对于同行评审文献中的汇总级流行病学数据的定量偏差分析方法:系统性审查
Xiaoting Shi1, Ziang Liu2, Mingfeng Zhang3
1Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA.
Journal of clinical epidemiology
|August 28, 2024
概括
这次审查确定了57种针对流行病学数据的定量偏差分析 (QBA) 方法. 这些方法有助于评估观察性研究和元分析中的系统错误,帮助研究人员了解潜在的偏见.
科学领域:
- 流行病学 流行病学
- 生物统计学 生物统计学
- 健康研究方法 卫生研究方法
背景情况:
- 定量偏差分析 (QBA) 方法对于评估观察性研究中的系统错误至关重要.
- 评估偏差对研究结果的影响对于可靠的科学结论至关重要.
- 需要对可用的QBA方法进行全面的了解,以了解总结级数据.
研究的目的:
- 系统地审查和描述总结级数据的定量偏差分析 (QBA) 方法.
- 为了确定现有的QBA方法所解决的偏差范围.
- 总结已发表的QBA方法的适用性和特点.
主要方法:
- 在主要数据库 (MEDLINE,Embase,Scopus,Web of Science) 进行系统的文献搜索.
- 包括英语文章描述QBA方法的总结级数据.
- 提取和记录关键特征:研究设计,解决偏差,偏差参数和软件可用性.
主要成果:
- 从53篇文章中确定了57种QBA方法,主要用于观察性研究 (93%).
- 大多数方法解决了未测量的混 (51%),其次是错误分类 (33%) 和选择偏差 (11%).
- 大多数 (67%) 产生了偏差调整的估计,而39%提供了可访问的代码或工具.
结论:
- 文献中有一套57种QBA方法用于总结层次的流行病学数据.
- 这一系统性审查为寻求适当的QBA方法的研究人员提供了宝贵的资源.
- 未来的研究可以利用这个摘要来选择和应用合适的偏差分析技术.
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