Faculty Bibliography

INTRODUCTION/BACKGROUND:Some living organ donors will decide to donate again at a later date. Evidence has indicated that this practice may have increased in recent years. We evaluated the incidence and outcomes of this practice to inform counseling of potential repeat donors. METHODS:Using SRTR data from 1994 to 2023, we identified 220 repeat living donors and their 415 recipients. We constructed donor comparison groups using weighting by the odds. We described clinical and lab results at 6 months, 1 year, and 2 years post-donation separately for kidney-second donors and liver-second donors. We compared all-cause graft failure for their recipients with those of comparison donors. RESULTS:The annual count of repeat living donors increased from 5 in 2018 to 25 in 2019 (p < 0.001). Of 220 donors, 159 were liver-second donors (72.3%) and 55 were kidney-second donors (25.0). The percentage of nondirected donations increased from 30.5% at first donation to 53.2% at second donation (p < 0.001). Liver-second donors had one death approximately 2.5 years post-donation. Seventeen were re-admitted and 20 experienced complications requiring an interventional procedure or re-operation. Among kidney-second donors, no deaths, re-admissions, or post-donation complications were reported. Post-donation outcomes in both groups were comparable when evaluated against organ-specific comparison donors. Recipients of repeat living donors experienced graft survival similar to recipients of comparison donors. CONCLUSIONS:Repeat living donation may be a safe practice for carefully selected living donors in the short term; however, long term safety is unknown. Outcomes for recipients are similar to recipients of comparison donors.

The proportion of deceased donor kidneys recovered for transplantation that are not transplanted reached 28% in 2023. Past research demonstrated that >90% of the non-use rate increase in the 2000s could be explained by the broadening donor pool. We used OPTN data to study kidneys recovered 2010-2023, applying causal inference methods to assess the degree to which the recent, sharp rise in the non-use rate could be explained by changes in donor clinical characteristics. Unadjusted odds of kidney non-use were 63% higher (95% CI: 56%, 70%) in 2023 vs 2018. After adjusting for donor factors, odds of non-use were only 12% (9%, 15%) higher in 2023. Both regression and propensity weighting demonstrated that 75-80% of the recent non-use rate increase can be explained by a rapidly expanding donor pool. Encouragingly, the non-use rate has not increased and remains low for above-average quality kidneys. However, the unexplained risk of non-use for kidneys in the highest kidney donor risk index quartile increased by ∼30%, potentially due to residual confounding and/or system-level, exogenous factors such as allocation policy changes. To improve placement efficiency, allocation policy should adapt to the increasingly heterogeneous donor pool by allocating kidneys differently along the donor quality spectrum.

BACKGROUND:In the 2018 Organ Procurement and Transplantation Network donor heart allocation system, patients listed for re-transplantation due to cardiac allograft vasculopathy (CAV) are assigned to Status 4 unless hemodynamic criteria are met. We aim to examine waitlist outcomes of CAV patients among adult heart transplant candidates. METHODS:We examined waitlist mortality stratified by CAV and waitlist status among adult heart transplant candidates using Scientific Registry of Transplant Recipients data from 10/1/2018-11/1/2023. We analyzed waitlist mortality using Kaplan-Meier curves and doubly-robust Cox regressions adjusted for age, gender, sex, race, and dialysis. We compared CAV to non-CAV patients by initial waitlist status, first status of interest, and time-dependent status. RESULTS:Of 21,586 listed patients, 368 were listed for CAV. CAV patients were most often listed at Status 4 with lower proportions at Status 3/2/1 compared with non-CAV patients. Status 4 and Status 3 CAV candidates demonstrated higher than expected waitlist mortality compared to non-CAV counterparts (Status 4: HR 0.51, 95% CI 0.31-0.84; p < 0.01; Status 3: HR 0.61, 95% CI 0.23-1.64; p = 0.33) with similar mortality to non-CAV patients in Status 3 and 2, respectively (Status 4: HR 0.80, 95% CI 0.48-1.35; p = 0.4; Status 3: HR 1.07, 95% CI 0.40-2.86; p = 0.89). When stratifying by status tier, CAV waitlist patients ever listed at Status 4 and 3 had a higher probability of death compared to their non-CAV counterparts (Status 4: HR 1.99, 95% CI 1.20-3.31, p < 0.01; Status 3: HR 3.06, 95% CI 1.06-8.87, p = 0.04). CONCLUSIONS:After 2018, CAV patients had a higher risk of waitlist mortality at Status 4 and 3 compared to non-CAV patients. These results suggest that CAV patients are underprioritized in the current allocation system.

PURPOSE/OBJECTIVE:In October 2018, the OPTN changed adult heart transplant (HT) allocation policy, increasing the number of adult candidates that had higher priority than pediatric candidates, potentially disadvantaging pediatric waitlist registrants. METHODS:To understand the impact of this policy change, we used SRTR data to identify 1469 pre-policy (7/2016-9/2018) and 2901 (10/2018-12/2022) post-policy pediatric (< 18 years) HT registrants. We quantified mortality and transplant risks using weighted cause-specific hazard models, and then using weighted competing risks regression. We further stratified these analyses by age to understand risks for those in direct competition with adults for organs (≥ 12 years). RESULTS:, p = 0.02). Post policy, 1-year transplant rate did not change in those < 12years (68.2%-71.0%, p = 0.77), but in those ≥ 12years, transplant rate increased (77.3%-81.0%, p = 0.003). CONCLUSIONS:Mortality on the waitlist decreased and access to HT for pediatric registrants did not decline following the 2018 policy change. The decreased mortality rate may reflect changes in patient casemix and/or improved patient care. Continued surveillance is important in ensuring equity in pediatric, and adult, HT.

BACKGROUND:Highly effective modulator therapies (HEMT) including ivacaftor (IVA) and elexacaftor/tezacaftor/ivacaftor (ETI) have transformed treatment for people with cystic fibrosis (pwCF). However, non-HEMT-responsive mutations are more common in pwCF of non-White race/ethnicity; introduction of HEMT might have exacerbated racial/ethnic disparities in CF care. METHODS:Using the Scientific Registry of Transplant Recipients, we identified all lung transplant candidates and recipients 05/2005-12/2022 and categorized them by diagnosis (CF/non-CF), race/ethnicity (non-Hispanic White/Black/Hispanic) and era [Pre-HEMT (2005-1/30/2012), IVA (1/31/2012-10/30/2019), ETI (10/31/2019-12/31/2022)]. We compared the percentage of patients listed, delisted/died, or transplanted by race/ethnicity and era. RESULTS:34,659 lung transplants were performed: 10,521 pre-HEMT, 15,944 in IVA era, and 7,888 in ETI era. Over the three eras, the percentage of lung recipients with CF of White race decreased (94.5 % to 92.4 % to 78.4 %) and of Black race (1.7 % to 2.4 % to 5.7 %) or Hispanic ethnicity increased (3.5 % to 4.6 % to 14.2 %; p < 0.001). Similarly, among candidates listed for CF over the three eras, the percentage that were of White race decreased (82.0 % vs. 78.6 % vs. 71.0 %) and of Black race (9.2 % vs. 10.0 % vs. 10.3 %) or Hispanic ethnicity increased (6.4 % vs. 8.6 % vs. 13.6 %; p < 0.001). CONCLUSION/CONCLUSIONS:The introduction of HEMT appears to have benefitted CF lung transplant candidates and recipients of Black race or Hispanic ethnicity less than those of White race. This is likely due to the higher prevalence of HEMT-ineligible CFTR mutations among Black and Hispanic patients and underscores the need for therapies aimed at non-HEMT-responsive mutations prevalent in these racial/ethnic populations.

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.