在元分析中使用决策值与两个新指数对不一致性的定量评估
Bernardo Sousa-Pinto1, Ignacio Neumann2, Rafael José Vieira1
1Faculty of Medicine, MEDCIDS - Department of Community Medicine, Information and Health Decision Sciences, University of Porto, Porto, Portugal; CINTESIS@RISE - Health Research Network, Faculty of Medicine, MEDCIDS, University of Porto, Porto, Portugal.
新的定量指标,决策不一致性 (DI) 和跨研究不一致性 (ASI) 指数,解决了评估证据综合不一致性的局限性,特别是与决策值 (DTs) 的局限性. 这些工具有助于更强大的定量不一致性评估.
科学领域:
- 生物统计学 生物统计学
- 卫生研究方法论 卫生研究方法论
- 证据综合 证据综合
背景情况:
- 在证据综合中,传统的不一致性评估 (视觉检查,I2,Q统计) 存在局限性,只有少数研究或精确的估计.
- 在GRADE决策证据 (EtD) 等框架中,越来越多地使用决策门 (DTs),需要在这些门周围固定不一致性措施.
研究的目的:
- 开发新的定量措施来评估证据综合中的不一致性,特别适用于与决策值 (DTs) 的使用.
- 引入决策不一致性 (DI) 和跨研究不一致性 (ASI) 指数作为不一致性评估的定量工具.
主要方法:
- 开发了决策不一致性 (DI) 和跨研究不一致性 (ASI) 指数,这些指数基于DT定义的类别中效果大小 (ES) 的后面样本的分布.
- 索引是在贝叶斯框架内开发的,随后扩展为频率应用.
- 创建了一个R包 (metainc) 和一个网络工具,以方便DI和ASI的计算,包括敏感性分析.
主要成果:
- DI指数量化了解释类别的整体不一致性,而ASI指数则衡量了与这些类别相对的研究水平差异.
- 重要不一致的建议值:DI ≥50%和ASI ≥25%.
- 有R包和Web工具可用于支持这些索引的实际应用.
结论:
- DI和ASI指数为评估证据综合中的不一致性提供了有价值的定量方法.
- 这些措施尤其重要,因为数据技术在证据综合和健康决策中的重要性越来越大.
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