title: The use of meta-analysis in cost-effectiveness analysis. Issues and recommendations.
abstract: Meta-analysis is used to statistically pool the results from individual studies, usually randomised trials, to obtain an estimate of the summary effect size across studies. The summary measure from a meta-analysis is often used to derive the probability of treatment success in a cost-effectiveness analysis. Recently, LeLorier and colleagues questioned the ability of meta-analysis to accurately predict the results of a subsequent large-scale trial, implying that the use of a summary measure from a meta-analysis may be inappropriate in an economic evaluation. We comment on this potential shortcoming by first providing an outline of the use of meta-analysis results in a cost-effectiveness analysis. Then, using examples of discrepancies between meta-analyses and subsequent large trials noted by LeLorier and colleagues, we examine the potential impact of using the results from a small trial versus a meta-analysis. We found that the meta-analyses were comparable to or better than small trials at predicting the results of subsequent large trials. We, therefore, argue that a meta-analysis of homogeneous studies can provide a reasonable estimate of the treatment effect for use in a cost-effectiveness analysis when no large, definitive clinical trial has been performed. However, care must be taken not to over-interpret the precision of the estimate, since both the homogeneity and quality of the primary studies need to be considered. We conclude by providing guidance on the appropriate use of summary measures derived from meta-analyses for cost-effectiveness studies.
authors.affiliation: Department of Medicine, University of Washington, Seattle, USA. saint@umich.edu
authors.forename: S
authors.initials: S
authors.lastname: Saint
authors.forename: D L
authors.initials: DL
authors.lastname: Veenstra
authors.forename: S D
authors.initials: SD
authors.lastname: Sullivan
mesh_terms: D003362:Cost-Benefit Analysis / Q000706:statistics & numerical data*; D015201:Meta-Analysis as Topic