Tool Boosts Accuracy in Assessing Breast Cancer Risk
SAN FRANCISCO -- August 19, 2015 -- A national risk model that gauges a woman’s chance of developing breast cancer has been refined to give a more accurate assessment. The revised figures, based on data from more than one million patients, reveal a 300% increase in a subset of women whose 5-year risk is estimated at 3% or higher.
In a study published on August 17 in the Journal of Clinical Oncology, researchers updated their current breast cancer risk model, which includes density categories -- an important factor in determining the possibility of developing the disease -- to one that also includes benign biopsy results.
The first version of the Breast Cancer Surveillance Consortium risk model does not account for non-malignant proliferative conditions diagnosed via biopsy. These include atypical ductal hyperplasia, which raises risk 3.5 to 5 times higher than those without the condition, and lobular carcinoma in situ, which raises risk to 7 to 11 times higher, according to the American Cancer Society.
Jeffrey Tice, MD, University of California at San Francisco, San Francisco, California, and colleagues analysed data from 1.1 million racially diverse women, aged 35 to 74 years, undergoing mammography with no history of breast cancer. During follow-up averaging 6.9 years, close to 18,000 women were diagnosed with invasive breast cancer -- defined as malignancy that had spread outside the lobules, or milk ducts, and had invaded healthy tissue.
When women with proliferative findings were identified, researchers discovered that the number whose risk for breast cancer was 3% or higher had swelled from 9.3% in the first version of the risk model to 27.8% in the updated model.
“This revised model enables us to more accurately identify those women whose risk may merit use of chemoprevention,” said Dr. Tice. “For these women, the benefits of medications that prevent breast cancer generally outweigh the harms.”
He believes that the new data boosts the benefits of the existing model, which calculates risk by age, race/ethnicity, family history of breast cancer and breast density.
“This new information will enable women to work with their physicians to implement an optimal screening and risk reduction plan to reduce their chances of breast cancer,” he said.
SOURCE: University of California, San Francisco