We discuss generalizability analyses under a partially nested trial design, where part of the trial is nested within a cohort of trial-eligible individuals, while the rest of the trial is not nested. This design arises, for example, when only some centers participating in a trial are able to collect data on non-randomized individuals, or when data on non-randomized individuals cannot be collected for the full duration of the trial. Our work is motivated by the Necrotizing Enterocolitis Surgery Trial (NEST) that compared initial laparotomy versus peritoneal drain for infants with necrotizing enterocolitis or spontaneous intestinal perforation. During the first phase of the study, data were collected from randomized individuals as well as consenting non-randomized individuals; during the second phase of the study, however, data were only collected from randomized individuals, resulting in a partially nested trial design. We propose methods for generalizability analyses with partially nested trial designs. We describe identification conditions and propose estimators for causal estimands in the target population of all trial-eligible individuals, both randomized and non-randomized, in the part of the data where the trial is nested, while using trial information spanning both parts. We evaluate the estimators in a simulation study.

翻译：我们讨论了部分嵌套试验设计下的一般性分析方法。在该设计中，试验的一部分嵌套于符合试验条件的人群队列中，而其余部分未嵌套。例如，当仅有部分参与试验的中心能够收集非随机化个体的数据，或无法在整个试验期间持续收集非随机化个体数据时，即会出现此类设计。本研究受坏死性小肠结肠炎手术试验（NEST）的启发，该试验比较了初始剖腹手术与腹腔引流术在坏死性小肠结肠炎或自发性肠穿孔婴儿中的疗效。研究第一阶段同时收集了随机化个体及知情同意的非随机化个体的数据；但第二阶段仅收集随机化个体的数据，从而形成了部分嵌套试验设计。我们针对部分嵌套试验设计提出了一般性分析方法，描述了识别条件，并提出了针对目标人群（所有符合试验条件的个体，包括随机化与非随机化个体）中因果估计量的估计方法——该方法利用试验嵌套部分的既有数据，同时整合跨越两阶段的试验信息。我们通过模拟研究对估计量进行了评估。