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JAMA Guide to Statistics and Methods
January 22, 2019

Random-Effects Meta-analysis: Summarizing Evidence With Caveats

Author Affiliations
  • 1Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California
  • 2Meta-research Innovation Center at Stanford, Stanford, California
  • 3Department of Medicine, Stanford University School of Medicine, Stanford, California
JAMA. 2019;321(3):301-302. doi:10.1001/jama.2018.19684

Questions involving medical therapies are often studied more than once. For example, numerous clinical trials have been conducted comparing opioids with placebos or nonopioid analgesics in the treatment of chronic pain. In the December 18, 2018, issue of JAMA, Busse et al1 evaluated the evidence on opioid efficacy from 96 randomized clinical trials and, as part of that work, used random-effects meta-analysis to synthesize results from 42 randomized clinical trials on the difference in pain reduction among patients taking opioids vs placebo using a 10-cm visual analog scale (Figure 2 in Busse et al).1 Meta-analysis is the process of quantitatively combining study results into a single summary estimate and is a foundational tool for evidence-based medicine. Random-effects meta-analysis is the most common approach.