Meta-analysis of Clinical Trials

Meta-analysis has become a popular approach for summarizing a large number of clinical trials and resolving discrepancies raised by these trials. In this chapter, we introduce the general procedures for meta-analysis: formulating the question, defining eligibility, identifying studies, abstracting data, statistical analysis, and reporting the results. One key issue determining whether studies can be combined is the extent of heterogeneity among individual studies. We review graphical and statistical tools for assessing heterogeneity, describing the fixed-effect and random-effect models commonly used in meta-analysis, and providing some general recommendations regarding when fixed-effect or random-effect approach is appropriate. Publication bias is an inherent issue with meta-analysis, since studies (especially smaller ones) with "negative" results are frequently unpublished. Funnel plot, Begg and Mazumdar's rank correlation, and Egger regression are useful tools for assessing publication bias. As an illustration of the concepts discussed, we apply meta-analysis techniques to studies examining the use of antiinflammatory therapies in sepsis.