Density Predicts Breast Cancer Risk, Study Shows

The researchers collected data from more than 1 million women at the time of their screening mammograms. They then identified 11,638 who were diagnosed with breast cancer within the next year. Information on women who did and did not get breast cancer was analyzed to develop and validate risk-prediction models.

Breast density is a measure of how well tissue can be seen on mammogram. Some tissue, such as the milk gland, is dense and appears white on an x-ray. This density makes it hard for doctors to see tumors, which also appear white. Fatty tissue is less dense and appears clear on the x-ray, allowing better tumor detection.

"Although breast cancer is harder to detect in women with dense breasts, our research showed that women with dense breasts are more likely to develop breast cancer," said William E. Barlow, PhD, a researcher with Group Health and the lead author of the article. After adjustment for age, the risk for breast cancer was almost four times greater for women with extremely dense breasts than for a woman with breasts that are almost entirely fat.

The scientists found that several risk factors influenced breast cancer diagnosis. In pre-menopausal women, risk factors included age, breast density, family history of breast cancer, and a prior breast procedure. In postmenopausal women, risk factors included ethnicity, greater body mass index, natural menopause, use of hormone therapy, a prior false-positive mammogram, as well as the risk factors found in pre-menopausal women.

In an accompanying article, Jinbo Chen, PhD, and Mitchell Gail, MD, PhD, of the National Cancer Institute (NCI), presents an updated version of the "Gail model," a breast cancer risk assessment tool that's been widely used since the 1980s. The updated version now includes breast density as well.

The new models may eventually help doctors identify women at high risk for breast cancer who might benefit from preventive interventions or more intensive screening, the researchers concluded. However, they cautioned that more research is needed before doctors can predict the development of cancer in individual women.