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设计和评估贝叶斯先进的自适应随机临床试验:一本实用指南
Anders Granholm1,2, Aksel Karl Georg Jensen1,2, Theis Lange2
1Department of Intensive Care 4131, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark.
先进的自适应性临床试验提供了效率和更好的参与者分配. 本指南提供了使用贝叶斯方法和适应性策略设计和评估这些试验的实际步骤.
科学领域:
- 生物统计学 生物统计学
- 临床试验设计 临床试验设计
- 统计建模 统计建模
背景情况:
- 先进的自适应性随机临床试验越来越多地被利用,因为它们的灵活性和效率.
- 对于设计和评估这些复杂的试验方法的指导是有限的.
- 适应性策略可以提高效率,确保确的结果,并优化参与者分配.
研究的目的:
- 为规划和评估先进的适应性试验提供全面的实践指南.
- 在贝叶斯统计框架内概述方法论考量.
- 为了促进适应性停止,手臂下降和响应适应性随机化的使用.
主要方法:
- 总结了贝叶斯先进适应性试验的方法考虑.
- 详细说明从规划到评估的整个工作流程.
- 使用统计模拟,并为实际应用提供R包代码 (adaptr).
主要成果:
- 涵盖关键决策,包括干预使用,结果类型,分析时间,分配规则和适应规则.
- 包括现实的例子和模拟代码用于评估.
- 处理性能指标,校准,敏感性分析和报告.
结论:
- 本指南为临床试验人员,方法学家和生物统计学家提供必要的工具.
- 它可以有效设计和评估贝叶斯先进的适应性试验.
- 促进更有效和更道德的临床试验实践.
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