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

作者：Hicks Amy^*; Fairhurst Caroline; Torgerson David J

来源：Journal of Clinical Epidemiology, 2018, 95: 55-62.

DOI：10.1016/j.jclinepi.2017.10.001

• Meta-analysis
• Heterogeneity
• Baseline variables
• Bias

Objectives: To perform a worked example of an approach that can be used to identify and remove potentially biased trials from meta analyses 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 I-2 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.

• 出版日期2018-3