When interested in a time-to-event outcome, competing events that prevent the occurrence of the event of interest may be present. In the presence of competing events, various statistical estimands have been suggested for defining the causal effect of treatment on the event of interest. Depending on the estimand, the competing events are either accommodated or eliminated, resulting in causal effects with different interpretation. The former approach captures the total effect of treatment on the event of interest while the latter approach captures the direct effect of treatment on the event of interest that is not mediated by the competing event. Separable effects have also been defined for settings where the treatment effect can be partitioned into its effect on the event of interest and its effect on the competing event through different causal pathways. We outline various causal effects that may be of interest in the presence of competing events, including total, direct and separable effects, and describe how to obtain estimates using regression standardisation with the Stata command standsurv. Regression standardisation is applied by obtaining the average of individual estimates across all individuals in a study population after fitting a survival model. With standsurv several contrasts of interest can be calculated including differences, ratios and other user-defined functions. Confidence intervals can also be obtained using the delta method. Throughout we use an example analysing a publicly available dataset on prostate cancer to allow the reader to replicate the analysis and further explore the different effects of interest.
翻译:当对时间到活动的结果感兴趣时,可能会出现防止发生利息事件的相互竞争事件。在出现相互竞争的事件时,已经建议了各种统计估计,以确定如何处理对利息事件产生的因果关系。视估计而定,竞争事件要么得到考虑,要么消除,产生因果影响,不同的解释不同。前一种办法反映处理对利息事件产生的总影响,而后一种办法则反映处理对利息事件产生的直接影响,而后者则反映处理对未经竞争事件调解的利息事件产生的直接影响。还确定了处理效应的可分效应,这些环境的处理效应可分为处理效应对利息事件的影响,以及通过不同的因果途径对相互竞争事件的影响。我们概述了对相互竞争事件可能具有的利益的各种因果关系,包括整体、直接和可分解的影响,并说明如何利用与Stata指令的回归标准化来获得估计数。在符合生存模式后,通过获得所有研究人群的个人个人估计的平均数,从而适用倒退的标准化效果。在对用户对利息事件的影响和通过不同的因果关系进行若干对比之后,我们还可以使用不同的用户比率来分析。