Bayesian optimal design for phase II screening trials
Bayesian optimal design for phase II screening trials
复制标题
DOI：
10.1111/j.1541-0420.2007.00951.x
复制
发表时间：
2008-09-01
期刊：
影响因子：
1.9
通讯作者：
Mueller, Peter
中科院分区：
文献类型：
--
作者：
Ding, Meichun;Rosner, Gary L.;Mueller, Peter
文献中大多数II期筛选设计一次只考虑一种治疗方法。每项研究都是单独考虑的。我们建议对第二阶段筛选过程采用更系统的决策方法。顺序设计可以提高效率并更好地了解治疗方法。该方法结合了贝叶斯层次模型，允许以正式的方式组合多个相关研究的信息，并通过借鉴其他处理方法的优势来改进小数据集的估计。该设计包含一个效用函数，包括采样成本和可能的未来收益。计算机模拟表明，该方法有很高的概率放弃低成功率的治疗，并将高成功率的治疗转移到III期试验。
Most phase II screening designs available in the literature consider one treatment at a time. Each study is considered in isolation. We propose a more systematic decision-making approach to the phase II screening process. The sequential design allows for more efficiency and greater learning about treatments. The approach incorporates a Bayesian hierarchical model that allows combining information across several related studies in a formal way and improves estimation in small data sets by borrowing strength from other treatments. The design incorporates a utility function that includes sampling costs and possible future payoff. Computer simulations show that this method has high probability of discarding treatments with low success rates and moving treatments with high success rates to phase III trial.