PDF(Pubmed)
Abstract：
Seamless phase 2/3 design has become increasingly popular in clinical trials with a single endpoint. Trials that define success based on the achievement of all co-primary endpoints (CPEs) encounter the challenge of inflated type 2 error rates, often leading to an overly large sample size. To tackle this challenge, we introduced a seamless phase 2/3 design strategy that employs Bayesian predictive power (BPP) for futility monitoring and sample size re-estimation at interim analysis. The correlations among multiple CPEs are incorporated using a Dirichlet-multinomial distribution. An alternative approach based on conditional power (CP) was also discussed for comparison. A seamless phase 2/3 vaccine trial employing four binary endpoints under the non-inferior hypothesis serves as an example. Our results spotlight that, in scenarios with relatively small phase 2 sample sizes (e.g., 50 or 100 subjects), the BPP approach either outperforms or matches the CP approach in terms of overall power. Particularly, with n1 = 50 and ρ = 0, BPP showcases an overall power advantage over CP by as much as 8.54%. Furthermore, when the phase 2 stage enrolled more subjects (e.g., 150 or 200), especially with a phase 2 sample size of 200 and ρ = 0, the BPP approach evidences a peak difference of 5.76% in early stop probability over the CP approach, emphasizing its better efficiency in terminating futile trials. It\'s noteworthy that both BPP and CP methodologies maintained type 1 error rates under 2.5%. In conclusion, the integration of the Dirichlet-Multinominal model with the BPP approach offers improvement in certain scenarios over the CP approach for seamless phase 2/3 trials with multiple CPEs.
摘要：
无缝2/3阶段设计在单一终点的临床试验中越来越受欢迎。根据所有共同主要终点（CPE）的成就定义成功的试验遇到了膨胀的2型错误率的挑战，通常导致样本量过大。为了应对这一挑战，我们引入了无缝2/3阶段设计策略,该策略在中期分析时采用贝叶斯预测能力(BPP)进行无用性监测和样本量重新估计.使用狄利克雷-多项分布合并多个CPE之间的相关性。为了进行比较，还讨论了一种基于条件功率（CP）的替代方法。在非劣质假设下采用四个二元终点的无缝2/3期疫苗试验作为示例。我们的结果突出表明，在第二阶段样本量相对较小的情况下(例如，50或100名受试者），BPP方法在整体功率方面优于或匹配CP方法。特别是,在n1=50和ρ=0的情况下，BPP展示了比CP高8.54%的整体功率优势。此外，当第二阶段登记了更多的受试者(例如，150或200），特别是在第2阶段样本量为200且ρ=0的情况下，BPP方法证明与CP方法相比，早期停止概率的峰值差异为5.76%，强调其在终止徒劳试验方面的更好效率。值得注意的是，BPP和CP方法都将类型1错误率保持在2.5%以下。总之,Dirichlet-Multinomal模型与BPP方法的集成在某些情况下,对于具有多个CPE的无缝2/3阶段试验,与CP方法相比,提供了改进.
