Andrew Wey

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, _2.343.32_4.71; PELD/MELD scores 33‐36, _1.702.51_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, _2.773.95_5.63; top 5 offers, _3.904.39_4.95; top 10 offers, _4.855.30_5.80). Candidates with exceptions had lower offer rates than candidates without exceptions for offers in the top 5 (ORR: hepatocellular carcinoma [HCC], _0.680.77_0.88; non‐HCC, _0.730.81_0.89) and top 10 (ORR: HCC, _0.590.65_0.71; non‐HCC, _0.690.75_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.

The Organ Procurement and Transplantation Network's Membership and Professional Standards Committee implemented an operational rule on March 1, 2017, intended to increase the number of kidneys transplanted from donors with kidney donor profile index (KDPI) ≥ 85% into recipients with poor estimated posttransplant survival (≥ 80%). Using data from the Scientific Registry of Transplant Recipients, ordinal and logistic regressions estimated, respectively, differences in kidney yield (number of transplanted kidneys per recovered donor) and offer acceptance practices before and after implementation. We included donors recovered January 1, 2016‐February 28, 2018. The odds of higher kidney yield for donors with KDPI ≥ 85% were 27% higher after implementation (odds ratio, _1.061.27_1.53), but odds were also 20% higher for donors with KDPI < 85% (_1.041.20_1.38). Thus, kidney yield was higher for all donors, with a slightly larger difference for donors with KDPI ≥ 85%. Additionally, the difference in offer acceptance before and after implementation was similar regardless of KDPI (KDPI < 85%, _0.971.02_1.07; KDPI ≥ 85%, _0.951.04_1.14). In the first year after implementation, kidney yield increased for donors with KDPI < and ≥ 85%. Thus, kidney yield from higher KDPI donors may have increased without the operational rule.

Patient mortality after listing for a solid organ transplant is a relevant, patient‐centric metric, but risk factors for patient mortality after listing present severe non‐proportional hazards. We propose piecewise exponential models (PEMs) with time‐varying effects to account for the non‐proportional hazards, and we use the LASSO to minimize the risk of overfitting. We consider two parameterizations of a PEM: The first model has an overall effect in addition to the time‐varying effects (PEM‐TID), whereas the second model has only time‐varying effects (PEM‐TD). Because the LASSO can shrink every time‐varying effect to 0, risk factors in the PEM‐TID model can have proportional effects during follow‐up. In contrast, covariates in the PEM‐TD model must have different or no effects during follow‐up. These characteristics were illustrated for patients listed for liver transplant. The PEM‐TID model had similar or better predictive performance than the PEM‐TD model, and both were better than the Cox proportional hazards model. Thus, PEMs with time‐varying effects can improve predictive performance for patient mortality after listing for a solid organ transplant.