Department of Mathematics, United States Naval Academy, Annapolis, Maryland, USA.
Department of Pediatrics, Johns Hopkins University, Baltimore, Maryland, USA.
Am J Transplant. 2021 Sep;21(9):3157-3162. doi: 10.1111/ajt.16621. Epub 2021 May 13.
The SRTR maintains the liver-simulated allocation model (LSAM), a tool for estimating the impact of changes to liver allocation policy. Integral to LSAM is a model that predicts the decision to accept or decline a liver for transplant. LSAM implicitly assumes these decisions are made identically for adult and pediatric liver transplant (LT) candidates, which has not been previously validated. We applied LSAM's decision-making models to SRTR offer data from 2013 to 2016 to determine its efficacy for adult (≥18) and pediatric (<18) LT candidates, and pediatric subpopulations-teenagers (≥12 to <18), children (≥2 to <12), and infants (<2)-using the area under the receiver operating characteristic (ROC) curve (AUC). For nonstatus 1A candidates, all pediatric subgroups had higher rates of offer acceptance than adults. For non-1A candidates, LSAM's model performed substantially worse for pediatric candidates than adults (AUC 0.815 vs. 0.922); model performance decreased with age (AUC 0.898, 0.806, 0.783 for teenagers, children, and infants, respectively). For status 1A candidates, LSAM also performed worse for pediatric than adult candidates (AUC 0.711 vs. 0.779), especially for infants (AUC 0.618). To ensure pediatric candidates are not unpredictably or negatively impacted by allocation policy changes, we must explicitly account for pediatric-specific decision making in LSAM.
SRTR 维护着肝脏模拟分配模型 (LSAM)，这是一种用于估计肝脏分配政策变化影响的工具。LSAM 的一个组成部分是一个预测接受或拒绝肝脏进行移植的决策的模型。LSAM 隐含地假设这些决策在成人和儿科肝移植 (LT) 候选者中是相同的，这一点以前没有得到验证。我们应用 LSAM 的决策模型来分析 2013 年至 2016 年 SRTR 的报价数据，以确定其在成人（≥18 岁）和儿科（<18 岁）LT 候选者中的效果，并确定儿科亚群——青少年（≥12 至 <18 岁）、儿童（≥2 至 <12 岁）和婴儿（<2 岁）的效果，使用接收者操作特征 (ROC) 曲线下的面积 (AUC)。对于非 1A 状态的候选者，所有儿科亚组的报价接受率都高于成人。对于非 1A 候选者，LSAM 的模型对儿科候选者的表现明显不如成人（AUC 分别为 0.815 和 0.922）；随着年龄的增长，模型的性能下降（AUC 分别为 0.898、0.806、0.783，用于青少年、儿童和婴儿）。对于 1A 状态的候选者，LSAM 对儿科候选者的表现也不如成人（AUC 分别为 0.711 和 0.779），特别是对于婴儿（AUC 为 0.618）。为了确保儿科候选者不会因分配政策的变化而不可预测或受到负面影响，我们必须在 LSAM 中明确考虑儿科特定的决策。
