Mega-trials and management of acute myocardial infarction
The LancetPublished 1 September 1995
KL Woods
Citations72
SJR quartileQ1
SJR score12.11
SNIP22.72
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TL;DR
These issues are illustrated by the examples of nitrates, angiotensin-converting-enzyme inhibitors, and magnesium in acute myocardial infarction but have general relevance to the validity and generalisability of simple trials.
Abstract
Clinical management of acute myocardial infarction has been strongly influenced by large, simple trials (mega-trials) with unrestrictive protocols and limited data collection. The design has been adopted to increase statistical power to a maximum. Its validity rests on an effective randomisation procedure and intention-to-treat analysis of deaths. Experience has shown that mega-trials tend to generate effect-estimates nearer the null than those from conventional trials or meta-analyses. When a small or absent observed treatment effect (or subgroup effect) in a mega-trial contrasts with the results of conventionally designed trials, it is necessary to assess both null bias and failure to increase the true treatment effect to a maximum in the mega-trial. Null bias will arise when the contrast between treatment and no-treatment, or between subgroups, is blunted either by non-protocol therapy or by inaccuracy of data, including misclassification between subgroups. Each is more likely with an unrestrictive design. To increase the true treatment effect to a maximum, trial conditions must be specified with insight into mechanism, dose-dependence, and time-dependence. The mega-trial design is therefore unsuited to an exploratory role. These issues are illustrated by the examples of nitrates, angiotensin-converting-enzyme inhibitors, and magnesium in acute myocardial infarction but have general relevance to the validity and generalisability of simple trials.
Keywords
MathematicsMedicineEconomics, Econometrics and Finance
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