A comparison of results of meta-analyses of randomized control trials and recommendations of clinical experts. Treatments for myocardial infarction.

  • 8 July 1992
    • journal article
    • research article
    • Vol. 268 (2), 240-8
Abstract
To examine the temporal relationship between accumulating data from randomized control trials of treatments for myocardial infarction and the recommendations of clinical experts writing review articles and textbook chapters. (1) MEDLINE search from 1966 to present; search terms used were myocardial infarction, clinical trials, multicenter studies, double-blind method, meta-analysis, and the text word "random:"; (2) references from pertinent articles and books; and (3) all editions of English-language general medical texts and manuals and review articles on treatment of myocardial infarction. Randomized control trials of therapies for reducing the risk of total mortality in myocardial infarction (acute and secondary prevention). Review articles and textbook chapters dealing with the general clinical management of patients with myocardial infarction. Two authors read the material and recorded the results; disagreements were resolved by conference. We used the technique of cumulative meta-analysis (performing a new meta-analysis when the results of a new clinical trial are published) and compared the results with the recommendations of the experts for various treatments for myocardial infarction. Discrepancies were detected between the meta-analytic patterns of effectiveness in the randomized trials and the recommendations of reviewers. Review articles often failed to mention important advances or exhibited delays in recommending effective preventive measures. In some cases, treatments that have no effect on mortality or are potentially harmful continued to be recommended by several clinical experts. Finding and analyzing all therapeutic trials in a given field has become such a difficult and specialized task that the clinical experts called on to summarize the evidence in a timely fashion need access to better databases and new statistical techniques to assist them in this important task.