Faculty Bibliography

Developing real-world evidence from electronic health records (EHR) is vital to advance kidney transplantation (KT). We assessed the feasibility of studying KT using the Epic Cosmos aggregated EHR dataset, which includes 274 million unique individuals cared for in 238 U.S. health systems, by comparing it with the Scientific Registry of Transplant Recipients (SRTR). We identified 69,418 KT recipients transplanted between January 2014 and December 2022 in Cosmos (39.4% of all US KT transplants during this period). Demographics and clinical characteristics of recipients captured in Cosmos were consistent with the overall SRTR cohort. Survival estimates were generally comparable, although there were some differences in long-term survival. At 7 years post-transplant, patient survival was 80.4% in Cosmos and 77.8% in SRTR. Multivariable Cox regression showed consistent associations between clinical factors and mortality in both cohorts, with minor discrepancies in the associations between death and both age and race. In summary, Cosmos provides a reliable platform for KT research, allowing EHR-level clinical granularity not available with either the transplant registry or healthcare claims. Consequently, Cosmos will enable novel analyses to improve our understanding of KT management on a national scale.

Since 2021, the Organ Procurement and Transplantation Network has reported a nearly 10-fold rise in out-of-sequence (OOS) kidney allocation, generating concern and halting development of continuous distribution policies. We report contemporary (2022-2023) practice patterns in OOS allocation using Organ Procurement and Transplantation Network data. We examined in sequence vs OOS donors with multivariable logistic regression and skipped vs OOS-accepting recipients with conditional logistic regression. Nearly 20% of kidney placements were OOS, varying from 0% to 43% acsoss organ procurement organizations; the 5 highest OOS-organ procurement organizations accounted for 29% of all OOS. Of OOS kidneys, 33% were declined ≥100 times in the standard allocation sequence and 51% were declined by ≥10 centers before OOS allocation began; 4.5% were made without any in-sequence declines. Nearly, all OOS offers were open offers. OOS kidneys were more likely to be from female, Black, older, donation after cardiac death, hypertensive, diabetic, and elevated creatinine donors. Candidates receiving OOS kidneys were more likely female, Asian, and older than skipped candidates. Higher-volume centers and centers with more White, fewer Hispanic, and more educated waiting list patients underwent transplantation disproportionately with more OOS kidneys. These findings suggest that the current, highly variable, discretionary use of OOS might exacerbate disparities, yet the impact of OOS on organ utilization cannot be determined with data now collected.

Graft failure and recipient death with functioning graft are important competing outcomes after kidney transplantation. Risk prediction models typically censor for the competing outcome thereby overestimating the cumulative incidence. The magnitude of this overestimation is not well described in real-world transplant data. This retrospective cohort study analyzed data from the European Collaborative Transplant Study (n = 125 250) and from the American Scientific Registry of Transplant Recipients (n = 190 258). Separate cause-specific hazard models using donor and recipient age as continuous predictors were developed for graft failure and recipient death. The hazard of graft failure increased quadratically with increasing donor age and decreased decaying with increasing recipient age. The hazard of recipient death increased linearly with increasing donor and recipient age. The cumulative incidence overestimation due to competing risk-censoring was largest in high-risk populations for both outcomes (old donors/recipients), sometimes amounting to 8.4 and 18.8 percentage points for graft failure and recipient death, respectively. In our illustrative model for posttransplant risk prediction, the absolute risk of graft failure and death is overestimated when censoring for the competing event, mainly in older donors and recipients. Prediction models for absolute risks should treat graft failure and death as competing events.

BACKGROUND:In recent years, changes to US organ allocation have aimed to improve equity and accessibility across regions. The Organ Procurement and Transplantation Network plans to adopt continuous liver distribution, prioritizing candidates based on a weighted composite allocation score (CAS) incorporating proximity, ABO types, medical urgency, and pediatric priority. The Liver Committee has requested research on CAS variations that account for geographical heterogenicity. METHODS:We describe a method for designing a geographically heterogeneous CAS with targeted broader sharing (CAS-TBS) to balance the highly variable geographic distributions of liver transplant listings and liver donations. CAS-TBS assigns each donor hospital to either broader sharing or nearby sharing, adjusting donor-candidate distance allocation points accordingly. RESULTS:We found that to reduce geographic disparity in the median Model for End-stage Liver Disease at transplant (MMaT), >75% of livers recovered in regions 2 and 10 should be distributed with broader sharing, whereas 95% of livers recovered in regions 5 and 1 should be distributed with nearby sharing. In a 3-y simulation of liver allocation, CAS-TBS decreased MMaT by 2.1 points in high-MMaT areas such as region 5 while increasing MMaT only by 0.65 points in low-MMaT areas such as region 3. CAS-TBS significantly decreased median transport distance from 202 to 167 nautical miles under acuity circles and decreased waitlist deaths. CONCLUSIONS:Our CAS-TBS design methodology could be applied to design geographically heterogeneous allocation scores that reflect transplant community values and priorities within the continuous distribution project of the Organ Procurement and Transplantation Network. In our simulations, the incremental benefit of CAS-TBS over CAS was modest.

INTRODUCTION/BACKGROUND:ChatGPT has shown the ability to answer clinical questions in general medicine but may be constrained by the specialized nature of kidney transplantation. Thus, it is important to explore how ChatGPT can be used in kidney transplantation and how its knowledge compares to human respondents. METHODS:We prompted ChatGPT versions 3.5, 4, and 4 Visual (4 V) with 12 multiple-choice questions related to six kidney transplant cases from 2013 to 2015 American Society of Nephrology (ASN) fellowship program quizzes. We compared the performance of ChatGPT with US nephrology fellowship program directors, nephrology fellows, and the audience of the ASN's annual Kidney Week meeting. RESULTS:Overall, ChatGPT 4 V correctly answered 10 out of 12 questions, showing a performance level comparable to nephrology fellows (group majority correctly answered 9 of 12 questions) and training program directors (11 of 12). This surpassed ChatGPT 4 (7 of 12 correct) and 3.5 (5 of 12). All three ChatGPT versions failed to correctly answer questions where the consensus among human respondents was low. CONCLUSION/CONCLUSIONS:Each iterative version of ChatGPT performed better than the prior version, with version 4 V achieving performance on par with nephrology fellows and training program directors. While it shows promise in understanding and answering kidney transplantation questions, ChatGPT should be seen as a complementary tool to human expertise rather than a replacement.

BACKGROUND:The number of deceased donor kidney transplants has been increasing and is at a record high, yet nonuse of kidneys recovered for transplantation has risen to 25.8% following circular kidney allocation system based on 250-nautical-mile circles implemented on March 15, 2021 (KAS250). METHODS:Using Scientific Registry of Transplant Recipients data, we studied all deceased donor kidneys recovered for transplant from March 15, 2019, to January 31, 2023. We calculated the association of multiple factors with kidney nonuse, including increasing recovery of kidneys from nonideal donors, delays in offer acceptance observed under KAS250, and impacts of COVID-19. RESULTS:In the 2 y before KAS250, the nonuse rate was 21.2%. Had this rate continued, 2334 more kidneys would have been transplanted through January 2023. We estimated that about 769 of these nonused kidneys (33%) were associated with offer acceptance delays under KAS250; about 994 of these nonused kidneys (43%) were associated with increased prevalence of nonideal donors: donation after circulatory death donors, older donors, and donors with elevated peak serum creatinine; and about 542 of these nonused kidneys (23%) were associated with an otherwise unexplained gradual upward trend in nonuse of recovered kidneys across the pre-KAS250 and KAS250 eras. The overall impact of COVID-19 on the nonuse rate was not significant. CONCLUSIONS:The rise in kidney nonuse rate was significantly associated with both increased recovery of nonideal donors, and with KAS250 allocation complexity and delays. Increasing recovery of kidneys from nonideal donors benefits patients because recovering more kidneys increases the number of kidneys available for transplant.

BACKGROUND:Since February 2020, exception points have been allocated equivalent to the median model for end-stage liver disease at transplant within 250 nautical miles of the transplant center (MMaT/250). We compared transplant rate and waitlist mortality for hepatocellular carcinoma (HCC) exception, non-HCC exception, and non-exception candidates to determine whether MMaT/250 advantages (or disadvantages) exception candidates. METHODS:Using Scientific Registry of Transplant Recipients data, we identified 23 686 adult, first-time, active, deceased donor liver transplant (DDLT) candidates between February 4, 2020, and February 3, 2022. We compared DDLT rates using Cox regression, and waitlist mortality/dropout using competing risks regression in non-exception versus HCC versus non-HCC candidates. RESULTS:Within 24 mo of study entry, 58.4% of non-exception candidates received DDLT, compared with 57.8% for HCC candidates and 70.5% for non-HCC candidates. After adjustment, HCC candidates had 27% lower DDLT rate (adjusted hazard ratio = 0.680.730.77) compared with non-exception candidates. However, waitlist mortality for HCC was comparable to non-exception candidates (adjusted subhazard ratio [asHR] = 0.931.031.15). Non-HCC candidates with pulmonary complications of cirrhosis or cholangiocarcinoma had substantially higher risk of waitlist mortality compared with non-exception candidates (asHR = 1.271.702.29 for pulmonary complications of cirrhosis, 1.352.043.07 for cholangiocarcinoma). The same was not true of non-HCC candidates with exceptions for other reasons (asHR = 0.540.881.44). CONCLUSIONS:Under MMaT/250, HCC, and non-exception candidates have comparable risks of dying before receiving liver transplant, despite lower transplant rates for HCC. However, non-HCC candidates with pulmonary complications of cirrhosis or cholangiocarcinoma have substantially higher risk of dying before receiving liver transplant; these candidates may merit increased allocation priority.

BACKGROUND/UNASSIGNED:Prioritization of HLA antigen-level matching in the US kidney allocation system intends to improve post-transplant survival but causes racial disparities and thus has been substantially de-emphasized. Recently, molecular matching based on eplets has been found to improve risk stratification compared to antigen matching. METHODS/UNASSIGNED:To assign eplets unambiguously, we utilized a cohort of 5193 individuals with high resolution allele-level HLA genotypes from the National Kidney Registry. Using repeated random sampling to simulate donor-recipient genotype pairings based on the ethnic composition of the historical US deceased donor pool, we profiled the percentage of well-matched donors for candidates by ethnicity. RESULTS/UNASSIGNED:The percentage of well-matched donors with zero-DR/DQ eplet mismatch was 3-fold less racially disparate for Black and Asian candidates than percentage of donors with zero-ABDR antigen mismatches, and 2-fold less racially disparate for Latino candidates. For other HLA antigen and eplet mismatch thresholds, the percentage of well-matched donors was more similar across candidate ethnic groups. CONCLUSIONS/UNASSIGNED:Compared to the current zero-ABDR antigen mismatch, prioritizing a zero-DR/DQ eplet mismatch in allocation would decrease racial disparities and increase the percentage of well-matched donors. High resolution HLA deceased donor genotyping would enable unambiguous assignment of eplets to operationalize molecular mismatch metrics in allocation. KEY POINTS/UNASSIGNED: