SEATTLE--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 and seven other health care organizations in the Breast Cancer Surveillance Consortium (BCSC). Presented 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 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.
The study was funded by the National Cancer Institute (NCI).
About the Breast Cancer Surveillance Consortium (BCSC)
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. The seven BCSC mammography registries that participated in this study included Group Health's Breast Cancer Surveillance Project, Carolina Mammography Registry, Colorado Mammography Project, New Hampshire Mammography Network, New Mexico mammography Project, San Francisco Mammography Registry, and the Vermont Breast Cancer Surveillance System. More information can be found at: www.breastscreening.cancer.gov .
About Group Health Center for Health Studies
Founded in 1947, Group Health is Seattle-based, consumer-governed, nonprofit health care system that coordinates care and coverage. The Group Health Center for Health Studies conducts research related to prevention, diagnosis, and treatment of major health problems. It is funded primarily through government and private research grants. More information can be found at: www.centerforhealthstudies.org .
Questions & Answers about the new breast cancer risk models
What did the researchers find?
In developing a new model to assess risks for breast cancer, the researchers identified several factors, which differed slightly between pre- and postmenopausal women. In pre-menopausal women, risk factors included greater age, higher breast density, family history of breast cancer, and a prior breast procedure. In postmenopausal women, risk factors also included ethnicity, greater body mass index, natural menopause, use of hormone therapy, and a prior false-positive mammogram, as well as the risk factors found in pre-menopausal women.
Their research appears in the September 6 issue of the Journal of the National Cancer Institute.
What was the most surprising finding?
The most surprising finding was that breast density is nearly as important as age in determining a woman's risk of developing breast cancer, even after taking into account other related factors. For example, after adjustment for age, the risk for women with highly dense breasts was more than three times greater than that for women whose breasts were the least dense.
What is breast density?
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, making tumors, which also appear white, harder to see. Fatty tissue is less dense and appears clear on the x-ray, allowing better tumor detection.
How is breast density determined?
Radiologists who examine x-rays of breast tissue assign a score of one to four based on how clear or opaque the breast tissue appears. A score of one is the lowest and a score of four is the highest. Although this is a subjective measure by individual radiologists, there are guidelines for using the four breast density values. How will these new findings affect breast cancer screening? It's too soon to tell. With more research to validate the models, doctors might use breast density, along with other risk factors, to identify women who could benefit from preventive interventions or more intensive screening. Currently, however, the models cannot be used to predict the development cancer in individual women.
What can women do to reduce their risk of breast cancer?
How was the study conducted?
Researchers examined breast cancer risk factor data collected on more than 1 million women from the United States at the time of their screening mammogram and identified all women who were diagnosed with breast cancer within the next year. A total of 11,638 women were diagnosed with breast cancer. The information on women who did and did not develop breast cancer was used to develop and validate risk prediction models.
Who conducted the study?
Scientists involved in the Breast Cancer Surveillance Consortium, including:
The study was funded by the National Cancer Institute.
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JNCI Journal of the National Cancer Institute