Being sceptical about meta-analyses: a Bayesian perspective on magnesium trials in myocardial infarction.
BACKGROUND
There has been extensive discussion of the apparent conflict between meta-analyses and a mega-trial investigating the benefits of intravenous magnesium following myocardial infarction, in which the early trial results have been said to be 'too good to be true'.


METHODS
We apply Bayesian methods of meta-analysis to the trials available before and after the publication of the ISIS-4 results. We show how scepticism can be formally incorporated into an analysis as a Bayesian prior distribution, and how Bayesian meta-analysis models allow appropriate exploration of hypotheses that the treatment effect depends on the size of the trial or the risk in the control group.


RESULTS
Adoption of a sceptical prior would have led early enthusiasm for magnesium to be suitably tempered, but only if combined with a random effects meta-analysis, rather than the fixed effect analysis that was actually conducted.


CONCLUSIONS
We argue that neither a fixed effect nor a random effects analysis is appropriate when the mega-trial is included. The Bayesian framework provides many possibilities for flexible exploration of clinical hypotheses, but there can be considerable sensitivity to apparently innocuous assumptions.
Higgins
Julian P T
JP
MRC Biostatistics Unit, Institute of Public Health, Cambridge, UK. julian.higgins@mrc-bus.cam.ac.uk
Spiegelhalter
David J
DJ
D001499:Bayes Theorem; D002121:Calcium Channel Blockers / Q000627:therapeutic use*; D006801:Humans; D008278:Magnesium Sulfate / Q000627:therapeutic use*; D015201:Meta-Analysis as Topic; D009203:Myocardial Infarction / Q000188:drug therapy*; D016032:Randomized Controlled Trials as Topic
D002121:Calcium Channel Blockers; D008278:Magnesium Sulfate