L. Liyanage1, D. Akizhanov1, S. Patel1, D.L. Segev1,2, A. Massie1, D. Stewart1, S. Gentry1 1NYU Langone, Department Of Surgery, New York, NY, USA 2Scientific Registry of Transplant Recipients, Minneapolis, MN, USA
Introduction: Out of sequence (OOS) allocation of kidneys skips candidates with higher priority on the match run and is meant to occur in exceptional circumstances. However, its usage has increased from 3-5% before 2021 to 20% in 2023. Given OOS allocation circumvents the standard allocation system (SA), it has the potential to exacerbate existing disparities in access to transplantation. We sought to better understand OOS practice patterns, including donor characteristics of those kidneys used OOS, transplant center utilization, and recipients receiving these OOS kidneys.
Methods: OPTN data from January 1, 2022 to December 31, 2023 were used. We examined donor characteristics associated with OOS vs. SA among transplanted kidneys using multivariable logistic regression. To examine candidate factors related to OOS acceptance vs. being the last skipped candidate on the national waitlist before OOS placement, or the last skipped candidate at the same center as the OOS placement, we built two logistic regression models conditioning on donor ID. Lorenz curve was used to examine center distribution.
Results: Kidneys from donors who were female (OR 1.14, p<0.001), Black (OR 1.19, p<0.001), older (OR 1.22, p<0.001), hypertensive (OR 1.23, p<0.001), diabetic (OR 1.15, p<0.01), and had elevated creatinine (OR 1.27, p<0.001) were more likely to have been allocated OOS. The odds of receiving an OOS kidney (vs. being skipped on the national waitlist) were higher for females (vs. males) (OR 1.15, p<0.01), Asians (vs. Whites) (OR 1.49, p<0.001), and older compared to younger patients (OR 1.38, p<0.001) (Figure A). Hispanic, Asian and older candidates had a higher odds of receiving an OOS kidney on the center waitlist (OR 1.30, 1.78, 1.56, respectively, p<0.001) (Figure B). OOS kidney transplants were clustered among fewer centers compared to SA (Gini coef: 0.65 vs. 0.48). The top 20 centers with the highest number of OOS transplants had a significantly higher proportion of females, Whites, and candidates with private insurance and higher education on their waitlists compared with 54 centers that used no OOS kidneys (p<0.001).
Conclusion: OOS kidneys are associated with non-ideal donor characteristics, potentially making these kidneys harder to place via standard allocation. OOS kidney transplantation occurs at disproportionately fewer centers with markedly different waitlist compositions from non-OOS centers, suggesting patients may not have equal access to deceased donor kidney transplantation.