在使用估计和框架的非劣势试验中处理间流动事件和缺失数据:结核病病例研究
Sunita Rehal1, Suzie Cro2, Patrick Pj Phillips3
1GlaxoSmithKline, Middlesex, UK.
Clinical trials (London, England)
|June 6, 2023
概括
本研究提出了在非劣质性临床试验中处理间流事件和缺失数据的原则方法. 拟议的估计框架和多重归算技术为准确的解释提供了统计学上严格的分析.
科学领域:
- 临床试验方法论 临床试验方法论
- 生物统计学 生物统计学
- 药学研究 药学研究
背景情况:
- 国际协调理事会附录E9 (2019) 提供了一个估计和框架,但缺乏对非劣等性试验的指导,特别是关于间接事件和缺失数据的指导.
- 对非劣势性研究的原则分析受到挑战,因为需要定义适当处理间流事件和缺失值的估值.
研究的目的:
- 提出和展示一个框架来定义非劣势临床试验中的估计值,解决间流事件和缺失数据.
- 引入和评估用于估计这些估计值的多种归算方法,包括灵敏度分析.
主要方法:
- 一个用结核病临床试验来定义初级和附加估计的非劣势的案例研究.
- 应用"双重"完全有条件的规范多重归算算法和基于引用的多重归算对二进制结果的应用.
- 将拟议方法的结果与原始研究的每项方案和治疗意图分析进行比较.
主要成果:
- 拟议的估计和框架,利用假设和治疗政策策略,与ICH E9附录相一致.
- 应用了多种归算方法,包括"双重"和基于参考的方法与灵敏度分析,以估计定义的估计值.
- 使用拟议方法的分析与原始研究一致,表明未能证明非劣等性.
结论:
- 精心构建的估计和适当的估计方法为非劣势试验分析提供了更有原则和更严格的统计方法.
- 拟议的方法提升了通过利用所有可用的信息和解决间流动事件和缺失数据来准确解释估计值.
- 该研究强调了对于复杂的临床试验设计,如非劣势研究,强大的统计框架的重要性.
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