Platform trials allow treatment arms to enter and exit over time while maintaining a shared control arm, yielding concurrent and non-concurrent controls (NCC). Pooling NCC is often motivated as a strategy to improve statistical efficiency, but it is unclear which estimand is targeted, what assumptions justify identification and estimation, and when precision gains are achievable; these questions are further complicated by time-to-event/survival data. Motivated by the Adaptive COVID-19 Treatment Trial (ACTT) platform trial with time to recovery as the primary endpoint, we develop an estimand-first causal survival framework targeting the treatment-specific counterfactual survival curve in the concurrent population and the corresponding functionals including the concurrent restricted mean survival time (RMST). We give nonparametric identification results and formalize conditions that justify pooling using NCC. We study covariate-adjusted outcome-regression (OR) and doubly robust (DR) estimators for the concurrent RMST, comparing concurrent-only versions to pooled-control versions. Pooling improves precision for OR estimators only when the pooling assumption holds and parametric hazard models are correctly specified; otherwise, pooling can induce bias. Moreover, in certain settings, pooling NCC yields no efficiency gain for the DR estimator. Overall, the most robust route to improve precision is to target concurrent causal survival estimands and use a covariate-adjusted DR estimation that uses only concurrent controls. An ACTT application corroborates these results.

翻译：平台试验允许治疗臂随时间进入和退出，同时保持共享的对照臂，从而产生并发和非并发对照（NCC）。合并NCC通常被视为提高统计效率的策略，但尚不清楚其针对何种估计目标、何种假设能够证明识别与估计的合理性，以及何时能够实现精度提升；这些问题因时间-事件/生存数据而进一步复杂化。基于以康复时间为主要终点的适应性COVID-19治疗试验（ACTT）平台试验，我们建立了一个以估计目标为先导的因果生存分析框架，该框架针对并发人群中治疗特异性反事实生存曲线及相应的泛函，包括并发限制平均生存时间（RMST）。我们给出了非参数识别结果，并形式化了证明使用NCC进行合并合理性的条件。我们研究了针对并发RMST的协变量调整结果回归（OR）估计量与双重稳健（DR）估计量，比较了仅使用并发对照的版本与合并对照的版本。仅当合并假设成立且参数风险模型被正确设定时，合并才能提高OR估计量的精度；否则，合并可能引入偏倚。此外，在某些情况下，合并NCC对DR估计量不会带来效率提升。总体而言，提高精度的最稳健途径是：以并发因果生存估计量为目标，并使用仅基于并发对照的协变量调整DR估计方法。一项ACTT应用验证了这些结果。