Identification of women at increased risk for breast cancer in a population-based screening program.

A multivariate model to assess breast cancer risk was developed by Gail et al. (M. H. Gail, L. A. Brinton, D. B. Byar, D. K. Corle, S. B. Green, C. Schairer, and J. J. Mulvihill, J. Natl. Cancer Inst., 81: 1879-1886, 1989) based on data analysis of the Breast Cancer Detection and Demonstration Project. We evaluated the model's usefulness for assigning women to risk groups for counseling and follow-up by applying it to the 1987 Texas Breast Screening Project data. We identified 3165 women with one or more first-degree relatives affected with breast cancer. The mean risk score for the group was 3.3 (range, 2.7-11.8), indicating a greater than 3-fold elevated risk. The mean risk score for the remaining 27,439 women without affected first-degree relatives was 1.5 (range, 1.24-3.2). Risk perception was found to be a motivator for participation. Women with a risk score greater than 5 perceived themselves to be at high risk for breast cancer. The perception of risk was related to the type of affected first-degree relatives: 80.0% of the women with three affected first-degree relatives and 71.5% of women whose mother and sister were both affected with breast cancer perceived themselves to be at high risk. The Gail model is potentially useful in the clinical setting because women at high risk for breast cancer can be entered into etiological studies, enrolled in primary prevention trials, or referred to programs seeking to improve compliance with screening mammography. The Gail model needs validation, but it is useful for estimating the risk of breast cancer in large populations.

Duke Scholars

Author Susan Halabi Biostatistics & Bioinformatics, Division of Biostatistics