分析试验失败预测因素的方法:范围审查和元流行病学研究
Aleksa Jovanovic1, Stojan Gavric1, Fabio Dennstädt2
1Wemedoo AG, Sumpfstrasse 24, Steinhausen, 6312, Switzerland.
BMC medical research methodology
|January 17, 2026
概括
方法的变化显著影响临床试验失败率. 标准化定义和计算方法对于准确预测试验成功或失败至关重要.
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
- 在医疗保健中的数据科学.
背景情况:
- 许多研究调查了临床试验失败预测因素,但缺乏对其方法和发现的全面审查.
- 这项研究解决了对用于分析临床试验失败预测因子的方法进行系统概述的需要.
研究的目的:
- 对分析临床试验失败预测因素的研究进行范围审查.
- 探索这些研究的方法特点和发现.
- 确定影响报告临床试验失败比例的因素.
主要方法:
- 系统地搜索欧维德的Medline和Embase数据库中的文献.
- 包括使用频率统计或机器学习 (ML) 来评估试验失败预测因素的研究.
- 应用通用线性模型 (GLM) 来评估方法因素对失败比例的影响.
主要成果:
- 从17961个记录中包括了81项研究;大多数使用的是clinicaltrials.gov数据和frequentist统计数据.
- 方法因素显著影响了报告的故障比例 (27.5%的偏差减少).
- 包括正在进行的试验在失败计算中降低了失败的几率 (OR=0.44,95% CI:0.29-0.67).
结论:
- 方法变化对报告的临床试验失败率有很大影响,突出了对标准化定义和计算方法的需求.
- 机器学习 (ML) 方法正在扩大,这表明试验失败预测中的潜在范式转变.
- 标准化建议包括将终止/撤回的研究归类为失败的,完成的研究归类为非失败的.
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