School of Population Health, University of Queensland, Brisbane, Queensland, Australia.
J Eval Clin Pract. 2013 Aug;19(4):653-7. doi: 10.1111/j.1365-2753.2012.01890.x. Epub 2012 Jul 29.
A unique challenge in meta-analysis of observational studies is bias adjustment. Two different approaches have been proposed for doing this - using summary scores versus component scores. The prevailing view on this matter is that summary quality scores are inaccurate because information from its components can cancel each other out.
A head-to-head comparison of the component score adjustment with our method using summary scores is undertaken, using data reported by the authors of the component method.
It is demonstrated that the consideration of components or of aggregate scores does indeed lead to the same conclusions. Yet, the latter does not require imputation of the direction and magnitude of changes to effect sizes.
The summary quality score used for bias adjustment within the context of an appropriate model may be most expedient. Implications for the bias adjustment of meta-analyses of observational studies are discussed.
观察性研究荟萃分析中的一个独特挑战是偏倚调整。为此提出了两种不同的方法 - 使用综合评分与分量评分。关于这个问题的主流观点认为，综合质量评分不准确，因为其分量的信息可能相互抵消。
使用分量方法的作者报告的数据，对使用综合评分的分量评分调整与我们的方法进行了头对头比较。
结果表明，考虑分量或综合评分确实会得出相同的结论。然而，后者不需要对效应大小的变化方向和幅度进行推断。
在适当的模型背景下，用于偏倚调整的综合质量评分可能最为便捷。讨论了对观察性研究荟萃分析的偏倚调整的影响。
