Abstract In this article, we propose a hybrid-Bayesian frequentist approach using a Bayesian sequential prediction of the index of satisfaction. For interim analysis that addresses prediction hypothesis, such as futility monitoring with delayed outcomes, the prediction of satisfaction properly accounts for the amount of data remaining to be observed in a clinical trial and has the flexibility to incorporate additional information via auxiliary variables. The prediction of satisfaction design guarantees the type I error rate and does not require intensive computation or comprehensive simulation. The design is retrospectively applied to a lung cancer clinical trial.

中文翻译：

---

用于监测多阶段临床试验的混合贝叶斯频率论预测设计

摘要 在本文中，我们提出了一种混合贝叶斯频率论方法，该方法使用满意度指数的贝叶斯顺序预测。对于解决预测假设的中期分析，例如对延迟结果的无效监测，满意度预测正确地考虑了临床试验中剩余的数据量，并且可以灵活地通过辅助变量合并其他信息。满意度设计的预测保证了第一类错误率，不需要密集的计算或综合模拟。该设计回顾性应用于肺癌临床试验。