Semiparametric Weighted Spline Regression (SWSR) in Confirmatory Clinical Trials with Time-Varying Placebo Effects
针对确认性III期临床试验中随时间变化的安慰剂效应，提出半参数加权样条回归方法，通过B样条非参数估计治疗效应，控制I类错误率并提高检验功效，适用于非适应性设计。
In confirmatory Phase 3 clinical trials with recruitment over the years, the underlying placebo effect may follow an unknown temporal trend. Taking a clinical trial on Hidradenitis Suppurativa (HS) as an example, fluctuations or variabilities are common in HS-related endpoints, mainly due to the natural disease characteristics, variations of evaluation from different physicians, and standard of care evolvement. The adjustment of time-varying placebo effects receives some attention in adaptive clinical trials and platform trials, but is usually ignored in traditional non-adaptive designs. However, under the impact of such a time drift, some existing methods may not simultaneously control the Type I error rate and achieve satisfactory power. In this article, we propose SWSR (Semiparametric Weighted Spline Regression) to estimate the treatment effect with B-splines to accommodate the time-varying placebo effects nonparametrically. Our method aims to achieve the following three objectives: a proper Type I error rate control under varying settings, an overall high power to detect a potential treatment effect, and robustness to unknown time-varying placebo effects. Simulation studies and a case study provide supporting evidence. Those three key features make SWSR an appealing option to be pre-specified for practical confirmatory clinical trials. Supplemental materials, including the R code, additional simulation results and theoretical discussion, are available online.