Bayesian synthesis using prior information on fracture risk from randomized trials to analyze post-market data

To conduct a Bayesian evidence synthesis using commonly available statistical procedures to estimate fracture risk for postmenopausal women undergoing hormonal therapy for breast cancer.

Using linked administrative data, we conducted a retrospective cohort study of women aged 66 years or older diagnosed with stage I to III breast cancer in Ontario, Canada, between April 1, 2003, and February 28, 2010. We used data augmentation to perform Bayesian Cox regression of the hazard of a hip, spine, or wrist/forearm fracture, adjusting for age, history of fragility fracture, corticosteroid use, osteoporosis, rheumatoid arthritis, dementia, or diabetes diagnoses.

Of 10,259 included in the sample, 3,733 initiated on tamoxifen and 6,526 on an aromatase inhibitor. Posterior probabilities that the hazard ratio (HR) exceeded 1 for aromatase inhibitor compared with tamoxifen were 46% (HR = 0.99, 95% credible interval [CrI] 0.71, 1.25), 35% (HR = 0.94, 95% CrI 0.78, 1.26), and 76% (HR = 1.08, 95% CrI 0.88, 1.32) with an uninformative prior, and 63% (HR = 1.04, 95% CrI 0.83, 1.3), 84% (HR = 1.12, 95% CrI 0.89, 1.4), and 89% (HR = 1.13, 95% CrI 0.93, 1.36) with an informative prior, for hip, spine, and wrist/forearm fractures, respectively.

Prior information resulted in higher posterior probabilities. The strength of evidence for increased risk varied by fracture site.