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Evaluating adjuvant hormonal therapy in early-stage breast cancer: a comparison of predictive decision models
Methodist Hospital System, Weill Cornell University, Houston, TX
Current guidelines from both the National Comprehensive Cancer Network and the American Society of Clinical Oncology Technology Assessment Status Report recommend that aromatase inhibitors (AIs) be included in adjuvant hormonal therapy for women with hormone-receptor–positive, early-stage breast cancer to reduce the risk of tumor recurrence. However, the timing and duration of adjuvant AI therapy have not been specified, nor have treatment schedules been directly compared. In the absence of such complete data, predictive mathematical models have been developed to evaluate the relative utility of these treatment strategies. In this review, the author discusses potential applications as well as limitations of two current predictive models of optimal treatment strategies for adjuvant endocrine therapy for postmenopausal women with hormone-receptor–positive, early-stage breast cancer. This review also highlights relevant data from clinical trials used in the creation of these decision models.
| Commun Oncol 2007;4:277–282 | full text |  108 kb |