Adapted from the NCI Cancer Bulletin.
Two new models for assessing a patient's risk of developing breast cancer focus on breast density as an important predictor. The two studies are reported in the September 6, 2006, Journal of the National Cancer Institute.
In the first study, Dr. William E. Barlow of Cancer Research and Biostatistics, and Group Health Cooperative in Seattle, and colleagues identified 11,638 women diagnosed with breast cancer within the Breast Cancer Surveillance Consortium, a large prospective study of mammography in clinical practice in the United States.
The study developed prediction models for pre- and postmenopausal women and used breast density reported as part of routine screening mammography by radiologists in clinical practice. The factors predicting risk in premenopausal women were limited to age, breast density, family history of breast cancer, and prior breast procedure. These factors also predicted risk for postmenopausal women, as did the additional risk factors of ethnicity, body mass index, natural menopause, use of hormone therapy, and a prior false-positive mammogram.
"The models establish breast density as a highly clinically significant predictor of breast cancer risk that is almost as powerful a risk factor as age...Nonetheless, ability to accurately predict breast cancer at the individual level remains limited," the authors wrote. However, these models may be helpful in identifying women at high risk for breast cancer who may benefit from preventive interventions or more intensive surveillance.
The second study, headed by Drs. Jinbo Chen and Mitchell H. Gail of NCI's Division of Cancer Epidemiology and Genetics, assessed the absolute risk of developing breast cancer using an updated version of the Gail model. The Gail model was developed in the 1980s to assess the risk of breast cancer for women who undergo annual mammography screening.
The new model included breast density, weight, age at first live birth, number of benign breast biopsy examinations, and number of first-degree relatives with breast cancer. The researchers investigated whether information on breast density, which was available for 7,251 women in the Breast Cancer Detection Demonstration Project (BCDDP), could improve absolute breast cancer risk projections compared with an earlier version of the Gail model, which was also based on BCDDP data.
The new model predicted higher risks than the previous model in women with high breast density, and previous analyses indicated that the new model had modestly higher discriminatory accuracy. However, Dr. Gail cautioned, "Independent validation studies are needed before we would recommend using this model for counseling."