Assessing treatment effects and publication bias across different specialties in medicine: a meta-epidemiological study.

ABSTRACT:

Objectives

To assess the prevalence of statistically significant treatment effects, adverse events and small-study effects (when small studies report more extreme results than large studies) and publication bias (over-reporting of statistically significant results) across medical specialties.

Design

Large meta-epidemiological study of treatment effects from the Cochrane Database of Systematic Reviews.

Methods

We investigated outcomes from 57 162 studies from 1922 to 2019, and overall 98 966 meta-analyses and 5534 large meta-analyses (≥10 studies). Egger's and Harbord's tests to detect small-study effects, limit meta-analysis and Copas selection models to bias-adjust effect estimates and generalised linear mixed models were used to analyse one of the largest collection

SUBMITTER: Schwab S 

PROVIDER: S-EPMC8442042 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature