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 all have some limitations related to model assumptions and clinical interpretation. Therefore, we introduce restricted mean time lost (RMTL) as an alternative that is easy to interpret in a competing risks framework. We propose a hypothetical test and sample size estimator based on the difference in RMTL (RMTLd). The simulation results show that the RMTLd test has robust statistical performance (both type I error and power). Meanwhile, the RMTLd-based sample size can approximately achieve the predefined power level. The results of two 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 when analyzing competing risks data and that the RMTLd even be regarded as the primary outcome when the proportional hazard assumption fails.

翻译：在临床和流行病学研究中,危险比率常常用于比较两组生存数据之间的治疗效果。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(CHHRs)和次分配危险比率(SHRs),但它们都与模型假设和临床解释有关,因此,我们采用有限的平均损失时间(RMTL)作为在相互竞争的风险框架内易于解释的替代方法。我们根据RMTL(RMTLd)的差异提出假设测试和样本大小估计值。模拟结果表明,RMTLd测试具有很强的统计性能(I型错误和功率)。与此同时,基于RMTLd的抽样规模可以大致达到预先确定的功率水平。两个例子分析的结果还验证了RMTLd试验的性能。从临床解释、应用条件和统计性能的角度来看,我们建议,在分析相互竞争的风险数据时,向HR报告RMTLd,即使RMTLd在比例危险假设失败时,也被视为主要结果。