Validation of a decision model for preventive pharmacological strategies in postmenopausal women

AbstractBackground: Benefits and risks of a combined hormone replacement therapy (HRT) based on randomized clinical trial emerged on various disease endpoints in 2002. The Women’s Health Initiative (WHI) provides an important health answer for healthy postmenopausal women, such as do not use combined HRT to prevent chronic disease, because of the elevated risk of coronary artery disease (CHD), stroke and venous thromboembolism. In March 2004, the NIH stopped the drugs in the estrogen-alone trial after finding an increase risk of stroke and no effect, neither an increase or a decrease, on risk of CHD after an average of 7 years in the trial. On the other hand, raloxifene, which does not seem to significantly increase the risk of cardiovascular events and could retain skeletal benefits without stimulating endometrial and breast tissue, requires decision-makers since no current data on these disease clinical endpoints have been published. Objective: To construct a multi-disease model based on patient-specific risk factor profiles, and to validate the multi-disease model with several tools of internal and external validities. Methods: A Markov state model was developed. The risks of these various diseases (including coronary artery disease, stroke, hip fracture and breast cancer) are derived from published hazards proportional models which take into account significant risk factors. Canadian-specific rates and data sources for these transition probabilities are derived from published studies and Canadian Health Statistics. The validation of our model were based on several tools of internal and external validities, such as Canadian life expectancy, population-based incidence rate of diseases, clinical trials and other published life expectancy models. Results: First, presumably, small changes in the lifetime probability of dying support the hypothesis that the disease states operate in a largely independent fashion. For instance, the difference in the probability of dying from a particular disease by the complete elimination of a selected disease, such as CHD, stroke or breast cancer, ranged from 0.2 to 2.2% of difference in the lifetime probability of dying of these diseases. Second, we demonstrated that the model adequately predicted the Canadian population life-table and disease-incidence rates from population-based data among women from 45 to 75 years old. The predictions of the model were cross-checked from non-source data, such as predicted outcomes versus observed outcomes from results of clinical trials. Predicted relative risks of CHD event, breast cancer and hip fracture fell in the reported 95% confidence interval of clinical trials. Finally, predicted treatment benefits are comparable with those of published life expectancy models. Conclusions: The results of the study demonstrated that this multi-disease model, including coronary artery disease, stroke, hip fracture and breast cancer, is a valid model to predict the impact on life expectancy or number of events prevented for preventive pharmacological interventions.