Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA.
Liver Transpl. 2012 Dec;18(12):1456-63. doi: 10.1002/lt.23548.
Under an ideal implementation of Model for End-Stage Liver Disease (MELD)-based liver allocation, the only factors that would predict deceased donor liver transplantation (DDLT) rates would be the MELD score, blood type, and donation service area (DSA). We aimed to determine whether additional factors are associated with DDLT rates in actual practice. Data from the Scientific Registry of Transplant Recipients for all adult candidates wait-listed between March 1, 2002 and December 31, 2008 (n = 57,503) were analyzed. Status 1 candidates were excluded. Cox regression was used to model covariate-adjusted DDLT rates, which were stratified by the DSA, blood type, liver-intestine policy, and allocation MELD score. Inactive time on the wait list was not modeled, so the computed DDLT hazard ratios (HRs) were interpreted as active wait-list candidates. Many factors, including the candidate's age, sex, diagnosis, hospitalization status, and height, prior DDLT, and combined listing for liver-kidney or liver-intestine transplantation, were significantly associated with DDLT rates. Factors associated with significantly lower covariate-adjusted DDLT rates were a higher serum creatinine level (HR = 0.92, P < 0.001), a higher bilirubin level (HR = 0.99, P = 0.001), and the receipt of dialysis (HR = 0.83, P < 0.001). Mild ascites (HR = 1.15, P < 0.001) and hepatic encephalopathy (grade 1 or 2, HR = 1.05, P = 0.02; grade 3 or 4, HR = 1.10, P = 0.01) were associated with significantly higher adjusted DDLT rates. In conclusion, adjusted DDLT rates for actively listed candidates are affected by many factors aside from those integral to the allocation system; these factors include the components of the MELD score itself as well as candidate factors that were considered but were deliberately omitted from the MELD score in order to keep it objective. These results raise the question whether additional candidate characteristics should be explicitly incorporated into the prioritization of wait-list candidates because such factors are already systematically affecting DDLT rates under the current allocation system.
在理想的终末期肝病模型(MELD)肝分配实施下,唯一能预测已故供体肝移植(DDLT)率的因素将是 MELD 评分、血型和供体服务区域(DSA)。我们旨在确定在实际实践中是否还有其他因素与 DDLT 率相关。分析了 2002 年 3 月 1 日至 2008 年 12 月 31 日期间等待名单上所有成年候选者的科学移植受者登记处的数据(n=57503)。排除状态 1 候选者。使用 Cox 回归模型来构建调整后的 DDLT 率,这些率根据 DSA、血型、肝肠政策和分配 MELD 评分进行分层。等待名单上的非活动时间未建模,因此计算的 DDLT 危险比(HR)被解释为活跃等待名单候选者。许多因素,包括候选者的年龄、性别、诊断、住院状态、身高、先前的 DDLT 以及肝-肾或肝-肠联合移植的登记,与 DDLT 率显著相关。与调整后 DDLT 率显著降低相关的因素包括血清肌酐水平升高(HR=0.92,P<0.001)、胆红素水平升高(HR=0.99,P=0.001)和接受透析(HR=0.83,P<0.001)。轻度腹水(HR=1.15,P<0.001)和肝性脑病(1 或 2 级,HR=1.05,P=0.02;3 或 4 级,HR=1.10,P=0.01)与调整后 DDLT 率显著升高相关。总之,积极等待的候选者的调整后 DDLT 率受到除分配系统固有因素以外的许多因素的影响;这些因素包括 MELD 评分本身的组成部分以及候选者因素,这些因素被认为是客观的,但为了保持其客观性而故意从 MELD 评分中删除。这些结果提出了一个问题,即是否应该明确将额外的候选者特征纳入等待名单候选者的优先排序中,因为在当前分配系统下,这些因素已经在系统地影响 DDLT 率。