Breast Cancer Risk Prediction Models among African-American Women

Statistical models have been developed to predict an individual woman’s risk of breast cancer. Existing breast cancer risk assessment models, such as the Gail model, are less accurate in predicting risk in African American women than they are in white women. African American women are more likely than white women to develop breast cancer before age 40 and to be diagnosed with estrogen receptor-negative (ER-negative) breast cancer, a subtype associated with poorer prognosis and increased 5-year mortality. A risk prediction model previously developed for African American women has yet to be validated among younger women. In addition, current breast cancer risk assessment models perform poorly in predicting risk of ER-negative breast cancer. Efforts are needed to develop models for African American women with better accuracy to predict an individual woman’s absolute risk of breast cancer, particularly early-onset breast cancer and ER-negative breast cancer.

Our objectives are to conduct analyses within the Black Women’s Health Study (BWHS) to validate an existing breast cancer risk prediction model for African American women and to develop a new risk model, by including additional breast cancer risk factors, that will better estimate breast cancer risk for African American women.

Lynn Rosenberg, Sc.D., Principal Investigator
Slone Epidemiology Center

Deborah Boggs, Sc.D., Epidemiologist
Slone Epidemiology Center

Michael Pencina, Ph.D., Biostatistician
Boston University School of Public Health

Source of Funding:

Susan G. Komen for the Cure

Study Period:

2011 to 2014