Methodological standards for conducting and reporting meta-analyses: Ensuring the replicability of meta-analyses of pharmacist-led medication review

Meta-analyses of clinical pharmacy services are frequently criticized for restricted data transparency and reproducibility.To describe the methodological characteristics of meta-analyses of pharmacist-led medication reviews, to identify the elements that limit their replicability and robustness, and to propose recommendations for an appropriate conduction and reporting.A meta-research study was conducted. Systematic searches of the PubMed, Scopus, and Web of Science databases were performed to identify meta-analyses of pharmacist services. Meta-analyses assessing the effect of pharmacist-led medication reviews were selected for data extraction, analysis and replication. Two replication exercises were performed for the two most common outcomes: (i) considering the data provided by authors to construct the meta-analysis and (ii) considering the raw data available in the primary studies included. Prediction intervals (PI), fragility index (FI), and number needed to treat (NNT) were also calculated for each replicated meta-analysis.Nine studies reporting meta-analyses about pharmacist-led medication review were found comprising 30 different outcomes. Eleven meta-analyses, including six for hospital admission and five for mortality, were replicated. In five meta-analyses, the pooled effect sizes of the replicated meta-analyses differed from the original ones. Only four meta-analyses mentioned the statistical method used. Other meta-analytic parameters (e.g., q-value, tau2) were omitted in all studies. In nine meta-analyses, the data from primary studies had been incorrectly extracted for at least one variable. The PI demonstrated that the uncertainty intervals of the effect sizes were always underestimated by the authors. NNTs showed wide intervals, ranging from benefit to harm, in almost all meta-analyses. Nine recommendations to facilitate the replication of a meta-analysis were proposed: providing all original data needed to build the analysis; informing about the imputed data or data obtained from different sources; performing sensitivity analyses for imputed or unpublished data; inform about all the statistical methods used; providing all statistical results; and reporting the PI, FI and NNT.Errors in data extraction and poor reporting of meta-analytic parameters are common in the pharmacy literature. We proposed nine recommendations to enhance data reproducibility and interpretability. Journal editors and peer reviewers should ensure that authors strictly comply with minimum standards for conduction and reporting of meta-analyses.