Bayesian Meta-analysis of Hormone Therapy and Mortality in Younger Postmenopausal Women

Abstract

Background: There is uncertainty over the risks and benefits of hormone therapy. We performed a Bayesian meta-analysis to evaluate the effect of hormone therapy on total mortality in younger postmenopausal women. This analysis synthesizes evidence from different sources, taking into account varying views on the issue. Methods: A comprehensive search from 1966 through January 2008 identified randomized controlled trials of at least 6 month's duration that evaluated hormone therapy in women with mean age <60 years and reported at least one death, and prospective observational cohort studies that evaluated the relative risk of mortality associated with hormone therapy after adjustment for confounding variables. Results: The results were synthesized using a hierarchical random-effects Bayesian meta-analysis. The pooled results from 19 randomized trials, with 16,000 women (mean age 55 years) followed for 83,000 patient-years, showed a mortality relative risk of 0.73 (95% credible interval 0.52-0.96). When data from 8 observational studies were added to the analysis, the resultant relative risk was 0.72 (credible interval 0.62-0.82). The posterior probability that hormone therapy reduces total mortality in younger women is almost 1. Conclusions: The synthesis of data using Bayesian meta-analysis indicates a reduction in mortality in younger postmenopausal women taking hormone therapy compared with no treatment. This finding should be interpreted taking into account the potential benefits and harms of hormone therapy.

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