目的:定量偏倚分析(QBA)方法评估系统误差引起的偏倚对观察性研究结果的影响。本系统综述旨在总结同行评议文献中发表的摘要水平数据的定量偏倚分析(QBA)方法的范围和特征。
方法:我们搜索了MEDLINE,Embase,Scopus,和WebofScience中描述QBA方法的英文文章。对于每种QBA方法,我们记录了关键特征,包括适用的研究设计,偏置(ES);偏置参数,和公开可用的软件。研究协议已在开放科学框架(https://osf.io/ue6vm/)上预先注册。
结果:我们的搜索确定了10,249条记录,其中53篇文章描述了总结水平数据的57种QBA方法。在57种QBA方法中,53(93%)明确设计用于观察性研究,和4(7%)的荟萃分析。有29种(51%)QBA方法解决了不可测量的混杂问题,19(33%)误分类偏差,6(11%)选择偏差,和3(5%)多重偏见。38(67%)QBA方法被设计用于生成偏差调整后的效应估计,18(32%)被设计用于描述偏差如何解释观察到的结果。22篇(39%)文章提供了实现QBA方法的代码或在线工具。
结论:在本系统综述中,在同行评审的文献中,我们确定了总共57种QBA方法用于总结流行病学数据.未来的研究人员可以使用此系统综述来确定汇总流行病学数据的不同QBA方法。
OBJECTIVE: Quantitative bias analysis (QBA) methods evaluate the impact of biases arising from systematic errors on observational study results. This systematic review aimed to summarize the range and characteristics of quantitative bias analysis (QBA) methods for summary level data published in the peer-reviewed literature.
METHODS: We searched MEDLINE, Embase, Scopus, and Web of Science for English-language articles describing QBA methods. For each QBA method, we recorded key characteristics, including applicable study designs, bias(es) addressed; bias parameters, and publicly available software. The study protocol was pre-registered on the Open Science Framework (https://osf.io/ue6vm/).
RESULTS: Our search identified 10,249 records, of which 53 were articles describing 57 QBA methods for summary level data. Of the 57 QBA methods, 53 (93%) were explicitly designed for observational studies, and 4 (7%) for meta-analyses. There were 29 (51%) QBA methods that addressed unmeasured
confounding, 19 (33%) misclassification bias, 6 (11%) selection bias, and 3 (5%) multiple biases. 38 (67%) QBA methods were designed to generate bias-adjusted effect estimates and 18 (32%) were designed to describe how bias could explain away observed findings. 22 (39%) articles provided code or online tools to implement the QBA methods.
CONCLUSIONS: In this systematic review, we identified a total of 57 QBA methods for summary level epidemiologic data published in the peer-reviewed literature. Future investigators can use this systematic review to identify different QBA methods for summary level epidemiologic data.