Covariate adjustment is desired by both practitioners and regulators of randomized clinical trials because it improves precision for estimating treatment effects. However, covariate adjustment presents a particular challenge in time-to-event analysis. We propose to apply covariate adjusted pseudovalue regression to estimate between-treatment difference in restricted mean survival times (RMST). Our proposed method incorporates a prognostic covariate to increase precision of treatment effect estimate, maintaining strict type I error control without introducing bias. In addition, the amount of increase in precision can be quantified and taken into account in sample size calculation at the study design stage. Consequently, our proposed method provides the ability to design smaller randomized studies at no expense to statistical power.

翻译：协变量调整是随机临床试验的实践者和监管者都期望的方法，因为它能提高治疗效应估计的精度。然而，在时间-事件分析中，协变量调整面临特殊挑战。我们提出应用协变量调整伪值回归来估计受限平均生存时间（RMST）的治疗组间差异。所提方法纳入预后协变量以提高治疗效应估计的精度，在严格控制I类错误的同时不引入偏差。此外，精度提升的幅度可在研究设计阶段量化并纳入样本量计算。因此，所提方法能够在不牺牲统计功效的前提下设计更小规模的随机研究。