Evidence map›Paper›PMID 40906047›Full record

ArticleThe patient2026

Do Patients Think it's Worth Waiting for a Kidney? Evidence from a Discrete-Choice Experiment.

Ching-Heng Wu, Shelby D Reed, Jui-Chen Yang, Sanjay Mehrotra, Lisa McElroy, Juan Marcos Gonzalez

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Article in The patient, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Ching-Heng WuRTI-Health Solutions, Durham, NC, USA. chinghengwu@rti.org.
Shelby D ReedDepartment of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA.
Jui-Chen YangDuke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA.
Sanjay MehrotraNorthwestern University, Evanston, IL, USA.
Lisa McElroyDepartment of Surgery, Duke University School of Medicine, Durham, NC, USA.
Juan Marcos GonzalezDepartment of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA.ORCID 0000-0002-5386-0907

Funding

Rescuing Kidneys at Risk of DiscardR01DK118425 · NIDDK · NORTHWESTERN UNIVERSITY AT CHICAGO · PI MEHROTRA, SANJAY · 2019 to 2022
$2.8M
Increasing Access to Transplant through Improved Clinical Decision MakingK08MD017632 · NIMHD · DUKE UNIVERSITY · PI Lisa M McElroy · 2022 to 2026
$551k
Foundation for the National Institutes of Health 1R01DK118425-01A1NIDDK NIH HHS R01 DK118425NIMHD NIH HHS K08 MD017632
6 · The paper itself

Abstract

objectiveNearly 30% of kidneys from deceased donors are discarded annually in the USA. A recent study indicated that a significant number of patients would accept lower-quality kidneys to avoid long waits. We expand on previous work to assess how the distribution of patient preferences for lower-quality kidneys would change with patient time on the transplant list.

methodsWe conducted a discrete-choice experiment with US pre-transplant patients waitlisted for kidneys from deceased donors. Respondents were asked to evaluate tradeoffs between expected graft survival and waiting time. We used a logit-based regression with patient covariates to explain membership of three patient-preference phenotypes previously identified with these data. Specifically, we tested the degree to which phenotype membership changed with waiting time and how such changes were moderated by observable patient characteristics such as age, insulin use, recipient function, time on dialysis, and household income.

resultsWaiting time had a nonlinear effect on phenotype probabilities, with more patients expected to be willing to accept lower-quality kidneys as waiting time increases. Patients with longer insulin dependence, lower income, and limited function were more likely to accept lower-quality kidneys. Higher income was significantly associated with the probability of being willing to wait for better future kidneys. Dialysis time had no significant effect.

conclusionsOur analysis provides insights into time-varying effects using cross-sectional data. Results suggest that patient preferences for organ acceptability vary with waiting time and are moderated by health status and socioeconomic factors. Longer waits and worse health statuses were generally associated with greater willingness to accept lower-quality kidneys.

Indexed as

Choice BehaviorKidney TransplantationPatient PreferenceTissue and Organ ProcurementWaiting ListsAdultAgedFemaleGraft SurvivalHumansMaleMiddle AgedTime FactorsTissue DonorsUnited States

Identifiers

PMID40906047
PMCPMC13213703

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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.