Meta-analysis and meta-regression are feasible and reliable statistical tools to assess the joint effect of divergent studies and studies that were underpowered or in uncertain areas. Meta-analysis should be performed accurately and have a clear objective. Conclusions of meta-analyses should not rely on small numbers of events and should not tell what is already known or obscure what should be remembered; similarly, those that rely on indirect comparison should be cautiously interpreted. New aspects of meta-analyses include analysis of subgroups, multivariate adjustment, assessment of bias or network meta-analyses. Meta-regression can elucidate the effect on variables predicted according to the results of previously available studies and can be adjusted for one or more explanatory variables that might influence the size of intervention effect. This has also been used for the estimation of the effect of novel therapies. This review summarises current knowledge related to meta-analysis and meta-regression with published examples.
Cordero et al. (2025) studied this question.