of late effects of therapeutic interventions103. Motor performance has been shown to be related to PA in healthy children82, and physical function as measured by the 6MWT is a reflection of functional exercise capacity52. To our knowledge, only the three studies7,13,14 have investigated the physical factors associated with PA in children treated for ALL using objective methods of motor performance or physical function. However, these studies included patients well after they have completed treatment with an median years off treatment ranging from 5.27 – 6.314 years, or 9.3 years after diagnosis13.  Only one study13 used a PA questionnaire validated in children with chronic disease (Past-Year Leisure-Time PA section of the Modifiable Activity Questionnaire) while the other two studies7,14 measured PA using unstandardized interviews asking about PA and sports participation. Finally, the inclusion criteria for the age of the children included in these studies vary, with studies including children ages 9.2 – 20.1 years old14, 9.0 – 18.7 years old7, and 9 – 18 years old with a mean age of 13.5 years13. To our knowledge, no study has examined motor performance and physical function exclusively in children between the ages of 8 – 13 years old within their first three years of completing treatment for ALL. Investigating PA levels, motor performance and physical function in children early after treatment will build an understanding of their PA levels, if the physical effects of treatment discussed in Section 1.3 are present, and if PA, motor performance, and physical function are associated with each other in this population. This will further inform 22  PA interventions for children who have just completed treatment for ALL, which has been suggested to potentially be a suitable time to re-integrate PA in habitual lifestyle9.  2.2 Purpose The purpose of this descriptive pilot study was to examine the integration of motor performance and physical function testing as part of a long-term follow-up visit to determine if motor performance and physical function are associated with PA levels in children who have completed treatment for ALL within the last 3 – 36 months.  2.3 Objectives and Hypothesis The primary objective of the current study was to determine the association between motor performance and physical function and self-report PA levels in children who have completed treatment for ALL.  We hypothesize lower self-report PA levels will be associated with lower motor performance and lower physical function in children who have completed treatment for ALL. 2.4 Methods 2.4.1 Ethical Approval Ethical approval for this study was provided by the Children’s and Women’s Research Ethics Board (H13 - 01823). This study was also approved by the Pediatric Hematology, Oncology, and Bone Marrow Transplant Program Research Oversight Committee at the British Columbia Children’s Hospital. 2.4.2 Participants 2.4.2.1 Population A cross-sectional sample of children ages 8 – 13 years old and who have completed primary treatment for ALL were recruited through the oncology Long-term Follow-up Clinic 23  (LTFU) in the Ambulatory Care Building at the British Columbia Children’s Hospital (BCCH). The inclusion criteria were: children who were 3 – 36 months post-treatment for ALL attending the LTFU at BCCH; children knowledgeable in English to complete the questionnaires and assent forms, with parents/guardians knowledgeable in English to complete the consent forms; and children treated for ALL at BCCH. Children were excluded if they had any symptoms or impairments unrelated to the cancer diagnosis and treatment which can influence physical function or motor performance, such as Down Syndrome or limb salvage surgery; patients who received cranial radiation; patients who had a relapse; or patients who were participating in other research studies. 2.4.2.2 Recruitment Potential participants were identified from the ALL oncology LTFU patient list.  Using the eligibility criteria listed above, a list of potential participants was developed by the clinical research associates in the Pediatric Hematology, Oncology, and Bone Marrow Transplant Program.  LTFU clinic nursing staff (Angela Pretula and Marion Nelson) pre-screened the list for eligible participants.  The updated list was then provided to the study Co-Principle Investigator (Dr. Pritchard) or Co-Investigator (Dr. Fryer) to confirm with the treating oncologists their approval to invite the patient to participate in the study. For the potential participants approved by the treating physician, a letter of invitation was mailed to parents of the eligible potential participants approximately one month prior to their next scheduled appointment to the LTFU.  A follow-up phone call was completed by the student investigator approximately 10 – 14 days later to ask if the parents were interested in participating and to answer any questions about the study. If the parents and child were interested, a study assessment visit was scheduled as part of the next LTFU clinic visit.  At that time, a copy of the informed consent and 24  assent for parent and child, respectively, was sent by mail or email (based on parent preference), for review prior to the LTFU clinic visit. The student investigator arranged to meet the parents and participants at the LTFU clinic before escorting them to complete testing at an examination room in the Physical Therapy and Occupational Therapy Department located in the same Ambulatory Care building at BCCH. 2.4.2.3 Sample Size ALL is the most commonly diagnosed malignancy in childhood cancers1 with the total number of diagnosis for ALL in children in British Columbia is approximately 30 diagnoses per year. The majority of patients in British Columbia is treated at BCCH and attends the LTFU yearly after treatment completion (approximately five patients per week). With the recruitment window of children who have completed treatment in the past 3 – 36 months, the overall recruitment pool was approximately 75 children over one year. The number of participants for this pilot study was not based on a sample size calculation, but rather aimed to recruit a representative sample of patients returning to the LTFU within an eight month period.   An anticipated recruitment rate of approximately 50% of the eligible pool allowed recruitment of a final sample size of approximately ten patients into the study. The anticipated recruitment target was based the willingness of children and the parents of a clinical population to participate in additional testing and prolonged clinic visit.  2.5 Procedures Depending on participant and parent preference, the study visit was scheduled prior to or after the LTFU clinic visit appointment with the physician.  In addition, some testing was completed while participants were waiting for their clinic visit within an appropriate time window confirmed with the clinic nurses.  At the study visit, informed consent and assent from 25  the parents and child, respectively, were obtained (five minutes). After informed consent and assent were obtained, the child was taken to the examination room located in the Physical and Occupational Therapy Department to complete: 1) the motor performance test (15 minutes), 2) PA questionnaire (15 minutes), and 3) fatigue questionnaire (10 minutes). The child then walked with the student investigator to the walk-way connecting the Ambulatory Care building and the main BCCH building (approximately one minute walk from the LTFU) to complete the physical function test (15 minutes).  The exact order of testing was not standardized other than ensuring the physical function test was always done after the motor performance test to ensure fatigue would not affect the participants’ motor performance. The questionnaires were completed at convenient intervals during the visit. The total study testing time at the clinic visit, including obtaining consent and assent attainment (five minutes), objective measures testing (30 minutes) and child questionnaires (25 minutes), was 60 minutes.  At completion of the study visit, a copy of the Canadian Physical Activity Guidelines prepared by the Canadian Society for Exercise Physiology was given to the participants. All parents/guardians received $10.00 as compensation for cost of parking during participation in the study appointment. 2.5.1 Demographics Data The following patient information was collected from the patient medical charts: height, weight, year and month of birth, date of diagnosis, date of treatment completion, date of clinic visit (study date), the total dose of anthracyclines in milligrams per metre squared (mg/m2), ALL risk level, and patient sex. This information was used to determine the current age, age at diagnosis, time from diagnosis to study date, and time from treatment completion to study date. The height and weight on the study date measured at the LTFU by the clinic nursing staff on the 26  day of the study assessment was used to determine body mass index (BMI). This information was obtained by the student investigator under the direction of Dr. Pritchard. 2.5.2 Outcome Measures A summary of the outcome measures can be found at the end of this sub-sub-section on Table 1. 2.5.2.1 Questionnaires 2.5.2.1.1 Physical Activity Questionnaire for Older Children (PAQ-C) PA was measured using the PA Questionnaire for Older Children104 (PAQ-C). The PAQ-C is a 10-item questionnaire designed for children ages 8 – 14 years assessing moderate to vigorous PA levels for the last seven days during a regular school day and weekend. The first question contains a checklist of 22 common leisure and sport PA and two “other” fields asking often they participated in these activities. This question is scored as the average of all activities under a 1 – 5 scale, 1 being “No”, 2 being “1-2”, 3 being “3-4”, 4 being “5-6”, and 5 being “7 times or more.” The other eight questions ask how often they were very active in their physical education classes, recess, lunch, after school, evenings, and weekends, and was scored using a 1 – 5 scale. The total score is an average of the sum of the nine questions ranging from 1 – 5, with 1 indicating low PA and 5 indicating high PA. The Chronbach’s alpha coefficient of internal consistency was reported as r = 0.73 for all age groups 105, while validity against a Caltrac motion sensor has been reported with a correlation of r = 0.39106. Depending on the participant’s literacy, the questionnaire took approximately 15 minutes to complete. 2.5.2.1.2 PedsQL™ – Multidimensional Fatigue Scale Cancer-related fatigue was measured using the PedsQL™ Multidimensional Fatigue Scale. Permission to use this questionnaire was requested by completing the standard permission 27  request forms found in their website (www.pedsql.org). This 18-item questionnaire captures three dimensions of fatigue: (1) General Fatigue (GF) (e.g., “I feel too tired to spend time with my friends.”), (2) Rest/Sleep Fatigue (SRF) (e.g., “I take a lot of naps.”), and (3) Cognitive Fatigue (CF) (e.g., “It is hard for me to keep my attention on things.”), with six items for each dimension. The participant is asked to grade how often they find problems with fatigue with the respective items using a Likert scale of 0 – 4, with 0 being “Never”, 1 being “Almost Never”, 2 being “Sometimes”, 3 being “Often”, and 5 being “Always”. The questionnaire is available in a child (8 – 12 years old) and teen (13 – 18 years old) self-report version, and in parent proxy version. All versions differ only in instructional prompting, but all 18 items are identical in all versions. The questionnaire asks the participant to rate fatigue related problems in the past month. The questionnaire is scored out of 100, with higher score indicating better health-related quality of life (lower fatigue symptoms). The questionnaire has been tested for construct validity against healthy children (p = 0.0001 for the total fatigue score and GF, p = 0.005 for SRF, and p = 0.024 for CF), and internal consistency reliability (Chronbach coefficient alpha of 0.88 for total score, 0.77 for GF, 0.74 for SRF, and for CF for child-report, and 0.92, 0.88, 0.87, and 0.91, respectively, for teen-report), in a pediatric cancer population107. Depending on the participant’s literacy, the length of time to complete the questionnaire is reported to be ten minutes. 2.5.2.2 Physical Assessments 2.5.2.2.1 Bruininks-Oseretsky Test of Motor Proficiency, Second Edition – Short Form (BOT-2 SF) Motor performance was assessed using the Short Form version of the Bruininks-Oseretsky Test of Motor Proficiency, Second Edition108 (BOT-2 SF). The first version, Bruininks-Oseretsky Test of Motor Proficiency (BOTMP), has been used in previous studies to 28  assess children with childhood cancers37,109. The BOTMP was revised using focus groups with experienced users, including occupational and physical therapists, with six improvement goals guiding the development of the BOT-2: (1) improving the relevance of the testing content; (2) expanding the range of fine and gross motor skills tested; (3) allowing better testing for younger children, ages four and five years old; (4) extending normative data with people up to ages 21 years and 11 months old; (5) improve the presentation of testing scripts for examiners and examinees; and (6) improve the quality of testing equipment110. The BOT-2 is a standardized, norm-referenced measurement tool used to assess fine and gross motor skills of children and youth between the ages 4 – 21 years of age. The BOT-2 allows practitioners and researchers to discriminate and evaluate motor performance in four motor area composites: fine manual control, manual coordination, body coordination, and strength and agility. The Short Form version of the BOT-2 consists of 14 tests selected by the creator as the most representative assessments of each motor area composite. Scores can be reported as a total score, which can then be converted to a standardized score to compare against pre-determined normalized scales or percentiles. After scoring, the participants can be placed in five performance descriptive categories: “Well-Above Average”, “Above Average”, “Average”, “Below Average”, and “Well-Below Average.”  The Short Form version was scored by reporting the standardized score and performance descriptive category.   The BOT-2 has been used to assess motor performance in clinical populations with developmental coordination disorders, mild to moderate mental disorders, and children with high-functioning autism or Asperger’s disorder. It successfully distinguishes between clinical and non-clinical populations by demonstrating significantly lower scores in clinical populations110. Each of the tests used in the BOT-2 have been tested for inter-rater, test-retest, 29  and internal consistency reliability, and have been reported as, depending on the individual test, > 0.86, > 0.80, and > 0.80, respectively110. This assessment was administered by the student investigator, and took approximately 15 minutes to complete. 2.5.2.2.2 Six Minute Walk Test (6MWT) Physical function was assessed using the 6MWT, using the standardized methods outlined by the American Thoracic Society (ATS)52. The 6MWT assesses overall aerobic endurance by having the participant walk as far as they can at a self-selected pace back and forth between two pylons. An existing 50 m course in the walkway connecting the Main Building and the Ambulatory Care building at BCCH was used, making the distance between the two pylons 25 m apart. The number of laps was counted, the distance of partial laps was measured using a tape measure, and the total distance covered within the six minutes (six-minute walk distance, 6MWD) was recorded. The only exception to the standardized methods as outlined by the ATS was the length of each lap. The ATS states each lap must be 60 m in length but the current study used an existing 6MWT course at the BCCH measuring 50 m per lap.  The 6MWT has been reviewed as a good representation of sub-maximal level of functional capacity which is easy to administer and reflects functional exercise levels for daily PA. Test-retest reliability for the 6MWT in chronic pediatric conditions has been reported in a systematic review of measurement properties with an interclass correlations ranging between 0.84 – 0.98 from six studies for different chronic conditions111. In the same systematic review, criterion validity for 6MWT was tested in one study against estimated VO2max (r = 0.34), two studies with measured VO2max (r = 0.76), and three studies with measured VO2peak (r = 0.43 – 0.53). This assessment was administered by the student investigator, and took approximately 15 minutes to complete.  30  Table 1 - Summary of Outcome Measures and Time to Administer Outcome Tool Citation Time to Administer (min) Completed by Questionnaires Physical Activity Physical Activity Questionnaire for Older Children (PAQ-C) Janz et al., 2008105 15 Child Fatigue PedsQL™ Multidimensional Fatigue Scale Varni et al., 2002107 10 Child Total Questionnaire Time to Administer:  25  Objective Measures Motor Performance Bruininks-Oseretsky Test of Motor Proficiency, Second Edition (BOT-2) Bruininsk and Bruininks, 2005108 15 Study/Clinical Staff Physical Function Six-Minute Walk Test (6MWT) Bartels, Groot & Terwee, 2012111 15 Total Time to Administer Objective Measures: 30 Minutes Obtaining Consent and Assent: 5 Minutes Total Time for Children with Consent/Assent: 60 Minutes  2.5.3 Statistical Analysis Demographic, anthropometric and medical information were summarized as means and standard deviations. Participants were categorized into ALL risk level group, namely Standard Risk and High Risk, and Anthracycline Cardiotoxicity Risk groups112 based on total anthracycline dosage (mg/m2), and Low Toxicity Risk (0 – 100 mg/m2), Moderate Toxicity (101 – 250 mg/m2), and High Toxicity Risk (> 250 mg/m2). Participants were also categorized into BMI group (i.e. healthy weight, overweight, and obese) based on the World Health Organization Child Growth Standards113 and descriptive category for the BOT-2 SF. Outcome variables were 31  summarized as sample means, standard deviations and 95% confidence intervals (CI) for the child self-reported PA as PAQ-C scores; standardized scores for BOT-2 SF; the measured distance for the 6MWT (6MWD), the calculated distance of the 6MWD for healthy children, and SDS for normative data comparison developed by Geiger et al.114; and the PedsQL™ Multidimensional Fatigue Scores as Total Fatigue, CF, SRF, and CF. The measured PedsQL™ Multidimensional Fatigue Scores was compared to the scores for childhood cancer patients (mix of on-treatment and off-treatment children) and healthy children from Varni et al.107.  Data analysis was done using SPSS statistical software (IBM, Version 22.0) with accepted levels of significance at p < 0.05. The hypothesis was tested using Spearman’s correlation coefficient to test the association between PAQ-C scores and BOT-2 scores and measured 6MWD. Mann Whitney U-Test was used to test the difference in outcome variables between ALL risk level group, BMI and Anthracycline Cardiotoxicity Risk groups, and a simple linear regression model was used to test the effect size in cases where associations were found. Covariates were analyzed to test their effect on primary and secondary outcomes using Spearman’s correlations. 2.6  Results 2.6.1 Participants At the start of recruitment a list of potential participants who would attend the LTFU clinic over the following eight month period was prepared by the LTFU Clinic clinical research associates. Twenty one potential participants were identified, and contacted regarding participation in the study.  Of these, 13 children participated in the study visit. Three children were not interested in participating, three could not be contacted, one had moved away from Vancouver, and one had a conflicting appointment and could not attend the study visit.   32  The participant characteristics are presented in Table 2.  The study participants were primarily male, with nine male participants and four female participants.  The mean age of the participants at the time of the study was 9.6 years and the mean BMI was 19.2 kg/m2. 2.6.2 Outcomes Measures  The means, standard deviations and 95% CI for the outcome measures are outlined in Table 3. The mean PAQ-C score was 3.1 (95% CI: 2.8 – 3.4). The mean BOT-2 SF standardized score was 50.9 (95% CI: 47.0 – 54.9) and the percentile score was 52.9 (95% CI: 55.5 – 89.0).  The 95% CI for the standardized score was within the range of “Average” scores (40 – 60)108 for motor performance, and 95% CI for the percentile scores were within or above “Average” (18 – 97)108, respectively. Using descriptive categories of the BOT-2 SF, one participant was considered to perform “Below Average”, nine were “Average”, and three were “Above Average”. The mean measured 6MWD was 544.42 m (95% CI: 486.8 – 602.1 m), calculated 6MWD was 628.4 m (95% CI: 610.8 – 645.9 m) and the mean 6MWD SDS was -1.62 (95% CI: -2.53 – -0.71) with a range from -4.15 – 1.42. Two participants performed above healthy norms for the 6MWD. The 95% CI for the measured 6MWD was less than calculated 6MWD and did not overlap with the 95% CI for the calculated 6MWD. The 95% CI for the 6MWD SDS was less than 0. These results provided confidence that the mean measured 6MWD was less than the mean calculated 6MWD, and the mean 6MWD SDS was less than normative values. The mean scores from the PedsQL™ Multidimensional Fatigue Scale for Total Fatigue, GF, SRF, and CF were 74.6 (95% CI: 67.9 – 81.3), 82.7 (95% CI: 76.4 – 89.0), 70.2 (95% CI: 61.0 – 79.4), and 74.6 (95% CI: 58.5 – 83.1),  respectively.  33  2.6.3 Relationship of PA with Motor Performance and Physical Function PAQ-C score was not significantly associated with BOT-2 SF standardized score (rs = 0.282, p = 0.35), and measured 6MWD (rs = -0.429, p = 0.14) or 6MWD SDS (rs = -0.094, p = 0.76).  2.6.4 Impact of Body Mass Index BMI SDS was significantly associated with measured 6MWD (rs = -0.602, p = 0.03) and 6MWD SDS (rs = -0.691, p < 0.01), and approached significance with BOT-2 SF standardized scores (rs = -0.515, p = 0.07).  The Mann-Whitney U test was used to test the difference in measured 6MWD, 6MWD SDS, BOT-2 standardized score, and the PAC-Q Score between the healthy weight (HW, n = 7) and overweight and obese (OWO, n = 6) children (Table 4).  The one-tailed p-value statistics was used because HW children were expected to have higher scores than the OWO children for each outcome measure. The mean rank for HW children and OWO children for the measured 6MWD were 9.14 and 4.50, respectively, and a significant difference was found (Mann-Whitney U (U) = 6.0, Z = -2.143, p = 0.04, r = 0.6).  The mean rank for HW and OWO children for the 6MWD SDS were 9.86 and 3.67, respectively, and a significant difference was found (U = 1.0, Z = -2.857, p < 0.01, r = 0.8). The mean rank for HW and OWO children for the BOT-2 SF standardized score were 9.00 and 4.57, respectively, and a trend towards a significant difference was found (U = 7.0, Z = -2.017, p = 0.05, r = 0.6).  The mean rank for the PAQ-C Score between the HW and OWO children were 6.93 and 7.08, respectively, and no significant difference was found (U = 20.5, Z = -0.072, p = 0.95, r = 0.02).  A simple linear regression model was done with BMI SDS being the independent variable and 6MWD SDS being the dependent variable. Every increase in one BMI SDS was associated with a decrease in 0.70 6MWD SDS (Constant = -0.98, β = -0.70, p = 0.04, R2 = 0.325). 34  2.6.5 Impact of ALL Risk Level The Mann-Whitney U test was used to test the difference in measured 6MWD, 6MWD SDS, BOT-2 standardized score, and the PAC-Q Score between the Standard and High Risk Level children (Table 5). No significant difference was found between the two Standard Risk (n = 9) and High Risk (n = 4) children. However, the mean PAQ-C score (U = 8.0, Z = -1.545, p = 0.15, r = 0.4), measured 6MWD (U = 10.0, Z = -1.234, p = 0.26, r = 0.3), 6MWD SDS (U = 10.0, Z = -1.234, p = 0.26, r = 0.3), and BOT-2 SF standardized score (U = 18.0, Z = 0, p = 1.00, r = 0) for the Standard Risk children were greater but not statistically different than the High-Risk children. 2.6.6 Impact of Anthracycline Dosage and Cardiotoxicity Risk Category The average cumulative anthracycline dosage for the current study was 105.8 mg/m2, with nine participants categorized as Low Toxicity Risk for cardiotoxicity, and four participants categorized as Moderate Toxicity Risk. Anthracycline dosage was not associated with PAQ-C Scores (rs = 0.469, p = 0.11), BOT-2 SF standardized scores (rs = -0.229, p = 0.45), or fatigue scores (GF rs = 0.152, p = 0.62; SRF rs = 0.266, p = 0.38; CF rs = 0.089, p = 0.77; Total Fatigue rs = 0.197, p = 0.51). However, there was a trend for an association between anthracycline dosage and measured 6MWD (rs = -0.492, p = 0.09), but not for 6MWD SDS (rs = -0.369, p = 0.22). The Mann-Whitney U test was used to test the difference in measured 6MWD, 6MWD SDS, BOT-2 standardized score, and the PAC-Q Score between the anthracycline cardiotoxicity risk categories (Table 6). No significant difference was found between the Low Toxicity (n = 9) and Moderate Toxicity (n = 4) children. The mean measured 6MWD, 6MWD SDS, and BOT-2 standardized score for the Low Risk children were greater but not statistically different than the Moderate Risk children. 35  2.6.7 Impact of Time from Treatment Completion Time from treatment completion was not associated with PAQ-C (rs = 0.165, p = 0.59), BOT-2 SF standardized scores (rs = 0.477, p = 0.12), measured 6MWD (rs = 0.440, p = 0.13) and 6MWD SDS (rs = 0.434, p = 0.14), or fatigue scores (GF rs = 0.265, p = 0.38; SRF rs = 0.248, p = 0.41; CF rs = 0.077, p = 0.80, Total Fatigue rs = 0.283, p = 0.35).   36  Table 2 - Participant Characteristics  Mean (SD) or n (%) Range Sex  4 Female (31%); 9 Male (69%)  Age at Study Session (years) 9.6 (1.4) 8.3 – 13.7 Age at Diagnosis (years) 5.0 (1.7) 2.6 – 8.8 Time from Diagnosis (years) 5.1 (0.9) 2.9 – 6.2 Time from Treatment Completion (years) 2.1 (0.7) 0.7 – 3.2 BMI (kg/m2) 19.2 (3.6) 14.5 – 26.0            Healthy 7 (54%)             Overweight 3 (24%)             Obese 3 (24%)             SDS 0.9 (1.2) -1.44 – 3.00            Percentile 72.2 (28) 8 – 99 ALL Risk Level            Standard Risk 9 (69%)             High Risk 4 (31%)  Anthracycline Dosage (mg/m2) 105.7 (44.7) 75 – 175            Low Toxicity Risk 9 (69%)             Moderate Toxicity Risk 4 (31%)  Abbreviations: BMI: body mass index; ALL: acute lymphoblastic leukemia.   37  Table 3 – Summary of Outcome Measures Outcome Measure Mean (SD) or n (%) Range 95% Confidence Interval PAQ-C Score 3.1 (0.5) 2.2 – 3.6 2.8 – 3.4 PedsQL™ Multidimensional Fatigue Scale            Total Fatigue Score 74.6 (11.1) 51.4 – 95.8 67.9 – 81.3           General Fatigue  82.7 (10.5) 66.7 – 100.0 76.4 – 89.0           Sleep/Rest Fatigue  70.2 (15.3) 37.5 – 91.7 61.0 – 79.4           Cognitive Fatigue 74.6 (11.1) 41.7 – 100.0 58.5 – 83.1 6 Minute Walk Test             Measured 6MWD (m) 544.4 (95.4) 409.72 – 735.19 486.8 – 602.1            Calculated 6MWD (m) 628.4 (29.0) 588.3 – 688.4 610.8 – 645.9            6MWD SDS -1.62 (1.50) -4.15 – 1.42 -2.53 – -0.71             Below Norm 11 (85%)              Above Norm 2 (15%)   BOT-2 SF             Standardized Score 50.9 (6.5) 40.0 – 61.0 47.0 – 54.9           Percentile Score 52.9 (22.5) 16.0 – 86.0 55.5 – 89.0 BOT-2 Descriptive Category               Below Average 1 (8%)              Average 9 (69%)               Above Average 3 (23%)   Abbreviations: PAQ-C: Physical Activity Questionnaire for Older Children; 6MWD: 6 minute walk distance; BOT-2 SF: Bruininks-Oseretsky Test of Motor Proficiency, 2nd Edition Short Form; SDS: standard deviation score.    38  Table 4 – Means and Mann-Whitney U Test statistics in Outcome Measures between Healthy Weight and Overweight/Obese Children  Outcome Measures Mean Mean Ranks U Z Effect size, r 1-tailed P-value HW n = 7 OWO n = 6 HW n = 7 OWO n = 6  6MWD SDS -0.63 -2.78 9.86 3.67 1.0 -2.857 0.8 < 0.01 6MWD (m) 595.9 484.3 9.14 4.50 6.0 -2.143 0.6 0.04 BOT-2 SF Standardized Score 54.7 46.5 9.00 4.57 7.0 -2.017 0.6 0.05 PAQ-C 3.1 3.1 6.93 7.08 20.5 -0.072 0.02 0.95 Abbreviations: HW: healthy weight, OWO, overweight or obese; PAQ-C: Physical Activity Questionnaire for Older Children; 6MWD: 6 minute walk distance; BOT-2 SF: Bruininks-Oseretsky Test of Motor Proficiency, 2nd Edition Short Form; SDS: standard deviation score.  Table 5 – Means and Mann-Whitney U Test Statistics for Outcome Measures between ALL Risk Level Groups   Outcome Measures Mean Mean Ranks U Z Effect size, r 1-tailed P-value Standard Risk n = 9 High Risk n = 4 Standard Risk n = 9 High Risk n = 4 6MWD SDS -1.28 -2.39 7.89 5.00 10.0 -1.234 0.3 0.26 6MWD (m) 563.2 502.1 7.89 5.00 10.0 -1.234 0.3 0.26 BOT-2 SF Standardized Score 51.7 49.3 7.00 7.00 18.0 0 0 1.00 PAQ-C 3.0 3.3 5.89 9.50 8.0 -1.545 0.4 0.15 Abbreviations: PAQ-C: Physical Activity Questionnaire for Older Children; 6MWD: 6 minute walk distance; BOT-2 SF: Bruininks-Oseretsky Test of Motor Proficiency, 2nd Edition Short Form; SDS: standard deviation score.    39  Table 6 - Means and Mann-Whitney U Test Statistics for Outcome Measures between Anthracycline Cardiotoxicity Risk Groups Outcome Measures Mean Mean Ranks U Z Effect size, r 1-tailed P-value Low Toxicity n = 9 Mod. Toxicity n = 4 Low Toxicity n = 9 Mod. Toxicity n = 4 6MWD SDS -1.48 -1.95 7.56 5.75 13.0 -0.772 0.2 0.50 6MWD (m) 565.0 498.0 8.00 4.75 9.0 -1.389 0.4 0.20 BOT-2 SF Standardized Score 52.9 46.6 7.78 5.25 11.0 -1.089 0.3 0.33 PAQ-C 3.0 3.3 6.06 9.13 9.5 -1.313 0.4 0.20 Abbreviations: PAQ-C: Physical Activity Questionnaire for Older Children; 6MWD: 6 minute walk distance; BOT-2 SF: Bruininks-Oseretsky Test of Motor Proficiency, 2nd Edition Short Form; SDS: standard deviation score.     40  Figure 1 - Scatter Plot of PAQ-C Scores and BOT-2 SF Standardized Scores  Abbreviations: PAQ-C: Physical Activity Questionnaire for Older Children; BOT-2 SF: Bruininks-Oseretsky Test of Motor Proficiency, 2nd Edition Short Form.        BOT – 2 SF Standardized Score PAQ-C Score 41  Figure 2 - Scatter Plot of PAQ-C Scores and 6MWD SDS  Abbreviations: PAQ-C: Physical Activity Questionnaire for Older Children; 6MWD: 6 minute walk distance; SDS: standard deviation score. PAQ-C Score 6MWD SDS 42  Chapter 3: Conclusion 3.1 Primary Objective and Hypothesis The primary objective of this pilot study was to examine if motor performance and physical function are associated with PA levels in children ages 8 – 13 years old who have completed treatment for ALL within the last 3 – 36 months. The hypothesis was lower PA levels would be associated with lower motor performance and lower physical function. In the current study, PA was not associated with motor performance, using the BOT-2 SF, or physical function, using the 6MWT. To our knowledge, this is the first study to have characterized and studied the association between motor performance, physical function, and PA in children who have recently completed treatment for ALL. The lack of observed association may be due to a small sample size of 13 participants, or may also suggest self-report PA levels may not be strongly associated with objective measures of motor performance or physical function in children who have completed treatment for ALL. The lack of observed association may also suggest PA levels in these children are influenced by other factors, such as parental/peer support and self-efficacy in children shortly after completing treatment73. 3.2 Effect of BMI on Outcome Measures Seven participants (54%) had a BMI in the healthy weight range, and six participants (46%) were overweight or obese.  The percentage of participants who were overweight or obese was higher than observed in the general population of children in Canada. Using data from 2009 – 2011 Statistics Canada115 for children between ages of 5 – 17 years old,  20% of children were overweight and 12% were obese (32% total).  In the current study, children categorized as healthy weight children performed better for their age group in both the BOT-2 SF and 6MWT compared with children who were overweight 43  and obese. In addition, the 6MWD SDS was significantly correlated with BMI SDS, where an increase in one BMI SDS was associated with a decrease in 0.70 6MWD SDS. This observed relationship between BMI and 6MWT is consistent with previous studies in healthy children and children who have completed treatment for ALL. Geiger et al.114 reported that healthy children with higher BMI had lower 6MWDs, and Hartman et al.7 found a weak negative association between BMI SDS and 6MWD SDS. The difference in BOT-2 SF standardized score between healthy weight children and children who were overweight or obese trended towards significance. In children with a cancer diagnosis, increased BMI has been shown to be related to reduced motor performance116. Finally, no difference in PA levels was found between children who were healthy weight and children who were overweight or obese, which was similar to the findings from Florin et al.66 study on PA in adult survivors of childhood ALL. 3.3 Relationship of PA with Motor Performance and Physical Performance  Although motor performance has been shown to be associated with PA levels in healthy children 49,82, only a few studies have recently examined the association of PA with motor performance and physical function in children who have completed treatment for ALL.  The results to date have been inconsistent. Similar to the current study, Hartman et al.7 found no significant difference in 6MWD between children who did and did not participate in sports in 34 children who completed treatment for ALL. The study measured motor performance, but did not analyze its association with sports participation. Contrary to the current study, Taskinen et al.14 studied 45 childhood ALL survivors and found an association between self-report PA and physical function. Children who reported exercising more than three times per week had better overall muscle performance measures than children who reported exercising less than three times per week. Muscle performance was assessed by six physical performance tests administered by a 44  physiotherapist, namely the leg-lift, repeated squatting, sit-up, sit-and-reach, back extension, and shuttle run tests. Hoffman et al.13 found an association between PA and 6MWD, where children who reported more minutes of weekly PA had greater 6MWD. Chung et al.12 used a self-report PA questionnaire and an open-ended question to investigate the factors affect PA levels in childhood cancer survivors of mixed diagnosis in Hong Kong and found PA levels to be lower in these survivors, and physical factors, such as self-reported fatigue and self-reported decrease in physical strength and endurance, were reasons for lowered PA levels, as well as prioritizing academic performance over PA.    3.4 Comparison of Outcome Measures with Published and Normative Data 3.4.1 Physical Activity The PA levels observed in the current study were comparable to those observed in a previous study of non-cancer children in United Kingdom117 and Canada118, which also used the Physical Activity Questionnaire for Older Children. Tomlin et al.119 used the same measure to capture sports participation and examined sport drinks consumption in children without a cancer diagnosis. This cross-sectional study separated children into two groups, namely children who participated in organized sports and those who did not.  The study participants were school aged children with an average age of 9.9 years in the non-sports group and 9.9 years in the sports group. In the non-sports group (n = 295 females and 204 males) scored 2.9 on the PAQ-C, and the sports group (n = 441 females and 445 males) scored 3.3. Participants in the current study scored an average of 3.1, which was lower than the group of healthy children who participated in organized sport. However, the 95% CI for the PAQ-C Score in the current study was 2.8 – 3.4, which includes both the non-sport group and sport group. These results did not provide confidence to conclude if participants in the current study were comparable to the non-sport 45  group or sport group. Furthermore, the designation of group, either non-sport or sport, was based on a single question asking whether or not children participated in organized sports. The authors of the study noted a limitation of using this method to measure sport participation was that it does not provide information on the quality of PA119. Previous studies have found PA levels in childhood ALL patients and survivors to be lower compared to their healthy counterparts. Chung et al.12 found significantly lower PA levels from before diagnosis to time of study participation (64.8% of participants having been off treatment for 24 months) in childhood cancer survivors of mixed diagnosis. Winter et al.9 completed a systematic review and found five studies measuring PA after treatment (1.5 years to 10 years from treatment). A reduced levels of PA was observed compared with healthy controls in three studies with self-report measures 60,61,63, one with heart-rate monitors59, and one with accelerometers62.  3.4.2 Motor Performance  The current study showed similar results to previous studies who have characterized motor performance in ALL survivors using the BOT-2. Ramchandren et al.37 used the first edition of the BOT and found 5% of patients performed below average compared with standardized norms, which is consistent with the findings of the current study, in which one participant performed below average (8%). De Luca et al.50 used the BOT-2 SF and found 16.2% (6/37) of participants performed below average, which is consistent with the percentage of people with motor impairments (17%) in the normal population. However, the average standardized BOT-2 SF score in the De Luca study was 51, which is comparable to the average standardized score of 50 observed in the current study. 46   In addition, the 95% CI for the BOT-2 SF standardized score were within the range of “Average” score (40 – 60)108 for motor performance, which suggests the motor performance of ALL children in the current study was “Average.” For studies using the Movement Assessment Battery for Children (MABC), the systematic review by Green et al.32 included five studies, and reported 25 – 54% of participants had gross or fine motor impairments. In a more recent study, not included in the review and also used the MABC-2, De Luca et al.50 reported 27% (10/37) of participants performing lower than norms. Hartman et al.7 used the MABC-2, and reported 38% (10/34) of participants were “at risk for impairment” at end of treatment, but performed with normal scores at 5-year follow-up. Only one participant was reported to be “at risk for impairment” at end of treatment and 5-year follow-up.  Other motor performance measurement tools have been used in children with ALL. Beulertz et al.51 used the MOT 4-6 and the DMT 6-18 to test motor performance in children ages 4 – 6 years old and 6 – 18 years old, respectively. While 27% of all participants’ performance below average, all children ages 4 – 6 performed normal and 34% of children ages 6 – 17 performed below average. Leone et al.49 reported 48.2% of participants were found to have impairments in gross motor skills using the University of Quebec in Chicoutimi and Montreal (UQAC-UQAM) motor skills battery tests.   A previous study50 and the current study used the BOT-2, or the first edition of the BOT37, and found lower incidences of motor performance impairment compared to studies who have used the MABC-2 or other motor performance measurement tools. This observation supports the work of De Luca et al.50 who proposed the BOT-2 SF is not as sensitive a measure of motor performance as the MABC-2. De Luca et al.50 reasoned the BOT-2 SF was designed as 47  a screening assessment and is considered to have purer, relatively simple, repetitive motor tests. In contrast, MABC-2, which includes motor skill tests requiring stronger motor planning and cognitive effort, may be more sensitive to the subtle impairments reported in childhood ALL survivors50. Furthermore, the differences in assessment tools make it difficult to compare the results across studies using other assessment tools.    The current study did not find a significant difference in motor performance by ALL risk level group or anthracycline cardiotoxicity groups. This finding was similar to Hartman et al.7, where treatment regimens had no effect on motor performance at the end of treatment. However, at 5-year follow-up, Hartman et al.7 found High Risk children had significantly better motor performance compared with Non-High Risk children. Taskinen et al.14 also found no significant difference with individual muscle performance tests and overall muscle performance between ALL risk level group.  3.4.3 Physical Function  For the 6MWT, the 95% CI for the measured 6MWD fell below the 95% CI for the calculated 6MWD, and the 95% CI 6MWD SDS was less than 0, both of which suggested the ALL children in the current study did not walk as far and had lower physical function compared with healthy children. The 6MWT results in the current study are consistent with previous studies in showing impairment in physical function in many childhood cancer survivors. Hartman et al.7 found all 34 ALL participants walked a shorter distance compared with normative values an average of 5.2 years after treatment. Hoffman et al.13 studied 183 patients of mixed cancer diagnosis, and reported patients had a lower 6MWD by 27 m compared to siblings. Hooke et al.55 tested children who were on treatment for ALL and followed them throughout 48  treatment cycles. After three treatment cycles, 93% of patients performed one or more standard deviations below the norm.  3.5 Fatigue Based on the study results, it could not be concluded if the children in the current study were fatigued after completing treatment for ALL. The mean scores from the PedsQL™ Multidimensional Fatigue Scale for Total Fatigue, GF, SRF, and CF were 74.6 (95% CI: 67.9 – 81.3), 82.7 (95% CI: 76.4 – 89.0), 70.2 (95% CI: 61.0 – 79.4), and 74.6 (95% CI: 58.5 – 83.1),  respectively. Varni et al.107 tested the validity and reliability of the PedsQL™ Multidimensional Fatigue Scale in 220 childhood cancer patients and survivors of mixed diagnoses (50% leukemia patients) ages 5 – 18 years old (mean age not reported). The mean scores from the PedsQL™ Multidimensional Fatigue scores for children who were off treatment for more than 12 months for Total Fatigue, GF, SRF, and CF were 74.6, 79.3, 72.8, and 71.63, In the same study, the scores for children without a cancer diagnosis for Total Fatigue, GF, SRF, and CF were 80.5, 85.3, 75.0, and 81.1, respectively. The scores for overall fatigue and the three dimensions of fatigue between children without a cancer diagnosis and children who were off treatment were not statistically different. The mean scores from the PedsQL™ Multidimensional Fatigue scores for on-treatment children for Total Fatigue, GF, SRF, and CF were 68.5, 71.4, 63.43, and 70.8, respectively. Although the mean scores for overall fatigue and all three fatigue dimensions for the children off treatment for 12 months and children without a cancer diagnosis were both within the 95% CI for the mean scores for the current study, the mean scores for Total Fatigue, SRF, and CF for children on treatment also fell within the 95% CI. These results did not provide confidence to conclude that the measured fatigue scores for the current study were comparable to the scores of the childhood cancer patients or to the children without a cancer diagnosis in the 49  Varni et al.107 study. Therefore, whether or not the children in the current study were fatigued after completing treatment for ALL was unclear.   The current study did not find fatigue to be associated with PA, motor performance, and physical function, which was inconsistent with the findings from previous studies. Fatigue has been suggested to be a significant symptom related to cancer treatment for ALL that can interfere with childhood developmental experiences and engagement in PA while the children are undergoing treatment46. Hooke et al.54 reported that 6MWD increased when fatigue levels decreased in children and adolescents receiving chemotherapy treatment.  An observational study investigating chronic fatigue in 102 long-term survivors of childhood lymphomas and leukemia found survivors with persistence chronic fatigue had reduced PA levels120. Hooke et al.55 observed an overall decrease in self-report fatigue from the first to the third cycle of treatment. The authors suggested this decrease in fatigue was because the third cycle of treatment does not include dexamethasone, which has been known to be associated with fatigue in ALL patients during treatment26, and the side effects would have diminished during the third cycle of treatment54. Although fatigue has been reported in long-term survivors of childhood ALL120, the inconclusive data regarding whether or not the current study participants were fatigued may have influenced the ability to detect an association between fatigue PA, motor performance, and physical function.  3.6 Study Strengths The current study had several strengths. First, to our knowledge, the current study was the first to use validated measurement tools to investigate the association between PA, motor performance, and physical function. Only one study13 used a PA questionnaire validated in health populations and children with chronic disease (Past-Year Leisure-Time Physical Activity 50  section of the Modifiable Activity Questionnaire). The other two studies7,14 that investigated physical factors associated with PA used unstandardized interview-based forms of measuring PA and sporting participation. Hartman et al.7 only examined the association between 6MWT and PA, but used an unstandardized tool to measure PA. To our knowledge, Hoffman et al.13 was the only study to date with standardized measurement tools for physical function and PA to study factors associated with PA. However, this association was studied in a population of mixed childhood cancer diagnosis, which may have affected the homogeneity of the study sample and making it difficult to examine the effects of treatment and diagnosis on PA and physical function13. Second, to our knowledge, the current study was the first to focus on understanding the physical factors influencing PA in children ages 8 – 13 years old who have completed treatment within 3 – 36 months in children. Previous studies included patients well after they have completed treatment with an median years off treatment ranging from 5.27 – 6.314 years, or 9.3 years after diagnosis13, and the age of the children included in these studies varied, with studies including children ages 9.2 – 20.1 years old14, 9.0 – 18.7 years old7, and 9 – 18 years old with a mean age of 13.5 years13. Third, this study also demonstrated the feasibility of performing motor performance and physical function tests as part of regular oncology follow-up visits in a hospital setting. 3.7 Study Limitations The current study has several limitations which should be considered in interpretation of the study results. First, with a small sample size of 13 children, the study was under powered to find a significant association between our primary outcomes, and potentially allowed for type-2 errors, false negatives, to occur. The absolute effect sizes (Spearman’s rho coefficient) of non-significant associations ranged from 0.077 – 0.515, with the upper bound of this range being 51  considered as associations with relatively large effect sizes. Associations between PA, motor performance, and physical function, and other exploratory associations, with relatively large effects sizes may have been statistical significance if a larger sample size was included in the current study. Also, the mean measured 6MWD, 6MWD SDS, and BOT-2 SF standardized score were not statistically different by ALL risk group and anthracycline cardiotoxicity groups.  Both of these group comparisons may have reached statistical significance with a larger sample size. With only 21 eligible patients identified within eight months, the participation rate (62%) was higher than anticipated, which implies it may be feasible for future studies to achieve a larger sample size.  The second limitation was participants in the current study may not be representative of all children who have completed treatment for ALL because of potential participation bias.  The study may have attracted participants and parents who were more physically active and/or concerned about physical function and motor performance.  The third limitations of the current study was the cross-sectional, observational study design of the study, which did not allow for analysis involving the changes in PA, motor performance, and physical function across the time course of cancer treatment.  The fourth limitation involved the outcome measures used. The PAQ-C is a self-report PA questionnaire designed to be completed by school-aged children. Self-report PA questionnaires in children have issues with recall bias. Children tend to have greater recall accuracy for short, sporadic types of PA, which would cause overall self-report PA to be irregular, with greater recall for higher intensity PA, and lower overall recall accuracy121. However, compared to objective measures of PA, such as activity monitors, self-report measurement tools are easy to administer, inexpensive, and relatively low burden to participants. 52  Another measurement option was a parental proxy measure, where parents and guardians estimate their child’s PA levels, but these forms of PA measurement have been reported to have poor reliability and validity122. Furthermore, the PAQ-C only provides a final score and does not individually quantify the duration, type, intensity, and frequency of PA, making it difficult to compare with PA recommendations, guidelines and other forms of PA measurements. The PAQ-C also measures PA during school, making it difficult to capture PA during the summer and winter holidays. Finally, the PAQ-C does not have published normative references for ease of comparison. Although more expensive and difficult to manage, the use of activity monitors would allow researchers to quantify duration, intensity, type, and frequency of PA objectively.  To measure motor performance, the BOT-2 SF was useful due to its relative ease of training and administration, acceptable inter-rater, test-retest, validity (Section 2.5.2.2.1), and ability to determine a standardized score for normative reference. However, the BOT-2 SF did not allow for separate analysis of gross and fine motor scores.  Also, BOT-2 SF may not be as sensitive of a measure in capturing motor impairments in childhood ALL survivors compared to the MABC-250. However, greater sensitivity does not imply greater accuracy in identifying motor performance impairments in this population. BOT-2 SF was designed to be a screening tool and includes purer, relatively simple, repetitive motor performance tests50, which may be a useful clinical tool in identifying those with greater impairments. However, it may not be sensitive for early detection of motor performance impairments. The MABC-2 tests motor performance skills requiring stronger motor planning and cognitive effort50, and it may be a useful clinical tool to distinguish fine and gross motor performance. Future studies should investigate the feasibility of using the MABC-2 and BOT-2 SF for identifying motor performance impairments in childhood ALL survivors in both research and clinical settings.  53  The 6MWT depends on participant motivation and interest in the task, which may have affected the results of the study52. The current study used the ATS guidelines to administer the test in a standardized manner. Study assessments done in a hospital setting may have been associated with medical procedures routinely encountered throughout their treatment and follow-up appointments, and affected the child’s motivation and interest in performing the study assessments. The current study used the Geiger et al.114 for the normative reference data, tested children in a school setting. Although the authors attempted to prevent competition between children by testing the children in smaller groups and in several separate locations, the knowledge of peers participating in a research study can motivate competition between children and influence scores114. Further, the Geiger study modified the standardized ATS52 script for the 6MWT, which is designed for all age groups, to help children interpret what “as far as possible” means by including “which means score as many meters as possible in 6 minutes”114 (pg. 396). Although this modification may have motivated children to walk a further distance to better reflect their physical function, comparison between studies may not be as valid. Finally, the standardized distance of the course set by the ATS is 60 m, but the current study used a pre-existing 50 m track at the British Columbia Children’s Hospital and may have affect the results of the 6MWT.  3.8 Future Studies Future studies investigating the factors influencing PA levels in childhood ALL survivors may want to include the following considerations. The first consideration would be to use an objective measure for PA, such as pedometers or accelerometers, which may provide the potential for higher accuracy in measuring PA in youths by allowing time-resolution and more information on the intensity of the exercise bout123. The second consideration is the measurement 54  tool for motor performance. Although the most suitable motor performance test to assess childhood cancer patients remains unclear, emerging evidence suggests the MABC-2 may be more sensitive in identifying motor performance impairments in childhood ALL survivors compared with the BOT-2 SF.  However, research is needed to determine if the MABC-2 is detecting true motor impairments or false-positive results. The MABC-2 can provide similar ease of administration and allows for normative reference analysis for the total score like the BOT-2 SF, as well as individual analysis for motor performance tasks involving manual dexterity, aiming/catching, and balance. The third consideration would be to test the validity and reliability of a revised script for the 6MWT designed for healthy children and clinical populations of children, which may help to improve interest and motivation in children to produce results in the 6MWT truly reflective of their physical function.  The fourth consideration would be to adopt a longitudinal study design to include measures starting from pre-treatment and follow children throughout and after their treatment to capture the trajectory of changes in, and associations between, PA, motor performance, and physical function.  Finally, given the lack of associations found in the current study among the measured physical outcomes and PA levels, future studies may want to explore psychosocial variables associated with PA, such as PA self-efficacy76.  PA self-efficacy is defined as the belief in one’s own ability to organize and perform PA, which has been shown to significantly influence PA behaviour in healthy children124. A recent study conducted by Gilliam et al.73 investigated the extent to which self-efficacy mediated the relationship between social support and PA levels in 105 childhood cancer survivors ages 8 – 16 years old.  Both self-efficacy and social support were directly associated with PA levels, and higher levels of peer and family support for PA were associated with higher levels of PA through increased self-efficacy. Other studies in childhood 55  cancer survivors also showed similar results, with PA levels in childhood cancer survivors being associated with PA self-efficacy61,64,77.  3.9 Implications of Study Results A recent large survey study investigating a large population of adult survivors of childhood ALL (n = 2648) reported survivors were more likely to be less physically active compared with the general population, and these lower levels of PA may be associated with increased risk of developing health issues, such as cardiovascular disease, obesity, osteoporosis, and all-cause mortality66. Therefore, completion of treatment may be a suitable time to reintroduce PA to avoid the persistent low PA levels noted in ALL survivors many years after treatment9. Previous studies have found PA levels were reduced in children actively receiving treatment70,71. Maintenance therapy, which is final stage of treatment and suggested to be the less intensive phase of treatment, has also been considered a suitable time for PA intervention and promotion17. Almost all participants in the current study had lower levels of physical function compared to normative values in healthy children. Furthermore, significant differences in physical function scores were found between healthy weight children and overweight or obese children. This finding is important because pediatric17 and adult16 survivors of ALL have been reported to have higher risk of developing obesity, and associated risks for developing cardiovascular disease125. Based on the study findings, physical therapy programs should focus on improving physical function and weight management in children who have just completed treatment for cancer. Furthermore, despite the fact that a small percentage of participants in the current study performed below average in the motor performance tests, motor performance impairments have 56  been reported to be present in as many as 54% of participants in previous studies32. Therefore, physical therapy programs should consider focusing on motor performance and skills assessment in this population. The implementation of physical function and motor performance assessments as part of follow-up appointments was shown to be feasible in the current study.   Motor performance has been associated with PA levels in healthy children49, but the contribution of motor performance on PA in ALL survivors remains unclear. A randomized trial has been conducted by Hartman et al.38 to investigate whether an exercise program can prevent side effects of treatment (reduced bone mineral density, altered body composition, impaired motor performance, and passive ankle dorsiflexion). The study found no difference between standard care and the exercise program, and reported the null findings were due to low program adherence. Although physiotherapist-led education sessions were given parents and children regarding the side-effects of chemotherapy and the importance of exercise, parents reported the two main reasons for not adhering to program exercises were that the child was physically unable to perform daily exercise or that regular daily exercise did not seem necessary38. However, follow-up sessions were conducted at six weeks, may have been too long for appropriate encouragement to maintain participation in the program38.  Takken et al.92 conducted a 12-week aerobic and strength exercise training program in nine pediatric ALL survivors with an average age of 9.3 years old, who had completed treatment within 12 – 36 months. The study assessed muscle strength using a hand held dynamometer, functional mobility using the timed up-and-go, and cardiopulmonary fitness with exercise testing. Similar to Hartman et al.38, the study only had four participants complete the intervention and found no differences in the study outcomes after completing the intervention. The authors suggested program adherence was a problem. Stages of disease, age of children, variety of 57  exercises, location of the intervention, and, most importantly, views and motivation of parents regarding participating in an exercise training program were key factors related to adherence. Considering these issues could potentially increase program adherence and lead to better exercise training effects from these programs92.  3.10 Conclusion In conclusion, the current study did not find an association between PA, motor performance, and physical function in children who had completed treatment for ALL. However, with a small sample size of 13 participants, the current study was not able to conclude PA in children who have completed treatment for ALL was not related to their physical function and motor performance. BMI was associated with 6MWD and 6MWD SDS, suggesting improvements in BMI status can potentially promote PA through improvements in physical function. Future studies should include a larger sample size, potentially from multiple centres to help achieve sufficient recruitment. Furthermore, a longitudinal design including baseline, objective measurements of PA at key time-points throughout and beyond treatment, may be important to enhance the understanding of the relationship between PA and physical factors in childhood ALL patients, how PA and physical factors change throughout treatment, and help to inform PA interventions during maintenance therapy and following treatment completion17.  Finally, including measures of psychosocial factors, such as self-efficacy, to determine the integrative impact of both physical and psychosocial factors influencing PA, may be important.  The current study helped to inform the need for PA interventions in children who have completed treatment for ALL, and demonstrated the feasibility of assessing motor performance and physical function as part of oncology follow-up. These findings can be used to help improve 58  PA levels in childhood ALL survivors, potentially through improving the BMI status of children who have completed treatment for ALL. 59  Bibliography 1. Stanulla M, Schrappe M. Treatment of childhood acute lymphoblastic leukemia. Seminars in hematology. 2009;46(1):52-63. 2. Pui CH, Mullighan CG, Evans WE, Relling MV. Pediatric acute lymphoblastic leukemia: where are we going and how do we get there? Blood. 2012;120(6):1165-1174. 3. Canadian Cancer Society. 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Bauman AE, Reis RS, Sallis JF, et al. Correlates of physical activity: why are some people physically active and others not? Lancet. 2012;380(9838):258-271. 125. Nottage KA, Ness KK, Li C, Srivastava D, Robison LL, Hudson MM. Metabolic syndrome and cardiovascular risk among long-term survivors of acute lymphoblastic leukaemia - From the St. Jude Lifetime Cohort. Br J Haematol. May 2014;165(3):364-374.  75  Appendices Appendix A  - Letter of Invitation  76  Appendix B  - Parent Consent Form          77  78  79  80  81      82   83  Appendix C  - Child Assent Form 84    85  Appendix D  - Medical Data Collection Form 86  Appendix E  - Physical Assessment Data Collection Form   87  Appendix F  - End of Study Letter to Participants   88   89  Appendix G  - Parking Reimbursement Form  

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