已发表的剂量反应元分析中的统计模型评估不足于最佳:来自对242个数据集的方法审查和再分析的证据
Marimuthu Sappani1, Shofiqul Islam2, Rohan D'Souza3
1Faculty of Health Sciences, Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada.
Journal of clinical epidemiology
|September 21, 2025
概括
剂量反应元分析 (DRMA) 研究往往缺乏严格的统计报告. 具有非固定节点的受限制立方线 (RCS) 模型显示出有希望的结果,但留下一个缺点的分析显示出对单个研究的敏感性.
科学领域:
- 流行病学 流行病学
- 生物统计学 生物统计学
- 临床研究 临床研究
背景情况:
- 剂量反应元分析 (DRMA) 对暴露风险关系至关重要.
- 尽管有软件可用,但DRMA中的统计方法需要彻底评估.
研究的目的:
- 评估DRMA中统计措施的报告质量.
- 使用实证数据比较不同统计模型的性能.
主要方法:
- 对DRMA研究进行系统的文献搜索.
- 适应线性,二次多项式和受限制立方线 (RCS) 模型.
- 通过leave-one-out (LOO) 分析评估了非线性,适用性 (GoF),模型比较和异常影响.
主要成果:
- 分析了146个DRMA研究 (242个数据集);对GoF的报告,模型比较和异常值分析是罕见的.
- 使用非固定节点的RCS模型发现了更多的非线性,并且比替代品更适合.
- LOO分析表明,在排除一项研究后,结论在约50%的案例中发生了变化.
结论:
- 已发表的DRMA研究显示,统计报告没有达到最佳水平.
- 带有非固定节点的RCS比其他模型具有优势.
- 整合临床判断和严格的统计评估,包括LOO,对于可信的元分析结果至关重要.
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