In clinical and epidemiological studies, hazard ratios are often applied to compare treatment effects between two groups for survival data. For competing risks data, the corresponding quantities of interest are cause-specific hazard ratios (cHRs) and subdistribution hazard ratios (sHRs). However, they both have some limitations related to model assumptions and clinical interpretation. Therefore, we recommend restricted mean time lost (RMTL) as an alternative that is easy to interpret in a competing risks framework. Based on the difference in restricted mean time lost (RMTLd), we propose a new estimator, hypothetical test and sample size formula. The simulation results show that the estimation of the RMTLd is accurate and that the RMTLd test has robust statistical performance (both type I error and power). The results of three example analyses also verify the performance of the RMTLd test. From the perspectives of clinical interpretation, application conditions and statistical performance, we recommend that the RMTLd be reported with the HR in the analysis of competing risks data and that the RMTLd even be regarded as the primary outcome when the proportional hazard assumption fails. The R code (crRMTL) is publicly available from Github (https://github.com/chenzgz/crRMTL.1). Keywords: survival analysis, competing risks, hazard ratio, restricted mean time lost, sample size, hypothesis test
翻译:在临床和流行病学研究中,危险比率常常用于比较两个类别之间对生存数据的处理效果。关于相互竞争的风险数据,相应的利息数量是特定原因的危险比率(cHRs)和次分配的危险比率(sHRs),但是,两者都有一些与模型假设和临床解释有关的限制限制时间损失(RMTL),因此,我们建议限制平均时间损失(RMTL),作为在相互竞争的风险框架内易于解释的一种替代办法。根据有限平均损失时间(RMTLd)的差异,我们提议一个新的估计标准、假设测试和抽样规模公式。模拟结果显示,RMTLd的估计准确,RMTLd的测试具有强有力的统计性能(第一类错误和权力)。三个实例分析的结果也验证了RMTLd测试的绩效。从临床解释、应用条件和统计业绩的角度,我们建议,在分析相互竞争风险数据时,将RMTLd报告与人力资源一起,在比例危险假设失败时,甚至将RMTLdL作为主要结果。RMT/regrevimeximal的样本样本(rb:RMT/regmgmb/regregmb surb surb surb surb surb surb surb surviewsurbsurbs surbs surviews surbs surdismex surbs surdex surdex sursurviolds surgisals surgs surgs surgisaldsmaldsurgs surds surg surg surg surgs)。