Evidence map›Paper›PMID 39366540›Full record

ArticleAmerican journal of kidney diseases : the official journal of the National Kidney Foundation2025

Associations Among Circle-Based Kidney Allocation, Center Waiting Time, and Likelihood of Deceased-Donor Kidney Transplantation.

David C Cron, Arnold E Kuk, Layla Parast, S Ali Husain, Kristen L King, Miko Yu, Sumit Mohan, Joel T Adler

Abstract read
In one paragraph

Article in American journal of kidney diseases : the official journal of the National Kidney Foundation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Kidney medicine · 2026
    Article
  2. Article
  3. Association between out-of-sequence allocation and deceased donor kidney nonuse across organ procurement organizations.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2025
    Article
  4. Optimizing kidney allocation: challenges and solutions.Current opinion in organ transplantation · 2025
    Review
  5. Short-term Pains for Long-term Gains? In Search of More Solutions to Inequities in Kidney Transplantation.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

David C CronDepartment of Surgery, Massachusetts General Hospital, Boston, Massachusetts; Center for Surgery and Public Health, Brigham and Women's Hospital, Boston, Massachusetts.
Arnold E KukBiomedical Data Sciences Hub, University of Texas, Austin, Texas.
Layla ParastDell Medical School, and Department of Statistics and Data Science, University of Texas, Austin, Texas.
S Ali HusainDepartment of Medicine, Division of Nephrology, Columbia University Medical Center, New York, New York; Columbia University Renal Epidemiology (CURE) Group, New York, New York.
Kristen L KingDepartment of Medicine, Division of Nephrology, Columbia University Medical Center, New York, New York; Columbia University Renal Epidemiology (CURE) Group, New York, New York.
Miko YuDepartment of Medicine, Division of Nephrology, Columbia University Medical Center, New York, New York; Columbia University Renal Epidemiology (CURE) Group, New York, New York.
Sumit MohanDepartment of Medicine, Division of Nephrology, Columbia University Medical Center, New York, New York; Columbia University Renal Epidemiology (CURE) Group, New York, New York.
Joel T AdlerDivision of Transplantation, Department of Surgery and Perioperative Care, University of Texas, Austin, Texas. Electronic address: joel.adler@austin.utexas.edu.

Funding

Using Decision Making Science to Optimize Deceased Donor Kidney AllocationK23DK133729 · NIDDK · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI HUSAIN, SYED ALI · 2022 to 2025
$678k
A mixed-methods approach to identify factors determining utilization of marginal quality deceased donor livers for transplantationF32DK128981 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI CRON, DAVID COULTON · 2021 to 2022
$146k
AHRQ HHS K08 HS028476NIDDK NIH HHS F32 DK128981NIDDK NIH HHS K23 DK133729
6 · The paper itself

Abstract

RATIONALE &

objectiveThe kidney allocation system (KAS250), using circle-based distribution, attempts to address geographic disparities through broader sharing of deceased-donor kidney allografts. This study evaluated the association between KAS250 and likelihood of deceased-donor kidney transplantation (DDKT) among wait-listed candidates, and whether the policy has differentially affected centers with shorter versus longer waiting time. STUDY

designRetrospective cohort study. SETTING &

participants160,941 candidates waitlisted at 176 transplant centers between March 2017 and March 2024. EXPOSURE: KAS250 allocation policy. OUTCOME: Rate of DDKT. ANALYTICAL APPROACH: Multivariable Cox regression, modeling KAS250 as a time-dependent variable.

resultsKAS250 was not independently associated with likelihood of DDKT overall (HR, 1.01 vs pre-KAS250 [95% CI, 0.97-1.04]). KAS250's association with likelihood of DDKT varied across centers from HR, 0.18 (DDKT less likely after KAS250), to HR, 17.12 (DDKT more likely) and varied even among neighboring centers. KAS250 was associated with decreased DDKT at 25.6% and increased DDKT at 18.2% of centers. Centers with previously long median waiting times (57+months) experienced increased likelihood of DDKT after KAS250 (HR, 1.20 [95% CI, 1.15-1.26]) whereas centers with previously short median waiting times (6-24 months; HR, 0.88 [95% CI, 0.84-0.92]) experienced decreased likelihood of DDKT. LIMITATIONS: Retrospective study of allocation policy changes, confounded by multiple changes over the study time frame.

conclusionsAssociation between KAS250 and DDKT varied across centers. For 1 in 4 centers, DDKT was less likely after KAS250 relative to pre-KAS250 trends. Candidates at centers with previously long waiting times experienced an increased likelihood of DDKT after KAS250. Thus, broader distribution of kidneys may be associated with improved equity in access to DDKT, but additional strategies may be needed to minimize disparities between centers. PLAIN-LANGUAGE SUMMARY: This study examines how a recent policy change, KAS250, aimed at broadening the geographic sharing of deceased-donor kidneys, has impacted likelihood of kidney transplantation in the United States. Historically, kidney allocation occurred within local geographic boundaries, leading to unequal rates of transplantation across regions. KAS250, implemented in March 2021, replaced this system with a broader allocation radius of 250 miles around the donor hospital. Using national registry data, the study found that while there was no overall significant increase in the likelihood of transplantation nationally under KAS250, the policy's effect varied widely even among neighboring transplant centers. One quarter of centers experienced a decrease in the likelihood of DDKT after KAS250. In contrast, centers with longer pre-KAS250 waiting times experienced an increased likelihood of transplantation, suggesting some success in reducing disparities between centers. Ongoing surveillance will be needed to ensure KAS250 is meeting the intended aim of more equitably distributing organs.

Indexed as

Kidney Failure, ChronicKidney TransplantationTissue and Organ ProcurementWaiting ListsAdultFemaleHumansMaleMiddle AgedRetrospective StudiesTime FactorsTissue DonorsUnited StatesAccess to transplantequitygeographic disparitiesKAS250kidney allocationkidney transplantation

Identifiers

PMID39366540
PMCPMC11930355

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.