When patient-level data are not available, confounding in meta-analysis can be minimized by using adjusted odds and/or hazard ratios from each source study. In their analysis, Chatterjee et al1(p133) instead chose to use unadjusted odds ratio (ORs) to “avoid bias from different types of adjustments in the various studies.” They adjusted their meta-regression with a limited number of group-level candidate predictors, which—except for baseline creatinine and hemoglobin levels—have not been validated as significant predictors of events in previous multivariate studies on the topic. This choice is not without serious limitations because it may lead to inaccurate inferences, especially when used with observational data.2