背景:终末期肝病模型(MELD)优先考虑欧洲移植肝移植候选人,基于INR的90天等待名单生存风险评分,肌酐和胆红素。几项研究修改了原始的MELD分数,UNOS-MELD,通过对候补名单登记的90天候补名单死亡率进行建模,利用移植候选数据,在除名或移植时审查患者。这种方法忽略了注册后报告的生物标志物,而忽略了通过移植和除名进行的信息性审查。
方法:我们研究了从日历时间横截面的修订以及使用逆概率审查权重(IPCW)对信息审查的校正如何影响MELD修订。为此,我们在2007年至2019年期间对欧洲移植等待名单上的慢性肝硬化患者(n=13,274)进行了UNOS-MELD修订,Cox模型以90天生存期为终点(a)从登记开始,(b)从每周绘制的日历-时间横断面开始.我们将IPCW横截面的修订分数称为DynReMELD,并将DynReMELD与UNOS-MELD和ReMELD进行比较,先前对欧洲移植的UNOS-MELD进行了修订,在地理验证中。
结果:从日历-时间横截面修改MELD导致MELD系数显著不同。IPCW将90天候补名单绝对死亡风险的估计值提高了约10个百分点。DynReMELD与UNOS-MELD(deltac-index:0.0040,p<0.001)和ReMELD(deltac-index:0.0015,p<0.01)相比,提高了辨别力,与向MELD中添加额外的生物标志物相比,其幅度差异相当(Δc指数:±0.0030)。
结论:通过移植/除名纠正选择偏倚并不能改善对修订后的MELD分数的歧视,但大大增加了估计的90天绝对死亡风险.从横截面的修订更有效地使用等待列表数据,与仅根据上市时提供的信息修订MELD相比,歧视有所改善。
BACKGROUND: Eurotransplant liver transplant candidates are prioritized by Model for End-stage Liver Disease (MELD), a 90-day waitlist survival risk score based on the INR, creatinine and bilirubin. Several studies revised the original MELD score, UNOS-MELD, with transplant candidate data by modelling 90-day waitlist mortality from waitlist registration, censoring patients at delisting or transplantation. This approach ignores biomarkers reported after registration, and ignores informative censoring by transplantation and delisting.
METHODS: We study how MELD revision is affected by revision from calendar-time cross-sections and correction for informative censoring with inverse probability censoring weighting (IPCW). For this, we revised UNOS-MELD on patients with chronic liver cirrhosis on the
Eurotransplant waitlist between 2007 and 2019 (n = 13,274) with Cox models with as endpoints 90-day survival (a) from registration and (b) from weekly drawn calendar-time cross-sections. We refer to the revised score from cross-section with IPCW as DynReMELD, and compare DynReMELD to UNOS-MELD and ReMELD, a prior revision of UNOS-MELD for
Eurotransplant, in geographical validation.
RESULTS: Revising MELD from calendar-time cross-sections leads to significantly different MELD coefficients. IPCW increases estimates of absolute 90-day waitlist mortality risks by approximately 10 percentage points. DynReMELD has improved discrimination over UNOS-MELD (delta c-index: 0.0040, p < 0.001) and ReMELD (delta c-index: 0.0015, p < 0.01), with differences comparable in magnitude to the addition of an extra biomarker to MELD (delta c-index: ± 0.0030).
CONCLUSIONS: Correcting for selection bias by transplantation/delisting does not improve discrimination of revised MELD scores, but substantially increases estimated absolute 90-day mortality risks. Revision from cross-section uses waitlist data more efficiently, and improves discrimination compared to revision of MELD exclusively based on information available at listing.