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      Influence of Socio-Economic Inequalities on Access to Renal Transplantation and Survival of Patients with End-Stage Renal Disease

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          Abstract

          Background

          Public and scientific concerns about the social gradient of end-stage renal disease and access to renal replacement therapies are increasing. This study investigated the influence of social inequalities on the (i) access to renal transplant waiting list, (ii) access to renal transplantation and (iii) patients’ survival.

          Methods

          All incident adult patients with end-stage renal disease who lived in Bretagne, a French region, and started dialysis during the 2004–2009 period were geocoded in census-blocks. To each census-block was assigned a level of neighborhood deprivation and a degree of urbanization. Cox proportional hazards models were used to identify factors associated with each study outcome.

          Results

          Patients living in neighborhoods with low level of deprivation had more chance to be placed on the waiting list and less risk of death (HR = 1.40 95%CI: [1.1–1.7]; HR = 0.82 95%CI: [0.7–0.98]), but this association did not remain after adjustment for the patients’ clinical features. The likelihood of receiving renal transplantation after being waitlisted was not associated with neighborhood deprivation in univariate and multivariate analyses.

          Conclusions

          In a mixed rural and urban French region, patients living in deprived or advantaged neighborhoods had the same chance to be placed on the waiting list and to undergo renal transplantation. They also showed the same mortality risk, when their clinical features were taken into account.

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          Most cited references36

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          A study of the quality of life and cost-utility of renal transplantation.

          The objective of this study was to assess the cost-utility of renal transplantation compared with dialysis. To accomplish this, a prospective cohort of pre-transplant patients were followed for up to two years after renal transplantation at three University-based Canadian hospitals. A total of 168 patients were followed for an average of 19.5 months after transplantation. Health-related quality of life was assessed using a hemodialysis questionnaire, a transplant questionnaire, the Sickness Impact Profile, and the Time Trade-Off Technique. Fully allocated costs were determined by prospectively recording resource use in all patients. A societal perspective was taken. By six months after transplantation, the mean health-related quality of life scores of almost all measures had improved compared to pre-transplantation, and they stayed improved throughout the two years of follow up. The mean time trade-off score was 0.57 pre-transplant and 0.70 two years after transplantation. The proportion of individuals employed increased from 30% before transplantation to 45% two years after transplantation. Employment prior to transplantation [relative risk (RR) = 23], graft function (RR 10) and age (RR 1.6 for every decrease in age by one decade), independently predicted employment status after transplantation. The cost of pre-transplant care ($66,782 Can 1994) and the cost of the first year after transplantation ($66,290) were similar. Transplantation was considerably less expensive during the second year after transplantation ($27,875). Over the two years, transplantation was both more effective and less costly than dialysis. This was true for all subgroups of patients examined, including patients older than 60 and diabetics. We conclude that renal transplantation was more effective and less costly than dialysis in all subgroups of patients examined.
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            Comparison of survival probabilities for dialysis patients vs cadaveric renal transplant recipients.

            To compare mortality risk among cadaveric renal transplant recipients vs transplant candidates on dialysis in the cyclosporine era. Patient mortality risk was analyzed by treatment modality for a completed statewide patient population. All Michigan residents younger than age 65 years who started endstage renal disease (ESRD) therapy between January 1, 1984, and December 31, 1989, were included. Patients were followed up from ESRD onset (n = 5020), to wait-listing for renal transplant (n = 1569), to receiving a cadaveric first transplant (n = 799), and to December 31, 1989. Mortality rates. Using a time-dependent variable based on the waiting time from date of wait-listing to transplantation and adjusting for age, sex, race, and primary cause of ESRD, the relative risk (RR) of dying was increased early after transplantation and then decreased to a beneficial long-term effect, given survival to 365 days after transplantation (RR, 0.36; P .05). Overall, the estimated times from transplantation to equal mortality risk was 117 +/- 28 days and to equal cumulative mortality was 325 +/- 91 days. The overall mortality risk following renal transplantation was initially increased, but there was a long-term survival benefit compared with similar patients on dialysis. These analyses allow improved description of comparative mortality risks for dialysis and transplant patients and allow advising patients regarding comparative survival outcomes.
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              Barriers to cadaveric renal transplantation among blacks, women, and the poor.

              Cadaveric renal transplantation rates differ greatly by race, sex, and income. Previous efforts to lessen these differences have focused on the transplant waiting list. However, the transplantation process involves a series of steps related to medical suitability, interest in transplantation, pretransplant workup, and movement up a waiting list to eventual transplantation. To determine the relative importance of each step in explaining differences in cadaveric renal transplantation rates. Prospective cohort study. A total of 7125 patients beginning long-term dialysis between January 1993 and December 1996 in Indiana, Kentucky, and Ohio. Completion of 4 separate steps during each patient-year of follow-up: (A) being medically suitable and possibly interested in transplantation; (B) being definitely interested in transplantation; (C) completing the pretransplant workup; and (D) moving up a waiting list and receiving a transplant. Compared with whites, blacks were less likely to complete steps B (odds ratio [OR], 0.68; 95% confidence interval [CI], 0.61-0.76), C (OR, 0.56; 95% CI, 0.48-0.65), and D (OR, 0.50; 95% CI, 0.40-0.62) after adjustment for age, sex, cause of renal failure, years receiving dialysis, and median income of patient ZIP code. Compared with men, women were less likely to complete each of the 4 steps, with ORs of 0.90, 0.89, 0.80, and 0.82, respectively. Poor individuals were less likely than wealthy individuals to complete steps A, B, and C, with ORs of 0.67, 0.78, and 0.77, respectively. Barriers at several steps are responsible for sociodemographic differences in access to cadaveric renal transplantation. Efforts to allocate kidneys equitably must address each step of the transplant process.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                15 April 2016
                2016
                : 11
                : 4
                : e0153431
                Affiliations
                [1 ]EHESP School of Public Health, Sorbonne Paris Cité, Rennes, France
                [2 ]CHU Pontchaillou, Service de néphrologie, Rennes, France
                [3 ]Université de Rennes 1, UMR 6290, équipe Kyca, Rennes, France
                [4 ]REIN Registry, Agence de la biomédecine, Saint Denis La Plaine, France
                [5 ]EHESP School of Public Health, Sorbonne Paris Cité, EA MOS, Rennes, France
                Clínica Universidad de Navarra, SPAIN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: WK CV SD MS CC SB. Performed the experiments: WK CV SD MS CC SB. Analyzed the data: WK CV SD SB. Contributed reagents/materials/analysis tools: WK CV SD SB. Wrote the paper: WK CV SD MS CC SB. Collected health data: WK MS. Geocoded the cases to the census-block level: WK. Guarantees quality assurance and rigor: CV. Interpretation of results: WK CV SD SB. The drafting of article: WK CV SD CC SB.

                Article
                PONE-D-15-43954
                10.1371/journal.pone.0153431
                4833352
                27082113
                4e1888f1-1c1c-4e1c-9575-a55d6bdbda22
                © 2016 Kihal-Talantikite et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 8 October 2015
                : 29 March 2016
                Page count
                Figures: 0, Tables: 3, Pages: 15
                Funding
                Funded by: French Biomedicine Agency
                Award Recipient :
                This study was supported by grants from French Biomedicine Agency.
                Categories
                Research Article
                Medicine and Health Sciences
                Surgical and Invasive Medical Procedures
                Transplantation
                Organ Transplantation
                Renal Transplantation
                Medicine and Health Sciences
                Surgical and Invasive Medical Procedures
                Urinary System Procedures
                Renal Transplantation
                Medicine and Health Sciences
                Nephrology
                Medical Dialysis
                Medicine and Health Sciences
                Nephrology
                Chronic Kidney Disease
                Earth Sciences
                Geography
                Human Geography
                Neighborhoods
                Social Sciences
                Human Geography
                Neighborhoods
                Medicine and Health Sciences
                Endocrinology
                Endocrine Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Metabolic Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Cardiovascular Medicine
                Cardiovascular Diseases
                Medicine and Health Sciences
                Nephrology
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Multivariate Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Multivariate Analysis
                Custom metadata
                All data used for this research were extracted from the REIN registry, coordinated and supported by the French Biomedecine Agency. The access to national data is regulated by a scientific committee of French Biomedecine Agency which analyzes each request, and so cannot be made publicly available due to legal restrictions. Data are available upon request. If readers need information about the data from the REIN registry, they can contact Dr. Cecile Couchoud who coordinates the REIN at the national level (email adress: cecile.couchoud@ 123456biomedecine.fr ).

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