基于信息价值的实用贝叶斯适应性试验设计:以价值为导向的适应性设计
Michael Dymock1,2, Julie A Marsh2,3, Mark Jones4
1School of Population and Global Health, The University of Western Australia, Nedlands, WA, Australia.
概括
本研究介绍了临床试验的价值驱动的适应性设计,使用抽样的预期净收益来指导临时决策. 这种方法通过专注于为决策者收集有价值的数据来提高试验的成本效益.
科学领域:
- 临床试验方法论 临床试验方法论
- 卫生经济学 卫生经济学
- 决策分析 决策分析
背景情况:
- 传统的临床试验设计优先考虑测试假设的错误控制,这对于涉及多个结果和不确定性的复杂决策是不够的.
- 信息价值 (VoI) 指标量化了决策者收集数据的货币价值.
- 将VoI集成到自适应试验设计中一直受到计算挑战的限制.
研究的目的:
- 提出一种新的以价值为导向的适应性试验设计,利用VoI指导试验适应.
- 开发方法来计算预期的净收益采样 (ENBS) 在中间分析,以告知试验的继续.
- 证明拟议设计在各种模型和成本函数中的灵活性和适用性.
主要方法:
- 提出了一个以价值为导向的自适应设计框架,使用VoI分析在中间阶段决定试验进展.
- 详细介绍了计算完美信息的预期净收益和连续分析的ENBS的方法.
- 该方法被设计为模型不可知,不需要对净收益的分配假设.
主要成果:
- 拟议的以价值为导向的自适应设计在一个关于婴儿免疫预防和呼吸道同胞病毒母体疫苗接种的案例研究中实施.
- 该研究展示了使用ENBS来定义中期分析停止规则的实际应用.
- 该方法提供了一个计算可行的方法,将VoI集成到适应性试验设计中.
结论:
- 以价值为导向的自适应设计通过关注信息的价值,使实用性临床试验与决策者的需求保持一致.
- 实施基于VoI的调整可以提高临床试验的成本效益.
- 这种方法有效地指导试验设计,以产生对知情决策至关重要的证据.
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