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Name of Journal: World Journal of TransplantationESPS Manuscript NO: 24345Manuscript Type: Original ArticleRetrospective Cohort StudyRisk factors for fracture in adult kidney transplant recipientsNaylor et al. Fracture risk factors in kidney transplantationKyla L Naylor, Guangyong Zou, William D Leslie, Anthony B Hodsman, Ngan N Lam, Eric McArthur, Lisa-Ann Fraser, Gregory A Knoll, Jonathan D Adachi, S Joseph Kim, Amit X GargKyla L Naylor, Amit X Garg, S Joseph Kim, Eric McArthur, Institute for Clinical Evaluative Sciences (ICES), London, Ontario, N6A 4G5, CanadaKyla L Naylor, 2nd Institute of Health Policy, Management and Evaluation, University of Toronto, Ontario, M5T 3M6, CanadaGuangyong Zou, Amit X Garg, Department of Epidemiology and Biostatistics, Western University, London, Ontario, N6A 5C1, CanadaWilliam D Leslie, Department of Medicine, University of Manitoba, Winnipeg, Manitoba, R2H 2A6, CanadaAnthony B Hodsman, Amit X Garg, Division of Nephrology, Western University, Ontario, N6A 5W9, CanadaNgan N Lam, Division of Nephrology, University of Alberta, Edmonton, Alberta, T6G 2G3, CanadaLisa-Ann Fraser, Division of Endocrinology, Western University, Ontario, N6A 5A5, CanadaGregory A Knoll, Division of Nephrology, Kidney Research Centre, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, K1H 7W9, CanadaJonathan D Adachi, Division of Rheumatology, McMaster University, Hamilton, L8S 4K1, CanadaS Joseph Kim, Division of Nephrology, University Health Network, University of Toronto, Toronto, M5G 2C4, CanadaAuthor contributions: All authors contributed to revising the manuscript. Institutional review board statement: This study was approved by the institutional review board at Sunnybrook Health Sciences Centre, Toronto, Canada. Informed consent statement: Data was obtained from data holdings at the Institute for Clinical Evaluative Sciences (ICES). ICES is named as a prescribed entity in Ontario’s privacy law Personal Health Information Protection Act. Prescribed entity status means that health information custodians of all types can legally disclose personal health information to ICES without informed consent for purposes of analysis, evaluation and compiling statistical information about our health care system. Conflict-of-interest statement: William Leslie: Speaker bureau: Amgen, Eli Lilly, Novartis. Research grants: Amgen, Genzyme. Jonathan Adachi: Speaker/Consultant: Amgen, Eli Lilly, Merck, Novartis, Warner Chilcott. Clinical Trials: Amgen, Eli Lilly, Merck, Novartis. Greg Knoll has received investigator-initiated research grants from Astellas, Pfizer, Roche and Novartis. Amit Garg received an investigator-initiated grant from Astellas and Roche for a Canadian Institutes of Health Research study in living kidney donors. The other authors declare that they have no competing interests.Data sharing statement: No additional data are available.Open-Access: This article is an open-access?article?which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed?in?accordance?with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: to: Dr. Kyla L Naylor, Institute for Clinical Evaluative Sciences, Room ELL-111, Westminster, London Health Sciences Centre, 800 Commissioners Road East, London, Ontario, N6A 4G5, Canada. kyla.naylor@ices.on.caTelephone: +1-519-6858500 Fax: +1-519-6858269Received: January 19, 2016Peer-review started: January 20, 2016First decision: March 24, 2016Revised: April 7, 2016Accepted: June 1, 2016Article in press: Published online: AbstractAIM: To determine the general and transplant-specific risk factors for fractures in kidney transplant recipients.METHODS: We conducted a cohort study of all adults who received a kidney-only transplant (n = 2723) in Ontario, Canada between 2002 and 2009. We used multivariable Cox proportional hazards regression to determine general and transplant-specific risk factors for major fractures (proximal humerus, forearm, hip, and clinical vertebral). The final model was established using the backward elimination strategy, selecting risk factors with a P-value ≤ 0.2 and forcing recipient age and sex into the model. We also assessed risk factors for other fracture locations (excluding major fractures, and fractures involving the skull, hands, or feet). RESULTS: There were 132 major fractures in the follow-up (8.1 fractures per 1000 person-years). General risk factors associated with a greater risk of major fracture were older recipient age (adjusted hazard ratio (aHR) per 5-year increase 1.11, 95%CI: 1.03-1.19) and female sex (aHR = 1.81, 95%CI: 1.28-2.57). Transplant-specific risk factors associated with a greater risk of fracture included older donor age (5-year increase) (aHR = 1.09, 95%CI: 1.02-1.17) and end-stage renal disease (ESRD) caused by diabetes (aHR = 1.72, 95%CI: 1.09-2.72) or cystic kidney disease (aHR = 1.73, 95%CI: 1.08-2.78) (compared to glomerulonephritis as the reference cause). Risk factors across the two fracture locations were not consistent (major fracture locations vs other). Specifically, general risk factors associated with an increased risk of other fractures were diabetes and a fall with hospitalization prior to transplantation, while length of time on dialysis, and renal vascular disease and other causes of ESRD were the transplant-specific risk factors associated with a greater risk of other fractures.CONCLUSION: Both general and transplant-specific risk factors were associated with a higher risk of fractures in kidney transplant recipients. Results can be used for clinical prognostication.Key words: Fracture; Risk factors; Kidney transplant recipient; Prognostication; Cohort study? The Author(s) 2016. Published by Baishideng Publishing Group Inc. All rights reserved.Core tip: We examined risk factors for major and other fractures in adult kidney transplant recipients. Increasing age and female sex were associated with an increased major fracture risk, while diabetes or cystic kidney disease as the cause of end-stage renal disease and increasing age of the kidney donor were the transplant-specific risk factors associated with an increased major fracture risk. Risk factors were variable across fracture locations (major vs other fractures). General and transplant-specific risk factors for fracture should be considered when assessing fracture risk in kidney transplant recipients. Different risk factors may need to be considered depending on the fracture location.Naylor KL, Zou GY, Leslie WD, Hodsman AB, Lam NN, McArthur E, Fraser LA, Knoll GA, Adachi JA, Kim SJ, Garg AX. Risk factors for fracture in adult kidney transplant recipients. World J Transplant 2016; In pressINTRODUCTIONKidney transplant recipients are at a higher risk of fracture compared to the general populationPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5SYW1zZXktR29sZG1hbjwvQXV0aG9yPjxZZWFyPjE5OTk8

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ADDIN EN.CITE.DATA [1-4]. Reasons for the increased fracture risk are multifactorial, and may include perturbations in bone and mineral metabolism that occur in renal bone disease, and the administration of glucocorticoids after transplantation ADDIN EN.CITE <EndNote><Cite><Year>2009</Year><RecNum>1168</RecNum><DisplayText>[5]</DisplayText><record><rec-number>1168</rec-number><foreign-keys><key app="EN" db-id="s9zd0vtsjaxsd9eeswv5szvqwett0fs0v59r">1168</key></foreign-keys><ref-type name="Book">6</ref-type><contributors></contributors><titles><title>KDIGO clinical practice guidelines for the prevention, diagnosis, evaluation, and treatment of Chronic Kidney Disease-Mineral and Bone Disorder (CKD-MBD)</title></titles><dates><year>2009</year></dates><publisher>Kidney international. Supplement. (113) (pp S1-130), 2009. Date of Publication: Aug 2009.</publisher><isbn>0098-6577</isbn><urls><related-urls><url> Technologies</remote-database-provider><language>English</language></record></Cite></EndNote>[5]. However, the risk factors for fracture after transplant remain uncertain. In a recent systematic review many classical risk factors for fracture in the general population (e.g., older age, female sex) were inconsistently associated with fractures in kidney transplant recipientsPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5OYXlsb3I8L0F1dGhvcj48WWVhcj4yMDEzPC9ZZWFyPjxS

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ADDIN EN.CITE.DATA [6]. Unlike the transplant population, risk factors for fracture in the general population are well-established and are included in the World Health Organization’s (WHO) Fracture Risk Assessment tool (FRAX). FRAX is used to guide treatment decisions in the general population by incorporating age, sex, clinical risk factors (body mass index, parental hip fracture, glucocorticoid use, rheumatoid arthritis, smoking, alcohol intake ≥ 3 units per day), and hip bone mineral density (optional) to predict the 10-year probability of hip fracture or major osteoporotic fracture (proximal humerus, forearm, hip, or clinical vertebral)PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5QYXBhaW9hbm5vdTwvQXV0aG9yPjxZZWFyPjIwMTA8L1ll

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ADDIN EN.CITE.DATA [7-9]. However, kidney transplant recipients may have different risk factors for fracture given the unique pathophysiology that underlies their bone disease ADDIN EN.CITE <EndNote><Cite><Author>Weisinger</Author><Year>2006</Year><RecNum>1109</RecNum><DisplayText>[10]</DisplayText><record><rec-number>1109</rec-number><foreign-keys><key app="EN" db-id="s9zd0vtsjaxsd9eeswv5szvqwett0fs0v59r">1109</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Weisinger, Jose R.</author><author>Carlini, Raul G.</author><author>Rojas, Eudocia</author><author>Bellorin-Font, Ezequiel</author></authors></contributors><auth-address>Division of Nephrology, Hospital Universitario de Caracas, Universidad Central de Venezuela, Caracas, Venezuela. jweising@.ve</auth-address><titles><title>Bone disease after renal transplantation</title><secondary-title>Clinical Journal of The American Society of Nephrology: CJASN</secondary-title><alt-title>Clin J Am Soc Nephrol</alt-title></titles><periodical><full-title>Clinical Journal of The American Society of Nephrology: CJASN</full-title><abbr-1>Clin J Am Soc Nephrol</abbr-1></periodical><alt-periodical><full-title>Clinical Journal of The American Society of Nephrology: CJASN</full-title><abbr-1>Clin J Am Soc Nephrol</abbr-1></alt-periodical><pages>1300-13</pages><volume>1</volume><number>6</number><keywords><keyword>*Bone Density</keyword><keyword>*Bone Diseases/ep [Epidemiology]</keyword><keyword>Bone Diseases/et [Etiology]</keyword><keyword>Bone Diseases/pa [Pathology]</keyword><keyword>Bone and Bones/pa [Pathology]</keyword><keyword>Humans</keyword><keyword>*Kidney Transplantation/ae [Adverse Effects]</keyword><keyword>Postoperative Complications/ep [Epidemiology]</keyword></keywords><dates><year>2006</year><pub-dates><date>Nov</date></pub-dates></dates><isbn>1555-905X</isbn><accession-num>17699362</accession-num><work-type>Research Support, Non-U.S. Gov&apos;t&#xD;Review</work-type><urls><related-urls><url>;[10]. For example, in a recent cohort study the only classical risk factor for fracture that reached statistical significance in kidney transplant recipients was high alcohol use ADDIN EN.CITE <EndNote><Cite><Author>Naylor</Author><Year>2014</Year><RecNum>3599</RecNum><DisplayText>[11]</DisplayText><record><rec-number>3599</rec-number><foreign-keys><key app="EN" db-id="s9zd0vtsjaxsd9eeswv5szvqwett0fs0v59r">3599</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Naylor, K. L.</author><author>Leslie, W. D.</author><author>Hodsman, A. B.</author><author>Rush, D. N.</author><author>Garg, A. X.</author></authors></contributors><auth-address>1 Division of Nephrology, Western University, London, ON, Canada. 2 Department of Epidemiology &amp; Biostatistics, Western University, London, ON, Canada. 3 Department of Medicine, University of Manitoba, Winnipeg, ON, Canada. 4 Institute for Clinical Evaluative Sciences (ICES), Toronto, ON, Canada. 5 Address correspondence to: William Leslie, Saint Boniface General Hospital, 409 Tache Avenue, Room C5102, Winnipeg, MB, R2H 2A6, Canada.</auth-address><titles><title>FRAX Predicts Fracture Risk in Kidney Transplant Recipients</title><secondary-title>Transplantation</secondary-title><alt-title>Transplantation</alt-title></titles><periodical><full-title>Transplantation</full-title><abbr-1>Transplantation</abbr-1></periodical><alt-periodical><full-title>Transplantation</full-title><abbr-1>Transplantation</abbr-1></alt-periodical><edition>2014/02/08</edition><dates><year>2014</year><pub-dates><date>Feb 5</date></pub-dates></dates><isbn>1534-6080 (Electronic)&#xD;0041-1337 (Linking)</isbn><accession-num>24503761</accession-num><urls><related-urls><url>;[11]; however, this study had only 21 fracture events and may have had inadequate statistical power to identify other risk factors ADDIN EN.CITE <EndNote><Cite><Author>Naylor</Author><Year>2014</Year><RecNum>3599</RecNum><DisplayText>[11]</DisplayText><record><rec-number>3599</rec-number><foreign-keys><key app="EN" db-id="s9zd0vtsjaxsd9eeswv5szvqwett0fs0v59r">3599</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Naylor, K. L.</author><author>Leslie, W. D.</author><author>Hodsman, A. B.</author><author>Rush, D. N.</author><author>Garg, A. X.</author></authors></contributors><auth-address>1 Division of Nephrology, Western University, London, ON, Canada. 2 Department of Epidemiology &amp; Biostatistics, Western University, London, ON, Canada. 3 Department of Medicine, University of Manitoba, Winnipeg, ON, Canada. 4 Institute for Clinical Evaluative Sciences (ICES), Toronto, ON, Canada. 5 Address correspondence to: William Leslie, Saint Boniface General Hospital, 409 Tache Avenue, Room C5102, Winnipeg, MB, R2H 2A6, Canada.</auth-address><titles><title>FRAX Predicts Fracture Risk in Kidney Transplant Recipients</title><secondary-title>Transplantation</secondary-title><alt-title>Transplantation</alt-title></titles><periodical><full-title>Transplantation</full-title><abbr-1>Transplantation</abbr-1></periodical><alt-periodical><full-title>Transplantation</full-title><abbr-1>Transplantation</abbr-1></alt-periodical><edition>2014/02/08</edition><dates><year>2014</year><pub-dates><date>Feb 5</date></pub-dates></dates><isbn>1534-6080 (Electronic)&#xD;0041-1337 (Linking)</isbn><accession-num>24503761</accession-num><urls><related-urls><url>;[11]. The same study also found that FRAX may be a useful tool to predict fracture in kidney transplant recipients (area under the receiver operating curve 0.62); however, the authors hypothesized that incorporating transplant-specific risk factors for fracture may further improve the performance of FRAX ADDIN EN.CITE <EndNote><Cite><Author>Naylor</Author><Year>2014</Year><RecNum>3599</RecNum><DisplayText>[11]</DisplayText><record><rec-number>3599</rec-number><foreign-keys><key app="EN" db-id="s9zd0vtsjaxsd9eeswv5szvqwett0fs0v59r">3599</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Naylor, K. L.</author><author>Leslie, W. D.</author><author>Hodsman, A. B.</author><author>Rush, D. N.</author><author>Garg, A. X.</author></authors></contributors><auth-address>1 Division of Nephrology, Western University, London, ON, Canada. 2 Department of Epidemiology &amp; Biostatistics, Western University, London, ON, Canada. 3 Department of Medicine, University of Manitoba, Winnipeg, ON, Canada. 4 Institute for Clinical Evaluative Sciences (ICES), Toronto, ON, Canada. 5 Address correspondence to: William Leslie, Saint Boniface General Hospital, 409 Tache Avenue, Room C5102, Winnipeg, MB, R2H 2A6, Canada.</auth-address><titles><title>FRAX Predicts Fracture Risk in Kidney Transplant Recipients</title><secondary-title>Transplantation</secondary-title><alt-title>Transplantation</alt-title></titles><periodical><full-title>Transplantation</full-title><abbr-1>Transplantation</abbr-1></periodical><alt-periodical><full-title>Transplantation</full-title><abbr-1>Transplantation</abbr-1></alt-periodical><edition>2014/02/08</edition><dates><year>2014</year><pub-dates><date>Feb 5</date></pub-dates></dates><isbn>1534-6080 (Electronic)&#xD;0041-1337 (Linking)</isbn><accession-num>24503761</accession-num><urls><related-urls><url>;[11]. The WHO has called for a global strategy on fracture prevention and management ADDIN EN.CITE <EndNote><Cite><Author>World Health Organization. Assessment of osteoporosis at the primary health care level. Summary Report of a WHO Scientific Group. WHO</Author><RecNum>3937</RecNum><DisplayText>[12]</DisplayText><record><rec-number>3937</rec-number><foreign-keys><key app="EN" db-id="s9zd0vtsjaxsd9eeswv5szvqwett0fs0v59r">3937</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>World Health Organization. Assessment of osteoporosis at the primary health care level. Summary Report of a WHO Scientific Group. WHO, Geneva 2004.</author></authors></contributors><titles></titles><dates></dates><urls></urls></record></Cite></EndNote>[12]. Such strategies require an understanding of well-validated fracture risk factors and prediction tools so populations at high risk can be targeted for diagnosis, treatment, and therapeutic trials. Given that risk factors for fracture in kidney transplant recipients have not been well-established, we conducted this study to determine general risk factors (e.g., age, sex, previous fracture, previous fall) and transplant-specific risk factors (e.g., length of time on dialysis prior to transplant) associated with major fractures (proximal humerus, forearm, hip, and clinical vertebral) in kidney transplant recipients. In an additional analysis we assessed risk factors for other fracture locations (excluding major fractures, and fractures involving the skull, hands, or feet).MATERIALS AND METHODSDesign and settingWe performed a population-based cohort study using healthcare databases held at the Institute for Clinical Evaluative Sciences (ICES) in Ontario, Canada. Ontario residents have universal access to hospital and physician services. These datasets were linked using unique encoded identifiers and analyzed at ICES. This study was approved by the institutional review board at Sunnybrook Health Sciences Centre, Toronto, Canada. Data sourcesWe used several databases to obtain our study cohort, characteristics, risk factors, and outcome data. Information on all kidney transplant recipients who received their transplant in Ontario was provided by the Canadian Organ Replacement Register (CORR). Information on provincial physicians’ billing claims was provided by the Ontario Health Insurance Plan database. The Canadian Institute for Health Information Discharge Abstract Database provided information on diagnostic and procedural codes during Ontario hospitalizations and information on emergency room visits was provided by the National Ambulatory Care Reporting System. The Ontario Registered Persons Database provided information on vital status and demographics.CohortWe identified all first-time kidney-only transplants in Ontario from April 1st, 2002 to December 31st, 2009, restricting to individuals ≥ 18 years of age at the transplant date. We selected April 1st, 2002 as our cohort entry date as this was when Canada changed the International Classification of Disease (ICD) system from version 9 to 10. The cohort entry date (index date) was the date an individual received their kidney transplant. Risk factorsWe assessed several general risk factors for fracture (e.g., age, sex, and prior major fracture) which are incorporated in FRAX. 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ADDIN EN.CITE.DATA [13-15]. We assessed several transplant-specific risk factors including: length of time on dialysis prior to transplant (years), type of donor (living vs deceased), cause of end-stage renal disease (ESRD, e.g., diabetes mellitus, glomerulonephritis, renal vascular disease, cystic kidney disease, or other [i.e., any cause of ESRD not included in the aforementioned categories such as pyelonephritis), pre-transplant dialysis modality (peritoneal, hemodialysis, or pre-emptive), and donor characteristics (age and sex).OutcomesWe followed kidney transplant recipients from the date of transplant until first fracture, death, or end of follow-up (March 31st, 2013). We did not censor kidney transplant recipients if they returned to chronic dialysis or if they had another transplant during follow-up. Our primary outcome was major fractures which were defined as a composite of hip, forearm, proximal humerus, and clinical vertebral fractures. We chose to assess risk factors for major fractures with hospital presentation (emergency room visit or hospital admission) as these fracture locations are associated with excess morbidity and mortality in the general populationPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5MZXNsaWU8L0F1dGhvcj48WWVhcj4yMDEwPC9ZZWFyPjxS

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ADDIN EN.CITE.DATA [16-18]. We also assessed other fracture locations, defined as: lower leg (ankle, tibia, fibula, patella), femoral shaft, rib/sternum/trunk, scapula, clavicle, and pelvis fractures. These fractures as a whole were considered the secondary outcome as they may be more common in kidney transplant recipients ADDIN EN.CITE <EndNote><Cite><Author>Weisinger</Author><Year>2006</Year><RecNum>1109</RecNum><DisplayText>[10]</DisplayText><record><rec-number>1109</rec-number><foreign-keys><key app="EN" db-id="s9zd0vtsjaxsd9eeswv5szvqwett0fs0v59r">1109</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Weisinger, Jose R.</author><author>Carlini, Raul G.</author><author>Rojas, Eudocia</author><author>Bellorin-Font, Ezequiel</author></authors></contributors><auth-address>Division of Nephrology, Hospital Universitario de Caracas, Universidad Central de Venezuela, Caracas, Venezuela. jweising@.ve</auth-address><titles><title>Bone disease after renal transplantation</title><secondary-title>Clinical Journal of The American Society of Nephrology: CJASN</secondary-title><alt-title>Clin J Am Soc Nephrol</alt-title></titles><periodical><full-title>Clinical Journal of The American Society of Nephrology: CJASN</full-title><abbr-1>Clin J Am Soc Nephrol</abbr-1></periodical><alt-periodical><full-title>Clinical Journal of The American Society of Nephrology: CJASN</full-title><abbr-1>Clin J Am Soc Nephrol</abbr-1></alt-periodical><pages>1300-13</pages><volume>1</volume><number>6</number><keywords><keyword>*Bone Density</keyword><keyword>*Bone Diseases/ep [Epidemiology]</keyword><keyword>Bone Diseases/et [Etiology]</keyword><keyword>Bone Diseases/pa [Pathology]</keyword><keyword>Bone and Bones/pa [Pathology]</keyword><keyword>Humans</keyword><keyword>*Kidney Transplantation/ae [Adverse Effects]</keyword><keyword>Postoperative Complications/ep [Epidemiology]</keyword></keywords><dates><year>2006</year><pub-dates><date>Nov</date></pub-dates></dates><isbn>1555-905X</isbn><accession-num>17699362</accession-num><work-type>Research Support, Non-U.S. Gov&apos;t&#xD;Review</work-type><urls><related-urls><url>;[10]. For example, in prior studies ankle fractures were common in kidney transplant recipientsPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5SYW1zZXktR29sZG1hbjwvQXV0aG9yPjxZZWFyPjE5OTk8

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ADDIN EN.CITE.DATA [21]. Statistical analysisWe compared differences in baseline characteristics of recipients with and without a fracture using the Mann Whitney U test for continuous variables and the chi-square test for categorical variables. We calculated the incidence rate of fracture (per 1000 person-years) censoring the observation period on the date of death, first fracture, or end of follow-up (March 31, 2013). We used the Cox proportional hazards model to assess effects of risk factors on the hazard of the first fracture. Prior to obtaining the adjusted hazard ratio (aHR) to quantify the effect of each risk factor, model assumptions such as the proportional hazards assumption and linearity of continuous factors (Martingale residuals) were assessed with a P-value < 0.05 used as criteria for a violation ADDIN EN.CITE <EndNote><Cite><Author>;[22-24]</DisplayText><record><rec-number>3941</rec-number><foreign-keys><key app="EN" db-id="s9zd0vtsjaxsd9eeswv5szvqwett0fs0v59r">3941</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author> Model Adequacy in&#xD;Proportional Hazards Regression</title><secondary-title>Michael G. Wilson</secondary-title></titles><periodical><full-title>Michael G. Wilson</full-title></periodical><dates></dates><urls></urls></record></Cite><Cite><Author> app="EN" db-id="s9zd0vtsjaxsd9eeswv5szvqwett0fs0v59r">3933</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author> app="EN" db-id="s9zd0vtsjaxsd9eeswv5szvqwett0fs0v59r">3927</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Lin, D., Wei, L. J., and Ying, Z. (1993), “Checking the Cox Model with Cumulative Sums of Martingale-Based Residuals,” Biometrika, 80, 557–572. </author></authors></contributors><titles></titles><dates></dates><urls></urls></record></Cite></EndNote>[22-24]. We used the backward elimination strategy to select risk factors that would be entered into the final model, with recipient age and sex forced into the model. To decrease the possibility of missing important risk factors for fracture post-transplant, a priori we chose a P-value of ≤ 0.2 to select variables for inclusion in the final model ADDIN EN.CITE <EndNote><Cite><Author>Maldonado</Author><Year>1993</Year><RecNum>3935</RecNum><DisplayText>[25]</DisplayText><record><rec-number>3935</rec-number><foreign-keys><key app="EN" db-id="s9zd0vtsjaxsd9eeswv5szvqwett0fs0v59r">3935</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Maldonado, G.</author><author>Greenland, S.</author></authors></contributors><auth-address>Division of Environmental and Occupational Health, School of Public Health, University of Minnesota, Minneapolis 55455.</auth-address><titles><title>Simulation study of confounder-selection strategies</title><secondary-title>Am J Epidemiol</secondary-title><alt-title>American journal of epidemiology</alt-title></titles><periodical><full-title>Am J Epidemiol</full-title><abbr-1>American journal of epidemiology</abbr-1></periodical><alt-periodical><full-title>Am J Epidemiol</full-title><abbr-1>American journal of epidemiology</abbr-1></alt-periodical><pages>923-36</pages><volume>138</volume><number>11</number><edition>1993/12/01</edition><keywords><keyword>Bias (Epidemiology)</keyword><keyword>*Cohort Studies</keyword><keyword>Confidence Intervals</keyword><keyword>*Confounding Factors (Epidemiology)</keyword><keyword>*Epidemiologic Methods</keyword><keyword>Humans</keyword><keyword>Logistic Models</keyword><keyword>Odds Ratio</keyword><keyword>*Regression Analysis</keyword><keyword>Reproducibility of Results</keyword><keyword>Research Design</keyword></keywords><dates><year>1993</year><pub-dates><date>Dec 1</date></pub-dates></dates><isbn>0002-9262 (Print)&#xD;0002-9262 (Linking)</isbn><accession-num>8256780</accession-num><work-type>Comparative Study&#xD;Research Support, Non-U.S. Gov&apos;t&#xD;Research Support, U.S. Gov&apos;t, P.H.S.</work-type><urls><related-urls><url>;[25]. We assessed for multicollinearity among variables prior to entering variables into the backward elimination model. We found limited concern for multicollinearity, since all variance inflation factors were less than 2 ADDIN EN.CITE <EndNote><Cite><RecNum>3934</RecNum><DisplayText>[26]</DisplayText><record><rec-number>3934</rec-number><foreign-keys><key app="EN" db-id="s9zd0vtsjaxsd9eeswv5szvqwett0fs0v59r">3934</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Allison PD. Logistic Regression Using the SAS System: Theory</author><author>and Application. Cary, NC: Wiley InterScience, SAS</author><author>Institute, 1999.</author></authors></contributors><titles></titles><dates></dates><urls></urls></record></Cite></EndNote>[26]. There were missing data for the following variables: Donor age (2.2%), donor sex (< 1%), cause of ESRD (11.6%), race (10.7%), and donor type (< 1%). We handled missing data by assigning values randomly selected from observed values with the exception of donor age for which we supplemented missing values with the median age. In the final model we interpreted two-sided P-values < 0.05 as statistically significant. We performed all analyses using SAS (Statistical Analysis Software), version 9.4 (). The statistical methods of this study were reviewed by a biostatistician, Guangyong Zou, PhD. RESULTSIncidence of fractureOf the 2723 kidney transplant recipients the total follow-up was 16274 person-years (average 6 years), during which 402 (14.8%) died and 132 (4.8%) sustained a major fracture [8.1 fractures per 1000 person-years, 95% confidence interval (CI) 6.8-9.6].Baseline characteristicsRecipients who sustained a major fracture in follow-up compared to recipients with no major fracture had a significantly higher median age (56.5 vs 50.5 years), were more likely to be women (48.5% vs 35.8%), and were less likely to have glomerulonephritis as their cause of ESRD (29.6% vs 36.7%) (Table 1). Univariable analysisWe found older recipient age and female recipient sex were the general risk factors associated with an increased risk of major fracture (Table 2). For example, female recipients had almost a two-fold greater risk of major fracture [hazard ratio (HR) = 1.65, 95%CI: 1.18-2.33). Due to the small number of recipients with a prior major fracture this risk factor was not able to be assessed. Regarding transplant-specific risk factors, cystic kidney disease (HR = 1.93, 95%CI: 1.20-3.08) and diabetes (HR = 1.80, 95%CI: 1.15-2.82) as the cause of ESRD (compared to glomerulonephritis as the reference cause) were both associated with a higher risk of major fracture. Each 5-year increase in donor age was also associated with a greater risk of major fracture (HR = 1.11, 95%CI: 1.04-1.18).Multivariable analysisIn the multivariable model, older recipient age (5-year increase) (aHR = 1.11, 95%CI: 1.03-1.19) and female recipient sex (aHR = 1.81, 95%CI: 1.28-2.57) were the general risk factors associated with a greater risk of major fracture (Table 2). Regarding transplant-specific risk factors diabetes (aHR = 1.72, 95%CI: 1.09-2.72) and cystic kidney disease (aHR = 1.73, 95%CI: 1.08-2.78) as the cause of ESRD (compared to glomerulonephritis as the reference cause), and older donor age (5-year increase) (aHR = 1.09, 95%CI: 1.02-1.17) were associated with a greater risk of major fracture.Other fracturesWhen we assessed other fracture events (excluding the major fractures, and skull, hands, or feet) kidney transplant recipients had 141 fractures (8.7 fractures per 1000 person-years, 95%CI: 7.3-10.2). Recipients with vs without such fractures were significantly more likely to have diabetes (40.4% vs 25.4%) and were more likely to have had a fall with hospitalization in the year prior to transplant (7.1% vs 3.5%) (Table 3). In the multivariable model we found diabetes and a fall with hospitalization prior to transplantation were the general risk factors associated with an increased risk of fracture, while length of time on dialysis, and renal vascular disease and other causes of ESRD were the transplant-specific risk factors associated with a greater risk of other fractures (Table 4). DISCUSSIONSimilar to the general population, we found increasing recipient age and female sex were associated with an increased major fracture risk in kidney transplant recipients. Unique to the kidney transplant population, we also found diabetes or cystic kidney disease as the cause of ESRD and increasing age of the kidney donor were associated with a significantly increased major fracture risk. However, risk factors were not consistent across fracture locations with increasing age and female sex not associated with an increased other fracture risk. Our findings suggest that both general and transplant-specific risk factors for fracture should be considered by clinicians when assessing fracture risk in kidney transplant recipients. However, different risk factors may need to be taken into account when considering different fracture locations.We previously published a study of 321 kidney transplant recipients from Manitoba, Canada and found that FRAX was able to modestly predict fracture and may be a useful tool for clinicians to use to help guide treatment decisions; the area under the receiver operating curve value was 0.62 and there was concordance in the observed vs predicted 10-year major osteoporotic fracture probability (6.3% vs 5.6%, respectively) ADDIN EN.CITE <EndNote><Cite><Author>Naylor</Author><Year>2014</Year><RecNum>3599</RecNum><DisplayText>[11]</DisplayText><record><rec-number>3599</rec-number><foreign-keys><key app="EN" db-id="s9zd0vtsjaxsd9eeswv5szvqwett0fs0v59r">3599</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Naylor, K. L.</author><author>Leslie, W. D.</author><author>Hodsman, A. B.</author><author>Rush, D. N.</author><author>Garg, A. X.</author></authors></contributors><auth-address>1 Division of Nephrology, Western University, London, ON, Canada. 2 Department of Epidemiology &amp; Biostatistics, Western University, London, ON, Canada. 3 Department of Medicine, University of Manitoba, Winnipeg, ON, Canada. 4 Institute for Clinical Evaluative Sciences (ICES), Toronto, ON, Canada. 5 Address correspondence to: William Leslie, Saint Boniface General Hospital, 409 Tache Avenue, Room C5102, Winnipeg, MB, R2H 2A6, Canada.</auth-address><titles><title>FRAX Predicts Fracture Risk in Kidney Transplant Recipients</title><secondary-title>Transplantation</secondary-title><alt-title>Transplantation</alt-title></titles><periodical><full-title>Transplantation</full-title><abbr-1>Transplantation</abbr-1></periodical><alt-periodical><full-title>Transplantation</full-title><abbr-1>Transplantation</abbr-1></alt-periodical><edition>2014/02/08</edition><dates><year>2014</year><pub-dates><date>Feb 5</date></pub-dates></dates><isbn>1534-6080 (Electronic)&#xD;0041-1337 (Linking)</isbn><accession-num>24503761</accession-num><urls><related-urls><url>;[11]. However, the number of major osteoporotic fracture events was small (n = 21), with correspondingly wide 95% confidence intervals ADDIN EN.CITE <EndNote><Cite><Author>Naylor</Author><Year>2014</Year><RecNum>3599</RecNum><DisplayText>[11]</DisplayText><record><rec-number>3599</rec-number><foreign-keys><key app="EN" db-id="s9zd0vtsjaxsd9eeswv5szvqwett0fs0v59r">3599</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Naylor, K. L.</author><author>Leslie, W. D.</author><author>Hodsman, A. B.</author><author>Rush, D. N.</author><author>Garg, A. X.</author></authors></contributors><auth-address>1 Division of Nephrology, Western University, London, ON, Canada. 2 Department of Epidemiology &amp; Biostatistics, Western University, London, ON, Canada. 3 Department of Medicine, University of Manitoba, Winnipeg, ON, Canada. 4 Institute for Clinical Evaluative Sciences (ICES), Toronto, ON, Canada. 5 Address correspondence to: William Leslie, Saint Boniface General Hospital, 409 Tache Avenue, Room C5102, Winnipeg, MB, R2H 2A6, Canada.</auth-address><titles><title>FRAX Predicts Fracture Risk in Kidney Transplant Recipients</title><secondary-title>Transplantation</secondary-title><alt-title>Transplantation</alt-title></titles><periodical><full-title>Transplantation</full-title><abbr-1>Transplantation</abbr-1></periodical><alt-periodical><full-title>Transplantation</full-title><abbr-1>Transplantation</abbr-1></alt-periodical><edition>2014/02/08</edition><dates><year>2014</year><pub-dates><date>Feb 5</date></pub-dates></dates><isbn>1534-6080 (Electronic)&#xD;0041-1337 (Linking)</isbn><accession-num>24503761</accession-num><urls><related-urls><url>;[11]. We hypothesized that a fracture prediction tool incorporating both general and transplant-specific risk factors may improve fracture prediction ADDIN EN.CITE <EndNote><Cite><Author>Naylor</Author><Year>2014</Year><RecNum>3599</RecNum><DisplayText>[11]</DisplayText><record><rec-number>3599</rec-number><foreign-keys><key app="EN" db-id="s9zd0vtsjaxsd9eeswv5szvqwett0fs0v59r">3599</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Naylor, K. L.</author><author>Leslie, W. D.</author><author>Hodsman, A. B.</author><author>Rush, D. N.</author><author>Garg, A. X.</author></authors></contributors><auth-address>1 Division of Nephrology, Western University, London, ON, Canada. 2 Department of Epidemiology &amp; Biostatistics, Western University, London, ON, Canada. 3 Department of Medicine, University of Manitoba, Winnipeg, ON, Canada. 4 Institute for Clinical Evaluative Sciences (ICES), Toronto, ON, Canada. 5 Address correspondence to: William Leslie, Saint Boniface General Hospital, 409 Tache Avenue, Room C5102, Winnipeg, MB, R2H 2A6, Canada.</auth-address><titles><title>FRAX Predicts Fracture Risk in Kidney Transplant Recipients</title><secondary-title>Transplantation</secondary-title><alt-title>Transplantation</alt-title></titles><periodical><full-title>Transplantation</full-title><abbr-1>Transplantation</abbr-1></periodical><alt-periodical><full-title>Transplantation</full-title><abbr-1>Transplantation</abbr-1></alt-periodical><edition>2014/02/08</edition><dates><year>2014</year><pub-dates><date>Feb 5</date></pub-dates></dates><isbn>1534-6080 (Electronic)&#xD;0041-1337 (Linking)</isbn><accession-num>24503761</accession-num><urls><related-urls><url>;[11]. 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ADDIN EN.CITE.DATA [27,28] Moreover, ;the strength of the transplant-specific risk factors was only moderate.. Additionally, the large sample size needed to update a model and the reasonable performance of the original FRAX model in kidney transplant recipients further suggests model updating may not be needed. However, to gain a more complete understanding of fracture risk, it is likely important for clinicians to consider some transplant-specific risk factors (e.g., cause of ESRD) in isolation, when assessing fracture risk. Future research should assess other potential transplant-specific risk factors (unavailable in our current analyses), including: change in body mass index after transplantation (weight changes found to increase fracture risk in the general population) and fibroblast growth factor 23 (suppresses mineralization of the bone matrix)PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5DcmFuZGFsbDwvQXV0aG9yPjxZZWFyPjIwMTU8L1llYXI+

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ADDIN EN.CITE.DATA [29,30]. We found that risk factors for fracture may vary across fracture locations. For example, there were different risk factors for fracture between our two fracture classifications (major fracture locations vs other fracture locations). A possible explanation for this finding is that in the kidney transplant population risk factors for fractures are site specific. For example, similar to what some studies have found in the general population, in our study increasing recipient age and female recipient sex were both associated with an increased major fracture riskPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5LYW5pczwvQXV0aG9yPjxZZWFyPjIwMDU8L1llYXI+PFJl

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ADDIN EN.CITE.DATA [31-33]. However, increasing recipient age and female sex were not associated with an increased risk of other fractures. This provides a potential explanation for the results of a previous systematic review which found risk factors for fracture in kidney transplant recipients were inconsistent; studies in the review included different fracture locationsPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5OYXlsb3I8L0F1dGhvcj48WWVhcj4yMDEzPC9ZZWFyPjxS

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ADDIN EN.CITE.DATA [6]. However, we cannot discount the possibility that the differences in risk factors across fracture locations found in this study were the result of a type II error. Future studies with larger sample sizes should assess site-specific risk factors for fractures (e.g., ankle) in kidney transplant recipients.Of concern, several of the risk factors for fracture identified in this study are becoming more common in recent eras of kidney transplant recipients. For example, we found diabetes as the cause of ESRD and older recipient age were significant risk factors for major fractures. The number of recipients with diabetes and the average recipient age has been increasingPEVuZE5vdGU+PENpdGU+PFJlY051bT4zNjY4PC9SZWNOdW0+PERpc3BsYXlUZXh0PlszNCwgMzVd

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ADDIN EN.CITE.DATA [37,38]. It is important to note that donor age may only be a surrogate measure for recipient age, with kidneys from older donors often being allocated to older recipients. Nevertheless, the increase in the aforementioned risk factors may have important implications for fracture risk in future recipients. Unfortunately, none of the risk factors for major fractures found in this study are easily modifiable. However, a hospitalized fall in the year prior to transplant was a significant risk factor for other fractures; falls are potentially modifiable through the use of fall prevention programsPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XaWxsaWFtcy1Kb2huc29uPC9BdXRob3I+PFllYXI+MjAw

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ADDIN EN.CITE.DATA [4]. The paucity of modifiable risk factors is concerning as one of the best ways to prevent fractures in the general population is to provide therapy (e.g., bisphosphonates); the efficacy of these therapies in kidney transplant recipients is unclear ADDIN EN.CITE <EndNote><Cite><Author>Palmer</Author><Year>2009</Year><RecNum>2847</RecNum><DisplayText>[42]</DisplayText><record><rec-number>2847</rec-number><foreign-keys><key app="EN" db-id="s9zd0vtsjaxsd9eeswv5szvqwett0fs0v59r">2847</key></foreign-keys><ref-type name="Book">6</ref-type><contributors><authors><author>Palmer, S. C.</author><author>McGregor, D. O.</author><author>Strippoli, G. F. M.</author></authors></contributors><titles><title>Interventions for preventing bone disease in kidney transplant recipients</title></titles><dates><year>2009</year></dates><publisher>Cochrane Database of Systematic Reviews. (4) , 2009. Article Number: CD005015. Date of Publication: 2009.</publisher><isbn>1469-493X</isbn><urls><related-urls><url> Technologies</remote-database-provider><language>English</language></record></Cite></EndNote>[42]. However, given that not many recipients sustained a fracture the lack of modifiable risk factors may be less of a concern.Limitations of the study are noted. First, we were unable to assess drug use (e.g., glucocorticoids) as a potential risk factor for fracture; drug information in our databases was only available for a minority of kidney transplant recipients; therefore, our sample size would have been decreased, limiting statistical power. It is important to note that a previous study found that kidney transplant recipients who received early corticosteroid withdrawal had a 1.6% reduction in fracture compared to recipients who received standard corticosteroid based immunosuppressionPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5OaWtrZWw8L0F1dGhvcj48WWVhcj4yMDEyPC9ZZWFyPjxS

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ADDIN EN.CITE.DATA [43]. Future studies should explore this further, including measuring glucocorticoid use as a continuous variable and assessing the impact of reduced dose on fracture risk and long-term immunological outcomes (e.g., graft loss) ADDIN EN.CITE <EndNote><Cite><Author>Zsom</Author><Year>2015</Year><RecNum>4270</RecNum><DisplayText>[44]</DisplayText><record><rec-number>4270</rec-number><foreign-keys><key app="EN" db-id="s9zd0vtsjaxsd9eeswv5szvqwett0fs0v59r">4270</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Zsom, L.</author><author>Wagner, L.</author><author>Fulop, T.</author></authors></contributors><auth-address>Lajos Zsom, Division of Transplantation, Institute of Surgery, University of Debrecen, 4032 Debrecen, Hungary.</auth-address><titles><title>Minimization vs tailoring: Where do we stand with personalized immunosuppression during renal transplantation in 2015?</title><secondary-title>World J Transplant</secondary-title><alt-title>World journal of transplantation</alt-title></titles><periodical><full-title>World J Transplant</full-title><abbr-1>World journal of transplantation</abbr-1></periodical><alt-periodical><full-title>World J Transplant</full-title><abbr-1>World journal of transplantation</abbr-1></alt-periodical><pages>73-80</pages><volume>5</volume><number>3</number><edition>2015/10/01</edition><dates><year>2015</year><pub-dates><date>Sep 24</date></pub-dates></dates><isbn>2220-3230 (Electronic)&#xD;2220-3230 (Linking)</isbn><accession-num>26421259</accession-num><urls><related-urls><url>;[44]. Second, we were unable to assess several risk factors, such as body mass index and estimated glomerular filtration rate, due to a high proportion of missingness (> 50%). Third, the small number of fracture events may have limited statistical power and increased concerns about the validity of the model. However, we selected a liberal P-value in our backward elimination analysis to ensure we were not excluding potentially important variables. Additionally, it is unlikely there were type I errors given there were at least 10 events per variablePEVuZE5vdGU+PENpdGU+PEF1dGhvcj5WaXR0aW5naG9mZjwvQXV0aG9yPjxZZWFyPjIwMDc8L1ll

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ADDIN EN.CITE.DATA [45]. Finally, due to the small number of fracture events we were also not able to assess several of the other risk factors included in the FRAX algorithm (e.g., rheumatoid arthritis). Last, the generalizability of these results to other races/ethnic groups may be limited as the majority (72%) of our sample was White.Both general and transplant-specific risk factors for fracture should be considered by clinicians when assessing fracture risk in this unique patient population; however, risk factors may be variable across fracture locations. Future studies with larger sample sizes should assess the ability of other transplant-specific risk factors to predict fracture.ACKNOWLEDGEMENTSDr. Naylor was supported by the Canadian Institute of Health Research Allied Health Professional Fellowship the Canadian National Transplant Research Program Astellas Training Award. Dr. Garg was supported by the Dr. Adam Linton Chair in Kidney Health Analytics. Dr. Lam was supported by a KRESCENT New Investigator award. This study was supported by the Institute for Clinical Evaluative Sciences (ICES) Western site. ICES is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC). Core funding for ICES Western is provided by the Academic Medical Organization of Southwestern Ontario (AMOSO), the Schulich School of Medicine and Dentistry (SSMD), Western University, and the Lawson Health Research Institute (LHRI). The research was conducted by members of the ICES Kidney, Dialysis and Transplantation team, at the ICES Western facility, who are supported by a grant from the Canadian Institutes of Health Research (CIHR). The opinions, results and conclusions are those of the authors and are independent from the funding sources. No endorsement by ICES, AMOSO, SSMD, LHRI, CIHR, or the MOHLTC is intended or should be inferred. Parts of this material are based on data and information compiled and provided by CIHI. However, the analyses, conclusions, opinions and statements expressed herein are those of the author, and not necessarily those of CIHI. Aspects of this project were conducted in the Lilibeth Caberto Kidney Clinical Research MENTSBackgroundCompared to the general population kidney transplant recipients are at an increased risk of fracture due to a multitude of factors, including: chronic kidney disease-mineral and bone disorder and glucocorticoid administration post-transplant. However, risk factors for fracture are not well-established in the kidney transplant population. An understanding of risk factors for fracture is important to target high risk recipients for treatment and therapeutic trials.Research frontiersTo determine the general and transplant-specific risk factors for fractures in kidney transplant recipients.Innovations and breakthroughsGeneral and transplant-specific risk factors for fracture should be considered by clinicians when assessing fracture risk in kidney transplant recipients. However, different risk factors may need to be taken into account when considering different fracture locations. Unfortunately, none of the risk factors for major fractures found in this study are easily modifiable. However, a hospitalized fall in the year prior to transplant was a significant risk factor for other fractures; falls are potentially modifiable through the use of fall prevention programs. This is an important finding given the commonality of falls in kidney transplant recipients .ApplicationsThe risk factors for fracture identified in this study are useful for clinical prognostication.TerminologyMajor fractures were defined as a composite of hip, forearm, proximal humerus, and clinical vertebral fractures. Other fracture locations were defined as a composite of lower leg (ankle, tibia, fibula, patella), femoral shaft, rib/sternum/trunk, scapula, clavicle, and pelvis fractures.Peer-reviewThis is a well written study on an important topic in transplantation as the risk of bone fractures after transplantation. The statistical analysis is well conducted.REFERENCES1?Ramsey-Goldman R, Dunn JE, Dunlop DD, Stuart FP, Abecassis MM, Kaufman DB, Langman CB, Salinger MH, Sprague SM. 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Minimization vs tailoring: Where do we stand with personalized immunosuppression during renal transplantation in 2015??World J Transplant?2015;?5: 73-80 [PMID: 26421259 DOI: 10.5500/wjt.v5.i3.73]45?Vittinghoff E, McCulloch CE. Relaxing the rule of ten events per variable in logistic and Cox regression.?Am J Epidemiol?2007;?165: 710-718 [PMID: 17182981 DOI: 10.1093/aje/kwk052]P-Reviewer: Cantarovich F, Fulop T, Kin T, Markic D, Salvadori M S-Editor: Qiu S L-Editor: E-Editor:Table SEQ Table_5. \* ARABIC 1 Characteristics of kidney transplant recipients classified by major fracture status1No fracture(n = 2591)Major Fracture(n = 132)P-valueGeneral risk factorsAge, years50.5 (41-61)56.5 (45-63)0.01Women928 (35.8%)66 (48.5%)0.004Race/ethnicity0.40 White1845 (71.2%)103 (78%) Asian 208 (8.0%)8 (6.1%) Black 198 (7.6%)7 (5.3%) Other2340 (13.1%)14 (10.6%)Diabetes673 (25.6%)40 (30.3%)0.27Fall with hospitalization in the year prior to the transplant date 92 (3.6%)8 (6.1%)0.15Major fracture prior to the transplant date3Transplant specific risk factors Length of time on dialysis prior to transplant (measured in years)42.8 (1.2-5.4)2.7 (0.92-5.1)0.56Type of donor 0.47 Deceased (vs Living)1458 (56.3%)70 (53.0%)Cause of end-stage renal disease50.004 Glomerulonephritis951 (36.7%)39 (29.6%) Cystic kidney disease385 (14.9%)31 (23.5%) Diabetes560 (21.6%)37 (28.0%) Other695 (26.8%)25 (18.9%)Pre-transplant dialysis modality60.99 Peritoneal dialysis701 (27.1%)35 (26.5%) Hemodialysis1622 (62.6%)83 (62.9%) Pre-emptive268 (10.3%)14 (11.6%)Donor CharacteristicsType of donor 0.47 Deceased (vs living)1458 (56.3%)70 (53.0%)Donor age, yr46 (36-54)47.5 (41-55)0.16Donor sex Women1295 (50.0%)68 (51.5%)0.73Data are median (interquartile range) or n (%). 1Major fracture events were comprised of forearm (n = 81), hip (n = 22), proximal humerus (n = 18), and clinical vertebral fractures (n = 13); 2Other was defined as a composite of: Indian Sub-Continent, Pacific Islander, Aboriginal, Mid East/Arabian, Latin American, Other/Multiracial; 3Due to the small number of recipients with a prior major fracture this risk factor was not able to be assessed; 4Includes individuals who received a pre-emptive transplant where the time spent on dialysis was defined as 0 years; 5Due to the small number of recipients with a major fracture who had renal vascular disease as the cause of their ESRD this category was combined into the other category; 6We defined hemodialysis and peritoneal dialysis based on the modality the recipient first received. We defined pre-emptive transplant as no evidence of hemodialysis or peritoneal dialysis prior to transplant.Table SEQ Table_5. \* ARABIC 2 Univariable and multivariable analysis of risk factors for major fracture in kidney transplant recipientsUnivariable analysisMultivariable analysisRisk factorsHazard ratio(95%CI)Hazard ratio(95%CI)Age (per 5 year increase)1.13 (1.06-1.21)1.11 (1.03-1.19)SexMen WomenReference1.65 (1.18-2.33)1.81 (1.28-2.57)Race/ethnicityWhiteReferenceAsian0.72 (0.35-1.47)Black0.65 (0.30-1.39)Other20.78 (0.44-1.36)Diabetes (vs none)1.40 (0.96-2.02)Fall with hospitalization in the year prior to the transplant date (vs none)2.00 (0.98-4.09)1.72 (0.84-3.50)Major fracture prior to the transplant date3 (vs none)Length of time on dialysis prior to transplant (measured in years)41.06 (0.61-1.84)Type of donor Living0.99 (0.70-1.39)DeceasedReferenceCause of end-stage renal disease5GlomerulonephritisReferenceReferenceCystic kidney disease1.93 (1.20-3.08)1.73 (1.08-2.78)Diabetes1.80 (1.15-2.82)1.72 (1.09-2.72)Other0.92 (0.56-1.53)0.88 (0.53-1.46)Pre-transplant dialysis modality6HemodialysisReferencePeritoneal dialysis0.99 (0.67-1.47)Pre-emptive0.96 (0.54-1.68)Type of donor Living0.99 (0.70-1.39)DeceasedReferenceDonor age (per 5 year increase)1.11 (1.04-1.18)1.09 (1.02-1.17)Donor sexMenWomenReference1.03 (0.73-1.44)2Other was defined as a composite of: Indian Sub-Continent, Pacific Islander, Aboriginal, Mid East/Arabian, Latin American, Other/Multiracial; 3Due to the small number of recipients with a prior major fracture this risk factor was not able to be assessed; 4Includes individuals who received a pre-emptive transplant where the time spent on dialysis was defined as 0 years; 5Due to the small number of recipients with a major fracture who had renal vascular disease as the cause of their ESRD this category was combined into the other category; 6We defined hemodialysis and peritoneal dialysis based on the modality the recipient first received. We defined pre-emptive transplant as no evidence of hemodialysis or peritoneal dialysis prior to transplant.Table SEQ Table_5. \* ARABIC 3 Characteristics of kidney transplant recipients classified by other fractures status5 No fracture(n = 2582)Other fracture(n = 141)P-valueGeneral risk factorsAge, years52 (42-61)54 (44-61)0.18Women944 (36.6%)48 (34.0%)0.55Race/ethnicity0.33 White1838 (71.2%)110 (78.0%) Asian 208 (8.1%)8 (5.7%) Black 198 (7.8%)7 (5.0%) Other2338 (13.1%)16 (11.4%)Diabetes656 (25.4%)57 (40.4%)< 0.001Fall with hospitalization in the year prior to the transplant index 90 (3.5%)10 (7.1%)0.03Major fracture prior to the transplant date7 69 (2.7%)13 (9.2%)< 0.001Transplant specific risk factors Length of time on dialysis prior to transplant (measured in years)42.7 (1.1-5.4)3.0 (1.7-5.3)0.068Type of donor Deceased1439 (55.7%)89 (63.1%)0.09Cause of end-stage renal disease0.003Glomerulonephritis958 (37.1%)32 (22.7%)Cystic kidney disease397 (15.4%)19 (13.5%)Diabetes555 (21.5%)42 (29.8%)Renal Vascular Disease294 (11.4%)23 (16.3%)Other378 (14.6%)25 (17.7%)Pre-transplant dialysis modality60.09Peritoneal dialysis694 (26.7%)42 (29.8%)Hemodialysis1613 (62.5%)92 (65.3%)Pre-emptive275 (10.7%)7 (5.0%)Donor characteristicsType of donor Deceased1439 (55.7%)89 (63.1%)0.09Donor age, years46 (36-54)48 (40-54)0.13Donor sexWomen1298 (50.3%)65 (46.1%)0.33Data are median (interquartile range) or n (%). 2Other was defined as a composite of: Indian Sub-Continent, Pacific Islander, Aboriginal, Mid East/Arabian, Latin American, Other/Multiracial; 4Includes individuals who received a pre-emptive transplant where the time spent on dialysis was defined as 0 years; 5Other fracture events were comprised of pelvis (n = 15), ankle (n = 37), patella (n = 8), tibia/fibula (n = 37), rib/sternum (n = 34), and other (femoral shaft, scapula, clavicle; n = 16); 6We defined hemodialysis and peritoneal dialysis based on the modality the recipient first received. We defined pre-emptive transplant as no evidence of hemodialysis or peritoneal dialysis prior to transplant; 7Prior major fracture had to occur from 1991 to cohort entry (date of transplant).Table SEQ Table_5. \* ARABIC 4 Univariable and multivariable analysis of risk factors for other fracture in kidney transplant recipientsUnivariable analysisMultivariable analysisRisk factorHazard ratio(95%CI)Hazard ratio(95%CI)Age (per 5 year increase)1.09 (1.02-1.17)1.03 (0.96-1.10)SexMen WomenReference0.99 (0.63-1.26)0.97 (0.68-1.39)Race/ethnicityWhiteReferenceAsian0.67 (0.33-1.37)0.67 (0.32-1.39)Black0.59 (0.27-1.26)0.47 (0.21-1.02)Other20.82 (0.49-1.39)0.73 (0.43-1.26)Diabetes (vs none)2.2 (1.57-3.08)2.19 (1.38-3.49)Fall with hospitalization in the year prior to the transplant date (vs none)2.37 (1.25-4.52)2.05 (1.07-3.93)Length of time on dialysis prior to transplant (measured in years)41.06 (1.00-1.12)1.07 (1.01-1.14)Type of donor LivingReferenceDeceased0.67 (0.47-0.92)Cause of end-stage renal diseaseGlomerulonephritisReferenceReferenceCystic kidney disease1.4 (0.8-2.47)1.35 (0.76-2.39)Diabetes2.47 (1.56-3.91)1.40 (0.78-2.49)Renal vascular disease2.40 (1.41-4.10)2.11 (1.22-3.65)Other2.04 (1.21-3.44)2.03 (1.20-3.45)Pre-transplant dialysis modality6HemodialysisReferencePeritoneal dialysis1.06 (0.74-1.53)Pre-emptive0.43 (0.2-0.92)Donor age (per 5 yr increase)1.07 (1.01-1.14)1.06 (0.99-1.12)Donor sexMenWomenReference0.83 (0.6-1.16)2Other was defined as a composite of: Indian Sub-Continent, Pacific Islander, Aboriginal, Mid East/Arabian, Latin American, Other/Multiracial; 4Includes individuals who received a pre-emptive transplant where the time spent on dialysis was defined as 0 years; 6We defined hemodialysis and peritoneal dialysis based on the modality they first received. We defined pre-emptive transplant as no evidence of hemodialysis or peritoneal dialysis prior to transplant. ADDIN EN.SECTION.REFLIST ................
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