A simple technique investigating baseline heterogeneity helped to eliminate potential bias in meta-analyses

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Objectives: To perform a worked example of an approach that can be used to identify and remove potentially biased trials from metaanalyses via the analysis of baseline variables.
Study Design: True randomisation produces treatment groups that differ only by chance; therefore, a meta-analysis of a baseline measurement should produce no overall difference and zero heterogeneity. A meta-analysis from the British Medical Journal, known to contain significant heterogeneity and imbalance in baseline age, was chosen. Meta-analyses of baseline variables were performed and trials systematically removed, starting with those with the largest t-statistic, until the I2 measure of heterogeneity became 0%, then the outcome meta-analysis repeated with only the remaining trials as a sensitivity check.
Conclusion: We argue that heterogeneity in a meta-analysis of baseline variables should not exist, and therefore removing trials which contribute to heterogeneity from a meta-analysis will produce a more valid result. In our example none of the overall outcomes changed when studies contributing to heterogeneity were removed. We recommend routine use of this technique, using age and a second baseline variable predictive of outcome for the particular study chosen, to help eliminate potential bias in meta-analyses.
Original languageEnglish
Number of pages55
JournalJournal of Clinical Epidemiology
Early online date13 Oct 2017
Publication statusE-pub ahead of print - 13 Oct 2017

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© Elsevier, 2017. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy.


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