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1 Departments of Medical Biostatistics and Pathology and 2 Departments of Family Practice, Radiology, and Health Promotion Research, University of Vermont College of Medicine, and Vermont Cancer Center, Burlington, Vermont
Requests for reprints: Pamela M. Vacek, Medical Biostatistics, 25 B Hills Building, University of Vermont, Burlington, VT 05405. Phone: (802) 656-2526; Fax: (802) 656-0632. E-mail: pvacek{at}uvm.edu
Mammographic breast density is a major risk factor for breast cancer but estimates of the relative risk associated with differing density patterns have varied widely. It is also unclear how menopausal status influences this association and to what extent the effects of density are due to its correlation with other risk factors. Most recent investigations of breast density have been case-control studies, which provide indirect estimates of relative risk. We have prospectively followed 61,844 women for an average of 3.1 years to directly estimate risk among women in the four mammographic breast density categories defined by the American College of Radiology's Breast Imaging Reporting and Data System (BI-RADS). The study was population-based and used density assessments routinely made by community radiologists. Cox regression was used to obtain age-adjusted relative risk estimates and to control for other risk factors. Risk increased with density and the risk associated with extremely dense breasts, relative to entirely fatty breasts, was 4.6 (95% confidence interval, 1.7–12.6) for premenopausal women and 3.9 (95% confidence interval, 2.6–5.8) for postmenopausal women. Estimates for pre- and postmenopausal women did not differ significantly. Although breast density was significantly related to body mass index, age at first childbirth, and postmenopausal hormone use (P < 0.001), adjustment for these variables only slightly altered the relative risk estimates. Our results correspond well to those from case-control studies using more quantitative measures of mammographic breast density and suggest that routine Breast Imaging Reporting and Data System density measurements may be useful in models for assessing breast cancer risk in individual women.
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