使用对二进制结果的非处理顺序多重推算来处理由处理政策策略处理的间歇事件
Sunita Rehal1, Nicky Best1, Sarah Watts1
1GlaxoSmithKline, London, UK.
Pharmaceutical statistics
|February 7, 2026
概括
估计和框架指导处理间流动事件,有利于治疗政策策略. 对于二进制终点来说,一个简单的检索失效模型是务实的,但需要大量的事件后数据来进行可靠的估计.
科学领域:
- 生物统计学 生物统计学
- 临床试验方法论 临床试验方法论
- 药学研究 药学研究
背景情况:
- 估计框架为临床试验中的间流事件提供了策略.
- 治疗政策策略与治疗意图原则保持一致.
- 处理因患者退出而缺少的数据对于准确估计至关重要.
研究的目的:
- 在治疗政策战略下,探索和比较检索的脱学模型,以估计治疗效应与二进制终点的治疗效应.
- 通过模拟和实践示例来评估这些模型的性能.
- 确定最务实的检索性弃模型,用于处理间流事件,如治疗中止.
主要方法:
- 调查了各种可检索的丢失模型,以归因缺失的间接事件后数据.
- 通过模拟研究,将拟议的模型与简单的归算模型进行比较.
- 应用和评估的模型使用的临床试验3期的数据为类风湿关节炎.
主要成果:
- 一个简单的检索掉队模型与一个间流事件指标被证明是最务实的.
- 该模型的有效性取决于至少有50%的观察到的间歇后事件数据.
- 模型的适用性取决于间隔事件后观察到的数据的可用性.
结论:
- 检索掉队模型提供了一种可行的方法,用于估计二元结果和间流事件的治疗效应.
- 务实选择需要足够的间流事件后观察到的数据来进行可靠的归算.
- 在在临床试验中实施这些模型之前,必须仔细考虑数据的可用性.
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