Introduction: Because of diminishing resources for new studies that could take years to complete, and the large number of interventions and treatments that need to be evaluated, quantitative methods for combining data will be needed to fully utilize results from existing observational studies. Quantitative methods for combining existing research results include reviews that combine original individual patient data and reviews that combine published and unpublished summary results.
Objective: To determine the relative merits of two quantitative methods used to estimate summary effects of observational studies by comparing results from a published pooled analysis to those from an original meta-analysis.
Methods: We compared a published pooled analysis that included an analysis of the relationship of oral contraceptive (OC) use and risk for epithelial ovarian cancer to an original meta-analysis of the studies used in the published pooled analysis. We calculated a dose-response slope from a linear model for the effects of duration of OC use on the log relative risk of ovarian cancer, again weighting each risk estimate for a given duration by the inverse of the variance of that risk. We tested for heterogeneity and performed subgroup analyses. We calculated estimates of the cost of both procedures.
Results: We found excellent quantitative agreement between the summary effect from the meta-analysis and the pooled analysis. A protective effect was apparent for studies with hospital control subjects (OR = 0.62 (0.39-0.99)) and for studies with community control subjects (OR = 0.55 (0.42-0.70)). A planning grant ($23,000) and 2 year analytical grant ($235,000) combined to show a cost of $259,300 for the pooled analysis, approximately 5 times that of the meta-analysis.
Discussion: We conclude that pooled analysis is preferred under the following circumstances: 1) when relationships among outcomes, exposures, and confounders that are not reported by the original investigators are of interest, 2) the original summary parameters differ and cannot be combined, or 3) when the issue being investigated is new and only a few studies are available. We conclude that meta-analysis is appropriate in the following circumstances:
* when resources are limited, or
* when original study data are not available or available from a biased sample of studies.
In public health and epidemiology, there may be fewer opportunities to apply pooled analysis than to apply meta-analysis because data from original studies for use in pooled analysis may be accessible only to limited numbers of research groups.