Methods for the bias adjustment of meta-analyses of published observational studies

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.