Journal
JOURNAL OF CLINICAL EPIDEMIOLOGY
Volume 142, Issue -, Pages 280-287Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.jclinepi.2021.08.004
Keywords
Baseline risk; Cochrane Database of Systematic Reviews (CDSR); Correlation; Meta -analysis; Odds ratio; Relative risks
Funding
- National Center for Advancing Translational Sciences Award [UL1-TR002494 (HC) 524]
- National Library of Medicine Award of the National Institutes of Health [R01LM012982, R01LM013049, R01LM012607]
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Studies in the Cochrane Database of Systematic Reviews have shown that study-specific OR tends to be higher in studies with lower baseline risks and there is a strong negative correlation between OR (RR or RD) and baseline risk, with conditional effects notably varying with baseline risks.
Objectives: A recent paper by Doi et al. advocated completely replacing the relative risk (RR) with the odds ratio (OR) as the effect measure in clinical trials and meta-analyses with binary outcomes. Besides some practical advantages of RR over OR, Doi et al.'s key assumption that the OR is portable in the meta-analysis, that is, study-specific ORs are likely not correlated with baseline risks, was not well justified. Study designs and settings: We summarized Spearman's rank correlation coefficient between study-specific ORs and baseline risks in 40,243 meta-analyses from the Cochrane Database of Systematic Reviews. Results: Study-specific ORs tend to be higher in studies with lower baseline risks of disease for most meta-analyses in Cochrane Database of Systematic Reviews. Using an actual meta-analysis example, we demonstrate that there is a strong negative correlation between OR (RR or RD) with the baseline risk and the conditional effects notably vary with baseline risks. Conclusions: Replacing RR or RD with OR is currently unadvisable in clinical trials and meta-analyses. It is possible that no effect measure is portable in a meta-analysis. In addition to the overall (or marginal) effect, we suggest presenting the conditional effect based on the baseline risk using a bivariate generalized linear mixed model. (C) 2021 Elsevier Inc. All rights reserved.
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