Evidence map›Paper›PMID 37170943›Full record

ArticleMedical decision making : an international journal of the Society for Medical Decision Making2023

Deceased Donor Kidney Transplantation for Older Transplant Candidates: A New Microsimulation Model for Determining Risks and Benefits.

Matthew B Kaufmann, Jane C Tan, Glenn M Chertow, Jeremy D Goldhaber-Fiebert

Abstract read
In one paragraph

Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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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.

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Matthew B KaufmannStanford Health Policy, Department of Health Policy, School of Medicine and Center for Health Policy, Freeman Spogli Institute, Stanford University, Stanford, CA, USA.ORCID 0000-0002-9947-936X
Jane C TanDepartment of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Glenn M ChertowDepartment of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Jeremy D Goldhaber-FiebertStanford Health Policy, Department of Health Policy, School of Medicine and Center for Health Policy, Freeman Spogli Institute, Stanford University, Stanford, CA, USA.ORCID 0000-0002-4007-5192

Funding

Stanford Health Services Research Training ProgramT32HS026128 · AHRQ · STANFORD UNIVERSITY · PI BAKER, LAURENCE C, OWENS, DOUGLAS K · 2018 to 2024
$3.6M
Mentoring Patient-Oriented Clinical Investigators in NephrologyK24DK085446 · NIDDK · STANFORD UNIVERSITY · PI CHERTOW, GLENN MATTHEW · 2010 to 2022
$1.4M
AHRQ HHS T32 HS026128NIDDK NIH HHS K24 DK085446
6 · The paper itself

Abstract

backgroundUnder the current US kidney allocation system, older candidates receive a disproportionately small share of deceased donor kidneys despite a reserve of potentially usable kidneys that could shorten their wait times. To consider potential health gains from increasing access to kidneys for these candidates, we developed and calibrated a microsimulation model of the transplantation process and long-term outcomes for older deceased donor kidney transplant candidates.

methodsWe estimated risk equations for transplant outcomes using the Scientific Registry of Transplant Recipients (SRTR), which contains data on all US transplants (2010-2019). A microsimulation model combined these equations to account for competing events. We calibrated the model to key transplant outcomes and used acceptance sampling, retaining the best-fitting 100 parameter sets. We then examined life expectancy gains from allocating kidneys even of lower quality across patient subgroups defined by age and designated race/ethnicity.

resultsThe best-fitting 100 parameter sets (among 4,000,000 sampled) enabled our model to closely match key transplant outcomes. The model demonstrated clear survival benefits for those who receive a deceased donor kidney, even a lower quality one, compared with remaining on the waitlist where there is a risk of removal. The expected gain in survival from receiving a lower quality donor kidney was consistent gains across age and race/ethnic subgroups. LIMITATIONS: Limited available data on socioeconomic factors.

conclusionsOur microsimulation model accurately replicates a range of key kidney transplant outcomes among older candidates and demonstrates that older candidates may derive substantial benefits from transplantation with lower quality kidneys. This model can be used to evaluate policies that have been proposed to address concerns that the current system disincentivizes deceased donor transplants for older patients. HIGHLIGHTS: The microsimulation model was consistent with the data after calibration and accurately simulated the transplantation process for older deceased donor kidney transplant candidates.There are clear survival benefits for older transplant candidates who receive deceased donor kidneys, even lower quality ones, compared with remaining on the waitlist.This model can be used to evaluate policies aimed at increasing transplantation among older candidates.

Indexed as

Kidney TransplantationTissue DonorsTransplant RecipientsAge FactorsComputer SimulationHumansRisk AssessmentTreatment OutcomeUnited Statescalibrationkidney transplantationmicrosimulationolder candidatesposttransplantwaitlist

Identifiers

PMID37170943
PMCPMC10330392

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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.