Trials of antiseizure medications involve static group assignments for treatments with pre-specified durations. We propose a response-adaptive crossover design using basic statistical assumptions regarding both seizure count and duration of treatment to determine when a participant can change group assignment. We modelled seizure frequency as a Poisson process and estimated the likelihood that seizure frequency had decreased by 50% compares to baseline using both a Bayesian and maximum likelihood approach. We simulated trials to estimate the influence of this design on statistical power and observation duration with each treatment. For patients with 9 baseline seizures in 4 weeks who had no change in seizure frequency, the simulation identified non-response in a median of 16 days. The response-adaptive crossover design resulted in a modest increase in statistical power to identify an effective treatment while maximizing the time in a group producing a response. Only 8% of participants remained in the placebo group for all 90 days of the simulated trials. These example theoretical results can provide quantitative guidance regarding objective criteria to determine non-response in real-time during a controlled clinical trial without revealing the assigned treatment. Implementing a response-adaptive crossover design may both improve statistical power while minimizing participant risk.

中文翻译：

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癫痫的个人水平响应自适应交叉试验设计：结构和模拟

抗癫痫药物的试验涉及静态小组分配，用于预先指定的疗程。我们提出了一种针对癫痫发作次数和治疗持续时间的基本统计假设，来制定响应适应性交叉设计，以确定参与者何时可以更改组分配。我们将癫痫发作频率建模为泊松过程，并使用贝叶斯方法和最大似然方法估计癫痫发作频率与基线相比降低了50％的可能性。我们模拟试验来估计该设计对每种治疗方法的统计功效和观察时间的影响。对于4周内发生9次基线癫痫发作且癫痫发作频率无变化的患者，模拟结果显示在16天的中位无反应。响应自适应的交叉设计导致统计能力的适度增加，以识别有效的治疗方法，同时最大化产生响应的组中的时间。在整个模拟试验的90天中，只有8％的参与者保留在安慰剂组中。这些示例性理论结果可提供有关客观标准的定量指导，以在受控临床试验期间实时确定无反应，而无需透露指定的治疗方法。实施响应自适应交叉设计既可以提高统计能力，又可以最大程度地降低参与者风险。这些示例性理论结果可提供有关客观标准的定量指导，以在受控临床试验期间实时确定无反应，而无需透露指定的治疗方法。实施响应自适应交叉设计既可以提高统计能力，又可以最大程度地降低参与者风险。这些示例性理论结果可提供有关客观标准的定量指导，以在受控临床试验期间实时确定无反应，而无需透露指定的治疗方法。实施响应自适应交叉设计既可以提高统计能力，又可以最大程度地降低参与者风险。