Group sequential designs in clinical trials allow for interim efficacy and futility monitoring. Adjustment for baseline covariates can increase power and precision of estimated effects. However, inconsistently applying covariate adjustment throughout the stages of a group sequential trial can result in inflation of type I error, biased point estimates, and anti-conservative confidence intervals. We propose methods for performing correct interim monitoring, estimation, and inference in this setting that avoid these issues. We focus on two-arm trials with simple, balanced randomization and continuous outcomes. We study the performance of our boundary, estimation, and inference adjustments in simulation studies. We end with recommendations about the application of covariate adjustment in group sequential designs.

翻译：组序贯设计在临床试验中允许进行中期疗效和无效性监测。对基线协变量进行调整能够提高统计检验效能并提升效应估计的精度。然而，在组序贯试验的各阶段不一致地应用协变量调整会导致I类错误膨胀、点估计有偏以及置信区间过于保守。我们针对该场景提出了正确进行中期监测、参数估计和统计推断的方法，从而避免上述问题。本研究聚焦于采用简单均衡随机化且结局变量为连续型的双臂试验。通过模拟研究评估了边界调整、参数估计和推断调整的性能。最后就协变量调整在组序贯设计中的应用提出了相关建议。