In time-to-event settings, the presence of competing events complicates the definition of causal effects. Here we propose the new separable effects to study the causal effect of a treatment on an event of interest. The separable direct effect is the treatment effect on the event of interest not mediated by its effect on the competing event. The separable indirect effect is the treatment effect on the event of interest only through its effect on the competing event. Similar to Robins and Richardson’s extended graphical approach for mediation analysis, the separable effects can only be identified under the assumption that the treatment can be decomposed into two distinct components that exert their effects through distinct causal pathways. Unlike existing definitions of causal effects in the presence of competing events, our estimands do not require cross-world contrasts or hypothetical interventions to prevent death. As an illustration, we apply our approach to a randomized clinical trial on estrogen therapy in individuals with prostate cancer.

在事件发生时间中，竞争事件的存在使因果效应的定义变得复杂。在这里，我们提出了新的可分离效应，以研究治疗对感兴趣事件的因果效应。可分离的直接作用是对感兴趣事件的治疗作用，而不是由其对竞争事件的作用所介导。可分离的间接效应是仅通过其对竞争事件的影响而对关注事件的治疗作用。与Robins和Richardson的扩展图形方法进行的调解分析相似，只有在假设治疗可以分解为两个通过不同因果途径发挥作用的不同成分的前提下，才能确定可分离的作用。与存在竞争事件时的因果效应的现有定义不同，我们的估计不需要跨世界的对比或假设性干预来防止死亡。作为说明，我们将我们的方法应用于对前列腺癌患者进行雌激素治疗的随机临床试验。