Decision Analysis of Breast Cancer Prophylactic Strategies in Postmenopausal Women: A Canadian Perspective. R. C. Lee, C. Donaldson, and L. Cook; CanTox Environmental Incorporated, and University of Calgary
Breast cancer detection and prophylaxis are currently of great interest to women at high risk of breast cancer and to health care payers. This is a complex decision, involving a number of possible alternatives for early detection or prevention, all of which have disparate benefits, risks (i.e. side effects), and costs. Decision analysis is a useful tool for evaluation of such disparate endpoints and associated uncertainties. The approach used is cost-utility analysis. The analysis is structured as a decision tree approach that incorporates a Markov model to examine changing costs and utilities (as measured by quality-adjusted life years, or QALYs) over time, as well as a Monte Carlo component for modeling uncertainties. The following alternatives are assessed: no action, screening, prophylactic mastectomy, tamoxifen treatment, raloxifene treatment, and lifestyle changes. The following health outcomes are assessed: invasive breast cancer, in situ breast cancer, endometrial cancer, stroke, venous thromboembolism, hip fracture, spinal fracture, cataracts, and clinical depression. Preliminary results indicate that, under current availability of alternatives in Canada, screening and lifestyle changes are preferred choices from an individual’s perspective, and screening and "no action" are preferred choices from a payer’s perspective. The drug raloxifene may represent a preferred alternative in both cases, contingent on a number of factors. Incremental costs per QALY gained are high for nondominated alternatives. Major uncertainties include discount rate, quality-of-life weights, and some costs. Results are robust to assessed uncertainties.
This project was funded by a grant from the Institute of Health Economics in Edmonton, Alberta. The views expressed in the paper are those of the authors and not the funding organization.
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