The role of meta-analyses and umbrella reviews in assessing the harms of psychotropic medications: beyond qualitative synthesis. (16th July 2018)

• Record Type: Journal Article
• Authors: Solmi, M.; Correll, C. U.; Carvalho, A. F.; Ioannidis, J. P. A.
• Is Part Of: Epidemiology and psychiatric sciences. Volume 27:Number 6(2018)
• Page Start: 537
• Page End: 542
• Publication Date: 2018-07-16
• Subjects: Meta-analysis, -- psychotropic medications, -- safety, -- umbrella review; Epidemiology -- Periodicals; Mental illness -- Periodicals; Community psychiatry -- Periodicals; 362.2
• DOI: 10.1017/S204579601800032X
• Languages: English
• ISSNs: 2045-7960

Abstract

Abstract: ὠφελέειν, ἢ μὴ βλάπτειν (Primum non nocere) – Hιppocrates' principle should still guide daily medical prescribing. Therefore, assessing evidence of psychopharmacologic agents' safety and harms is essential. Randomised controlled trials (RCTs) and observational studies may provide complementary information about harms of psychopharmacologic medications from both experimental and real-world settings. It is considered that RCTs provide a better control of confounding variables, while observational studies provide evidence from larger samples, longer follow-ups, in more representative samples, which may be more reflective of real-life clinical scenarios. However, this may not always hold true. Moreover, in observational studies, safety data are poorly or inconsistently reported, precluding reliable quantitative synthesis in meta-analyses. Beyond individual studies, meta-analyses, which represent the highest level of 'evidence', can be misleading, redundant and of low methodological quality. Overlapping meta-analyses sometimes even reach different conclusions on the same topic. Meta-analyses should be assessed systematically. Descriptive reviews of reviews can be poorly informative. Conversely, 'umbrella reviews' can use a quantitative approach to grade evidence. In this editorial, we present the main factors involved in the assessment of psychopharmacologic agents' harms from individual studies, meta-analyses and umbrella reviews. Study design features, sample size, number of the events of interest, summary effect sizes, p -values, heterogeneity, 95% prediction intervals, confounding factor adjustment and tests of bias (e.g., small-study effects and excess significance) can be combined with other assessment tools, such as AMSTAR and GRADE to create a framework for assessing the credibility of evidence.