🤖 AI Summary
本文探讨了妊娠期间时间-事件分析中使用目标试验框架定义因果估计量的问题，通过对比两种时间尺度（孕龄和研究进入后的时间）来解决这一挑战。
📝 Abstract
The target trial framework is increasingly used to define the causal estimand for an observational analysis. However, designing time-to-event analyses that align with the causal estimand is challenging in pregnancy because the timescale on which outcomes are often defined, "gestational age", differs from the timescale on which outcomes are measured, "time since study entry". We argue that neither timescale is "best" but that each aligns with a different estimand. In this article, we use the target trial framework to define the causal estimands corresponding to each timescale. We consider a (hypothetical) target trial comparing randomization to 17-alpha hydroxyprogesterone caproate (17-OHPC) versus placebo between 16-20 weeks of gestation to prevent delivery before 37 weeks' gestation, whether by miscarriage, stillbirth, or live birth. We define the estimand of time-to-event analyses on the "time since study entry" timescale as the effect of randomization to 17-OHPC versus placebo between 16-20 weeks of gestation on delivery before 37 weeks'. In contrast, the causal estimand of time-to-event analyses using the "gestational age" timescale corresponds to the effect had, counter to fact, all participants been randomized at one gestational age (e.g., 16 weeks). We review specific challenges to estimation and possible solutions for each timescale.