Novel Features of Breast Tissue May Predict Cancer Risk
Study suggests tissue-based approach offers way to measure individual risk
TUESDAY, Oct. 6 (HealthDay News) -- Assessing the features of a woman's normal breast tissue can help to identify those at increased risk of breast cancer, according to a study published online Oct. 5 in the Journal of Clinical Oncology.
Kevin P. McKian, M.D., of the Mayo Clinic in Rochester, Minn., and colleagues conducted a study of 85 women who underwent a benign breast biopsy and who developed breast cancer, as well as 142 age-matched controls from the Mayo Benign Breast Disease cohort. They counted the number of acini per lobule and lobular area and predicted the five-year risk of breast cancer.
The number of acini per lobule was associated with breast cancer risk in a step-wise manner, regardless of parity, histology and family history of the disease, the researchers found.
"Optimal early detection and prevention strategies for breast cancer require accurate identification of individuals at significantly increased risk for the disease," the authors write. "We have developed a means to assess degree of regression of normal breast lobules quantitatively. We have shown that higher acinar counts within the lobules and larger lobule size are associated with higher risk of breast cancer. These simple physiologic features may offer an alternative strategy for breast cancer risk prediction in women who have had benign breast biopsies."