In recent placebo-controlled randomized phase 3 oncology trials, evaluation of overall survival with frequent crossover is crucial for regulatory and pricing decisions. The problem is that an intention-to-treat based analysis causes a substantial loss of power to detect causal survival effect without crossover, and performance of existing methods is not satisfactory. In this article, our aims were to evaluate properties of the existing and a proposed Bayesian power prior method where data from an external trial is available. Simulation results suggested that proposed method was the most powerful under typical scenarios where patients with better prognosis are likely to crossover.

在最近的安慰剂对照的随机第3期肿瘤试验中，评估具有频繁交叉反应的总体生存率对于监管和定价决策至关重要。问题在于，基于意向性的分析导致在没有交叉的情况下检测因果生存效应的能力大大降低，并且现有方法的性能并不令人满意。在本文中，我们的目的是评估现有的和拟议的贝叶斯幂先验方法的属性，该方法可以从外部试验获得数据。仿真结果表明，该方法在预后较好的患者可能会交叉的典型情况下是最有效的。