应用可运输性和通用性分析的系统审查:景观分析
Quang Vuong1, Rebecca K Metcalfe2, Albee Ling3
1Core Clinical Sciences, 509-2525 Willow Street, Vancouver, BC V5Z 3N8, Canada.
Annals of epidemiology
|March 10, 2025
概括
可转移性和可概括性分析通过评估外部有效性来增强因果推断. 这种景观分析揭示了它们的多样化的应用,常见的方法,以及需要标准化的报告来提高证据的相关性和试验设计.
科学领域:
- 因果推理的原因推理.
- 生物统计学 生物统计学
- 医疗服务研究 医疗服务研究
背景情况:
- 可转移性和可概括性分析是新的因果推理方法.
- 评估外部有效性对于将研究成果应用于新环境至关重要.
- 目前在实践中的应用和方法尚不清楚.
研究的目的:
- 描述应用可运输性和可通用性分析的现状.
- 确定共同的方法和应用领域.
- 评估报告质量并确定需要改进的领域.
主要方法:
- 在PubMed,CINAHL和Embase的系统文献搜索.
- 补充了手动搜索来识别相关出版物.
- 分析了68个出版物,83个源-目标数据集对和99个不同的分析.
主要成果:
- 大多数数据集来自美国.
- 常见的应用包括将RCT结果传输到观察性研究或其他RCT.
- 方法经常使用权重和个体级患者数据.
- 非标准应用包括识别效果调整器和校准测量.
结论:
- 可转移性分析通过提高证据的相关性来支持决策.
- 它通过识别效果修饰器和校准测量来增强试验设计.
- 分析和报告的标准化是必要的,以提高透明度和采用.
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