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 and
Jeremy D. Goldhaber-Fiebert
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Matthew B. Kaufmann: Stanford Health Policy, Department of Health Policy, School of Medicine and Center for Health Policy, Freeman Spogli Institute, Stanford University, Stanford, CA, USA
Jane C. Tan: Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
Glenn M. Chertow: Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
Jeremy D. Goldhaber-Fiebert: Stanford Health Policy, Department of Health Policy, School of Medicine and Center for Health Policy, Freeman Spogli Institute, Stanford University, Stanford, CA, USA
Medical Decision Making, 2023, vol. 43, issue 5, 576-586
Abstract:
Background Under 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. Methods We 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. Results The 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. Conclusions Our 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.
Keywords: kidney transplantation; waitlist; posttransplant; older candidates; microsimulation; calibration (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:43:y:2023:i:5:p:576-586
DOI: 10.1177/0272989X231172169
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