Faculty Bibliography

BACKGROUND:In the context of the organ shortage, donation after circulatory death (DCD) provides an opportunity to expand the donor pool. Although deceased-donor liver transplantation from DCD donors has expanded, DCD livers continue to be discarded at elevated rates; the use of DCD livers from older donors, or donors with comorbidities, is controversial. METHODS:Using US registry data from 2009 to 2020, we identified 1564 candidates on whose behalf a DCD liver offer was accepted ("acceptors") and 16 981 candidates on whose behalf the same DCD offers were declined ("decliners"). We characterized outcomes of decliners using a competing risk framework and estimated the survival benefit (adjusted hazard ratio [95% confidence interval]) of accepting DCD livers using Cox regression. RESULTS:Within 10 y of DCD offer decline, 50.9% of candidates died or were removed from the waitlist before transplantation with any type of allograft. DCD acceptors had lower mortality compared with decliners at 10 y postoffer (35.4% versus 48.9%, P < 0.001). After adjustment for candidate covariates, DCD offer acceptance was associated with a 46% reduction in mortality (0.54 [0.49-0.61]). Acceptors of older (age ≥50), obese (body mass index ≥30), hypertensive, nonlocal, diabetic, and increased risk DCD livers had 44% (0.56 [0.42-0.73]), 40% (0.60 [0.49-0.74]), 48% (0.52 [0.41-0.66]), 46% (0.54 [0.45-0.65]), 32% (0.68 [0.43-1.05]), and 45% (0.55 [0.42-0.72]) lower mortality risk compared with DCD decliners, respectively. CONCLUSIONS:DCD offer acceptance is associated with considerable long-term survival benefits for liver transplant candidates, even with older DCD donors or donors with comorbidities. Increased recovery and utilization of DCD livers should be encouraged.

BACKGROUND:The Organ Procurement and Transplantation Network (OPTN) is eliminating geographic boundaries in liver allocation, in favor of continuous distribution. Continuous distribution allocates organs via a composite allocation score (CAS): a weighted sum of attributes like medical urgency, candidate biology, and placement efficiency. The opportunity this change represents, to include new variables and features for prioritizing candidates, will require lengthy and contentious discussions to establish community consensus. Continuous distribution could instead be implemented rapidly by computationally translating the allocation priorities for pediatric, status 1, and O/B blood type liver candidates that are presently implemented via geographic boundaries into points and weights in a CAS. METHODS:Using simulation with optimization, we designed a CAS that is minimally disruptive to existing prioritizations, and that eliminates geographic boundaries and minimizes waitlist deaths without harming vulnerable populations. RESULTS:Compared with Acuity Circles (AC) in a 3-year simulation, our optimized CAS decreased deaths from 7771.2 to 7678.8 while decreasing average (272.66 NM vs. 264.30 NM) and median (201.14 NM vs. 186.49 NM) travel distances. Our CAS increased travel only for high MELD and status 1 candidates (423.24 NM vs. 298.74 NM), and reduced travel for other candidates (198.98 NM vs. 250.09 NM); overall travel burden decreased. CONCLUSION/CONCLUSIONS:Our CAS reduced waitlist deaths by sending livers for high-MELD and status 1 candidates farther, while keeping livers for lower MELD candidates nearby. This advanced computational method can be applied again after wider discussions of adding new priorities conclude; our method designs score weightings to achieve any specified feasible allocation outcomes.

Acuity circles (AC), the new liver allocation system, was implemented on February 4, 2020. Difference-in-differences analyses estimated the effect of AC on adjusted deceased donor transplant and offer rates across Pediatric End-Stage Liver Disease (PELD) and Model for End-Stage Liver Disease (MELD) categories and types of exception statuses. The offer rates were the number of first offers, top 5 offers, and top 10 offers on the match run per person-year. Each analysis adjusted for candidate characteristics and only used active candidate time on the waiting list. The before-AC period was February 4, 2019, to February 3, 2020, and the after-AC period was February 4, 2020, to February 3, 2021. Candidates with PELD/MELD scores 29 to 32 and PELD/MELD scores 33 to 36 had higher transplant rates than candidates with PELD/MELD scores 15 to 28 after AC compared with before AC (transplant rate ratios: PELD/MELD scores 29-32, _2.34 3.32_4.71 ; PELD/MELD scores 33-36, _1.70 2.51_3.71 ). Candidates with PELD/MELD scores 29 or higher had higher offer rates than candidates with PELD/MELD scores 15 to 28, and candidates with PELD/MELD scores 29 to 32 had the largest difference (offer rate ratios [ORR]: first offers, _2.77 3.95_5.63 ; top 5 offers, _3.90 4.39_4.95 ; top 10 offers, _4.85 5.30_5.80 ). Candidates with exceptions had lower offer rates than candidates without exceptions for offers in the top 5 (ORR: hepatocellular carcinoma [HCC], _0.68 0.77_0.88 ; non-HCC, _0.73 0.81_0.89 ) and top 10 (ORR: HCC, _0.59 0.65_0.71 ; non-HCC, _0.69 0.75_0.81 ). Recipients with PELD/MELD scores 15 to 28 and an HCC exception received a larger proportion of donation after circulatory death (DCD) donors after AC than before AC, although the differences in the liver donor risk index were comparatively small. Thus, candidates with PELD/MELD scores 29 to 34 and no exceptions had better access to transplant after AC, and donor quality did not notably change beyond the proportion of DCD donors.

Status 1A liver transplant candidates are given the highest medical priority for the allocation of deceased donor livers. Organ Procurement and Transplantation Network (OPTN) policy requires physicians to certify that a candidate has a life expectancy without a transplant of less than 7 days for that candidate to be given status 1A. Additionally, candidates receiving status 1A must have one of six medical conditions listed in policy. Using Scientific Registry of Transplant Recipients data from all prevalent liver transplant candidates from 2010 to 2020, we used a bias-corrected Kaplan-Meier model to calculate the survival of status 1A candidates and to determine their life expectancy without a transplant. We found that status 1A candidates have a life expectancy without a transplant of 24 (95% CI 20-46) days-over three times longer than what policy requires for status 1A designation. We repeated the analysis for subgroups of status 1A candidates based on the medical conditions that grant status 1A. We found that none of these subgroups met the life expectancy requirement. Harmonizing OPTN policy with observed data would sustain the integrity of the allocation process.