Assessment of key characteristics, methodology, and effect size measures used in meta-analysis of human-health-related animal studies

Res Synth Methods. 2022 Nov;13(6):790-806. doi: 10.1002/jrsm.1578. Epub 2022 Jul 8.

Abstract

Since the early 1990s the number of systematic reviews (SR) of animal studies has steadily increased. There is, however, little guidance on when and how to conduct a meta-analysis of human-health-related animal studies. To gain insight about the methods that are currently used we created an overview of the key characteristics of published meta-analyses of animal studies, with a focus on the choice of effect size measures. An additional goal was to learn about the rationale behind the meta-analysis methods used by the review authors. We show that important details of the meta-analyses are not fully described, only a fraction of all human-health-related meta-analyses provided rationales for their decision to use specific effect size measures. In addition, our data may suggest that authors make post-hoc decisions to switch to another effect size measure during the course of their meta-analysis, and possibly search for significant effects. Based on analyses in this paper we recommend that review teams: 1) publish a review protocol before starting the conduct of a SR, prespecifying all methodological details (providing special attention to the planned meta-analysis including the effect size measure and the rational behind choosing a specific effect size, prespecifying subgroups and restricting the number of subgroup analyses), 2) always use the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) checklist to report your SR of animal studies, and 3) use the random effects model (REM) in human-health-related meta-analysis of animal studies, unless the assumptions for using the fixed effect model (FEM) are all met.

Keywords: effect size measures; meta-analysis; meta-research; systematic review of animal studies.

Publication types

  • Meta-Analysis

MeSH terms

  • Animals
  • Checklist*
  • Humans
  • Research Design
  • Research Report*