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Mohan S, Yu M, Maclay LM, Adler JT, Huml AM, Schold JD, Husain SA. Outcomes for Patients With a Deceased Donor Kidney Offer in the New Allocation System. Kidney Int Rep 2025; 10:1111-1121. [PMID: 40303214 PMCID: PMC12034855 DOI: 10.1016/j.ekir.2025.01.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2024] [Revised: 01/13/2025] [Accepted: 01/13/2025] [Indexed: 05/02/2025] Open
Abstract
Introduction In the United States (US), disparities in access to kidney transplantation exist for waitlisted candidates with end-stage kidney disease. Meanwhile, changes in kidney allocation policy have been associated with a dramatic increase in the number of organ offers declined before an organ is successfully placed. Methods We describe transplant and mortality rates for waitlisted candidates from 2015 to 2022 following these allocation changes. Results Among 249,145 incident waitlisted adults, 180,039 received at least 1 offer and were included in the study. Of these, 37.7% received a deceased donor kidney allograft, 14.7% received a living donor allograft, 7.4% died while on the waiting list, 12.7% were removed, and 27.5% were still waitlisted by the study end period. Overall, candidates' median number of days to receiving their first offer declined from 20 (7-48) in 2015 to 5 (2-13) in 2022. Candidates who died while on the waiting list received a median of 25 (9-56) offers and candidates who were removed received a median of 22 (8-53) offers during the study period. The total number of offers generated by the match-run algorithm, including those from nonutilized kidneys, increased sharply from 7,911,688 offers in 2015 to 13,682,914 in 2019, and to 29,332,516 in 2022. Conclusion These findings emphasize the inefficiencies inherent in our current allocation algorithms and the need to rethink how waitlisted patients are prioritized for a given deceased donor organ in order to maximize the probability of appropriate utilization of lifesaving organs .
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Affiliation(s)
- Sumit Mohan
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Columbia University Renal Epidemiology Group, New York, New York, USA
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Miko Yu
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Columbia University Renal Epidemiology Group, New York, New York, USA
| | - Lindsey M. Maclay
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Columbia University Renal Epidemiology Group, New York, New York, USA
| | - Joel T. Adler
- Division of Transplantation, Department of Surgery and Perioperative Care, Dell Medical School at the University of Texas at Austin, Austin, Texas, USA
| | - Anne M. Huml
- Department of Kidney Medicine, Cleveland Clinic, Cleveland, Ohio, USA
| | - Jesse D. Schold
- Department of Surgery, University of Colorado – Anschutz Medical Campus, Aurora, Colorado, USA
- Department of Epidemiology, School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - S. Ali Husain
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Columbia University Renal Epidemiology Group, New York, New York, USA
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