Literature DB >> 35301050

Referral and Evaluation for Kidney Transplantation Following Implementation of the 2014 National Kidney Allocation System.

Rachel E Patzer1, Mengyu Di2, Rebecca Zhang3, Laura McPherson4, Derek A DuBay5, Matthew Ellis6, Joshua Wolf7, Heather Jones8, Carlos Zayas5, Laura Mulloy9, Amber Reeves-Daniel10, Sumit Mohan11, Aubriana C Perez2, Amal N Trivedi12, Stephen O Pastan13.   

Abstract

RATIONALE &
OBJECTIVE: The national kidney allocation system (KAS) implemented in December 2014 in the United States redefined the start of waiting time from the time of waitlisting to the time of kidney failure. Waitlisting has declined post-KAS, but it is unknown if this is due to transplant center practices or changes in dialysis facility referral and evaluation. The purpose of this study was to assess the impact of the 2014 KAS policy change on referral and evaluation for transplantation among a population of incident and prevalent patients with kidney failure. STUDY
DESIGN: Cohort study. SETTING & PARTICIPANTS: 37,676 incident (2012-2016) patients in Georgia, North Carolina, and South Carolina identified within the US Renal Data System at 9 transplant centers and followed through December 2017. A prevalent population of 6,079 patients from the same centers receiving maintenance dialysis in 2012 but not referred for transplantation in 2012. EXPOSURE: KAS era (pre-KAS vs post-KAS). OUTCOME: Referral for transplantation, start of transplant evaluation, and waitlisting. ANALYTICAL APPROACH: Multivariable time-dependent Cox models for the incident and prevalent population.
RESULTS: Among incident patients, KAS was associated with increased referrals (adjusted HR, 1.16 [95% CI, 1.12-1.20]) and evaluation starts among those referred (adjusted HR, 1.16 [95% CI, 1.10-1.21]), decreased overall waitlisting (adjusted HR, 0.70 [95% CI, 0.65-0.76]), and lower rates of active waitlisting among those evaluated compared to the pre-KAS era (adjusted HR, 0.81 [95% CI, 0.74-0.90]). Among the prevalent population, KAS was associated with increases in overall waitlisting (adjusted HR, 1.74 [95% CI, 1.15-2.63]) and active waitlisting among those evaluated (adjusted HR, 2.01 [95% CI, 1.16-3.49]), but had no significant impact on referral or evaluation starts among those referred. LIMITATIONS: Limited to 3 states, residual confounding.
CONCLUSIONS: In the southeastern United States, the impact of KAS on steps to transplantation was different among incident and prevalent patients with kidney failure. Dialysis facilities referred more incident patients and transplant centers evaluated more incident patients after implementation of KAS, but fewer evaluated patients were placed onto the waitlist. Changes in dialysis facility and transplant center behaviors after KAS implementation may have influenced the observed changes in access to transplantation.
Copyright © 2022 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Allocation time; health care access; health care policy; kidney allocation policy (KAS); kidney failure; kidney transplantation; transplant referral; waitlisting

Year:  2022        PMID: 35301050      PMCID: PMC9470777          DOI: 10.1053/j.ajkd.2022.01.423

Source DB:  PubMed          Journal:  Am J Kidney Dis        ISSN: 0272-6386            Impact factor:   11.072


  26 in total

1.  Graphing survival curve estimates for time-dependent covariates.

Authors:  Lonni R Schultz; Edward L Peterson; Naomi Breslau
Journal:  Int J Methods Psychiatr Res       Date:  2002       Impact factor: 4.035

2.  Systematic review: kidney transplantation compared with dialysis in clinically relevant outcomes.

Authors:  M Tonelli; N Wiebe; G Knoll; A Bello; S Browne; D Jadhav; S Klarenbach; J Gill
Journal:  Am J Transplant       Date:  2011-08-30       Impact factor: 8.086

3.  A test of the association of a time-dependent state variable to survival.

Authors:  A B Cantor
Journal:  Comput Methods Programs Biomed       Date:  1995-02       Impact factor: 5.428

4.  Major Variation across Local Transplant Centers in Probability of Kidney Transplant for Wait-Listed Patients.

Authors:  Kristen L King; S Ali Husain; Jesse D Schold; Rachel E Patzer; Peter P Reese; Zhezhen Jin; Lloyd E Ratner; David J Cohen; Stephen O Pastan; Sumit Mohan
Journal:  J Am Soc Nephrol       Date:  2020-10-09       Impact factor: 10.121

5.  Investigation of the freely available easy-to-use software 'EZR' for medical statistics.

Authors:  Y Kanda
Journal:  Bone Marrow Transplant       Date:  2012-12-03       Impact factor: 5.483

6.  Racial/ethnic disparities in waitlisting for deceased donor kidney transplantation 1 year after implementation of the new national kidney allocation system.

Authors:  Xingyu Zhang; Taylor A Melanson; Laura C Plantinga; Mohua Basu; Stephen O Pastan; Sumit Mohan; David H Howard; Jason M Hockenberry; Michael D Garber; Rachel E Patzer
Journal:  Am J Transplant       Date:  2018-04-18       Impact factor: 8.086

7.  Awareness of the New Kidney Allocation System among United States Dialysis Providers with Low Waitlisting.

Authors:  Rachel E Patzer; Mohua Basu; Kayla D Smith; Laura Plantinga; Sumit Mohan; Cam Escoffery; Joyce J Kim; Taylor Melanson; Stephen O Pastan
Journal:  Am J Nephrol       Date:  2018-02-22       Impact factor: 3.754

8.  Decisional conflict between treatment options among end-stage renal disease patients evaluated for kidney transplantation.

Authors:  Laura McPherson; Mohua Basu; Jennifer Gander; Stephen O Pastan; Sumit Mohan; Michael S Wolf; Mariana Chiles; Allison Russell; Kristie Lipford; Rachel E Patzer
Journal:  Clin Transplant       Date:  2017-05-29       Impact factor: 3.456

9.  The ASCENT (Allocation System Changes for Equity in Kidney Transplantation) Study: a Randomized Effectiveness-Implementation Study to Improve Kidney Transplant Waitlisting and Reduce Racial Disparity.

Authors:  Rachel E Patzer; Kayla Smith; Mohua Basu; Jennifer Gander; Sumit Mohan; Cam Escoffery; Laura Plantinga; Taylor Melanson; Sean Kalloo; Gary Green; Alex Berlin; Gary Renville; Teri Browne; Nicole Turgeon; Susan Caponi; Rebecca Zhang; Stephen Pastan
Journal:  Kidney Int Rep       Date:  2017-02-09

10.  Simulation shows undesirable results for competing risks analysis with time-dependent covariates for clinical outcomes.

Authors:  Inga Poguntke; Martin Schumacher; Jan Beyersmann; Martin Wolkewitz
Journal:  BMC Med Res Methodol       Date:  2018-07-16       Impact factor: 4.615

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  1 in total

Review 1.  The New Distance-Based Kidney Allocation System: Implications for Patients, Transplant Centers, and Organ Procurement Organizations.

Authors:  David C Cron; Syed A Husain; Joel T Adler
Journal:  Curr Transplant Rep       Date:  2022-10-13
  1 in total

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