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Mammographic Density Correlation with Gail Model Breast Cancer Risk Estimates and Component Risk Factors

¹ City of Hope National Medical Center, Duarte, California; ² Fred Hutchinson Cancer Research Center; and ³ University of Washington School of Medicine, Seattle, Washington

Requests for reprints: Melanie R. Palomares, Department of Clinical Cancer Genetics, City of Hope National Medical Center, 1500 East Duarte Road, Duarte, CA 91010. Phone: 626-256-8662; Fax: 626-930-5495. E-mail: mpalomares{at}coh.org

Background: The Gail model is a validated breast cancer risk assessment tool that is primarily based on nonmodifiable breast cancer risk factors. Conversely, mammographic breast density is strongly correlated with breast cancer risk and responds to risk-modifying interventions. The purpose of our study was to correlate mammographic density with breast cancer risk as calculated by the Gail model and to examine the relative association of each of the model covariates to mammographic density.

Methods: The study included 99 participants of the National Surgical Breast and Bowel Project P-1 trial, ages 36 to 74 years, all of whom had a mammogram and Gail model risk estimates done upon trial entry. Baseline mammograms were retrieved and digitized, and mammographic density was assessed by both subjective and computer-assisted objective measures.

Results: Mammographic density was 2-fold higher in women with a >15% lifetime risk of breast cancer compared with those with <15% risk, by all density assessment methods. This was equivalent to a 3% to 6% increase in density per 10% increase in risk. Gail model covariates that measured benign or premalignant breast tissue changes accounted for the majority (41%) of the relationship with increased mammographic density. Seven percent of density was not explained by risk factors included in the Gail model.

Conclusions: The Gail model does not fully account for the association between breast density and calculated breast cancer risk. Because mammographic density is a modifiable marker, development of a breast cancer risk assessment tool that includes mammographic density could be beneficial for assessing individual risk. (Cancer Epidemiol Biomarkers Prev 2006;15(7):1324–30)

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