Institute of Medical Biometry, University Medical Center Ruprecht-Karls University Heidelberg, Heidelberg, Germany.
Institute of Biometry and Clinical Epidemiology, Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Pharm Stat. 2022 Nov;21(6):1121-1137. doi: 10.1002/pst.2228. Epub 2022 May 23.
Adaptive planning of clinical trials allows modifying the entire trial design at any time point mid-course. In this paper, we consider the case when a trial-external update of the planning assumptions during the ongoing trial makes an unforeseen design adaptation necessary. We take up the idea to construct adaptive designs with defined features by solving an optimization problem and apply it to the situation of unplanned design reassessment. By using the conditional error principle, we present an approach on how to optimally modify the trial design at an unplanned interim analysis while at the same time strictly protecting the type I error rate. This linking of optimal design planning and the conditional error principle allows sound reactions to unforeseen events that make a design reassessment necessary.
临床试验的适应性计划允许在任何时间点中途修改整个试验设计。在本文中，我们考虑了在进行中的试验期间对计划假设进行试验外部更新的情况，这使得需要进行意外的设计调整。我们通过解决优化问题来构建具有明确定义特征的自适应设计，并将其应用于未计划的设计重新评估的情况。通过使用条件误差原则，我们提出了一种在未计划的中期分析时如何最优地修改试验设计的方法，同时严格保护Ⅰ型错误率。这种将最优设计规划与条件误差原则联系起来的方法，允许对需要进行设计重新评估的意外事件做出合理的反应。
