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A Predictive Model for the Development of Hormone-Responsive Breast Cancer

¹ Department of Surgery, The Lynn Sage Breast Program, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
² Department of Preventive Medicine, The Lynn Sage Breast Program, Feinberg School of Medicine, Northwestern University, Chicago, Illinois

Correspondence: Address correspondence and reprint requests to: Monica Morrow, MD, Department of Surgery, Fox Chase Cancer Center, 333 Cottman Avenue, C-302, Philadelphia, PA 19111-2497, USA; E-mail: monica.morrow{at}fccc.edu

Background: Effective therapies to reduce the risk of hormone-sensitive breast cancers (ER or PR positive) exist. Available models predict the risk of breast cancer without addressing hormone receptor status. The purpose of this study was to identify risk factors predictive of the development of hormone-sensitive cancers.

Methods: A total of 1285 invasive breast cancers in 1263 women were identified from a prospectively maintained database. Risk factors were compared for ER⁺ and ER^– cancers by using Fishers exact test.

Results: Models were developed for premenopausal and postmenopausal women. In premenopausal women, white race, age at menarche <12 years, and nulliparity or age at first birth >20 years were used. The risk of ER⁺ cancer increased from 67.7% with 0 variables to 83.8% with all three (P = .013). In postmenopausal women, white race and a history of estrogen therapy were used. With none of the variables present, the incidence of ER⁺ cancer was 70.0%; it was 77.6% with one variable and 85.4% with both variables (P = .002). In postmenopausal women, variables predicted significant differences in hormone sensitivity only for those aged 60 years. In the subset of women with information on alcohol use, adding this variable to the model improved the prediction of hormonal status.

Conclusions: Our findings, if prospectively validated, may help identify those who would obtain the greatest benefit from hormonal chemoprevention strategies for breast cancer risk reduction.

Key Words: Chemoprevention • Risk model • Estrogen receptor • Positive cancers • Hormone-sensitive cancers