Breast density clearly a cancer risk factor

New model emphasizes denser breast tissue as a predictor of cancer risk
Doctor studying breast scan
Breast cancer is difficult to detect in women with dense breasts because dense tissue appears white, the same color as a tumor. The study showed that cancer risk can be almost four times greater for women with dense breasts. Photo by Todd McNaught

Breast density is nearly as important as age in determining a woman's risk of developing breast cancer, according to a new model developed by scientists from Group Health Cooperative's Center for Health Studies and seven other health-care organizations in the Breast Cancer Surveillance Consortium (BCSC). Dr. Emily White, an epidemiologist in the Hutchinson Center's Public Health Sciences Division, co-authored the findings.

Published in the September 6 issue of the Journal of the National Cancer Institute, the model is based on the largest study of this issue to date in terms of population size and the number of risk factors examined.

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 also more likely to develop breast cancer," said Dr. William Barlow, 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, Drs. Jinbo Chen and Mitchell Gail of the National Cancer Institute (NCI) presented 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.

The study was funded by NCI. The BCSC was established in 1994 by NCI to assess community mammography practice and outcomes, collect risk factors prospectively at the time of each screening mammogram, and ascertain cancer outcomes for all women. Center researchers on Group Health's BCSC advisory board include White and Drs. Chris Li, Anne McTiernan, Peggy Porter and Connie Lehman.

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