Am J Epidemiol. 2022 Jan 1;191(1):163-172. doi: 10.1093/aje/kwab235.
In clinical and epidemiologic studies, hazard ratios are often applied to compare treatment effects between 2 groups for survival data. For competing-risks data, the corresponding quantities of interest are cause-specific hazard ratios and subdistribution hazard ratios. However, they both have some limitations related to model assumptions and clinical interpretation. Therefore, we recommend restricted mean time lost (RMTL) as an alternative measure that is easy to interpret in a competing-risks framework. Based on the difference in RMTL (RMTLd), we propose a new estimator, hypothetical test, and sample-size formula. Simulation results show that estimation of the RMTLd is accurate and that the RMTLd test has robust statistical performance (both type I error and statistical power). The results of 3 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 along with the hazard ratio in analyses of competing-risks data and that the RMTLd even be regarded as the primary outcome when the proportional hazards assumption fails.
在临床和流行病学研究中,风险比常用于比较 2 组生存数据的治疗效果。对于竞争风险数据,相应的感兴趣的量是特定原因的风险比和亚分布风险比。然而,它们都存在与模型假设和临床解释相关的一些局限性。因此,我们建议将受限平均时间损失(RMTL)作为替代指标,在竞争风险框架下易于解释。基于 RMTL 的差异(RMTLd),我们提出了一种新的估计量、假设检验和样本量公式。模拟结果表明,RMTLd 的估计是准确的,RMTLd 检验具有稳健的统计性能(均为Ⅰ类错误和统计功效)。3 个实例分析的结果也验证了 RMTLd 检验的性能。从临床解释、应用条件和统计性能的角度来看,我们建议在竞争风险数据的分析中,除了风险比外,还应报告 RMTLd,并且当比例风险假设失效时,RMTLd 甚至可以作为主要结局指标。