Sequential nested trial (SNT) emulation is a powerful approach for maximizing precision and avoiding time-related biases. However, there exists little discussion about the implied causal estimands in comparison to a real-world single point trial. We used Monte Carlo simulation to compare treatment effect estimates from an SNT emulation that re-indexed patients annually and a SNT emulation with a treatment decision design to the estimates from a single point trial. We generated 5,000 cohorts of 5,000 people with 3 years of follow-up. For the single point trial, patients were randomized to initiate or not initiate treatment at Visit 1. For the SNT emulations, simulated patients could contribute up to two index dates. When disease severity did not modify the treatment effect, both SNT approaches returned treatment effect estimates identical to the single point trial. In the presence of treatment effect modification by disease severity, both SNT approaches returned treatment effect estimates that diverged from the single point trial even after confounding-adjustment. These findings underscore the difficulties of interpreting causal estimands from a SNT emulation: the target population does not correspond to a single time point trial. Such implications are important for communicating study results for evidence-based decision-making.

翻译：序贯嵌套试验（SNT）模拟是一种最大化精确度并避免时间相关偏倚的有效方法。然而，与真实世界单点试验相比，其隐含的因果估计量尚未得到充分讨论。我们采用蒙特卡洛模拟方法，比较了每年重新索引患者的SNT模拟、采用治疗决策设计的SNT模拟与单点试验的治疗效果估计值。我们生成了5,000个队列，每个队列包含5,000名受试者，随访时间为3年。在单点试验中，受试者在首次访视时被随机分配至启动治疗组或不启动治疗组。在SNT模拟中，模拟受试者最多可贡献两个索引日期。当疾病严重程度不改变治疗效果时，两种SNT方法得到的治疗效果估计值与单点试验完全一致。当疾病严重程度存在治疗效果修饰作用时，即使经过混杂因素调整，两种SNT方法得到的治疗效果估计值仍与单点试验存在差异。这些发现凸显了阐释SNT模拟因果估计量的困难：其目标人群并不对应于单一时间点试验。这一结论对于基于证据的决策过程中研究结果的解读具有重要意义。