Two Breast Imaging Reporting and Data System (BI-RADS) density measures were found to produce similar results as a one-density model for predicting 5-year breast cancer risk in women, according to an article published online in the journal Cancer Epidemiology, Biomarkers & Prevention.
Participants in the study included 722,654 women ranging between 35 to 74 years who completed two mammograms approximately 1.8 years apart.
The two mammograms had BI-RADS density measures and found that 13,715 of the women developed invasive breast cancer. Several factors were evaluated using Cox regression to find their relative hazards of breast cancer.
These factors included the women’s age, race/ethnicity, family history of breast cancer, breast biopsy history, and either one or two density measures.
Results showed that the two-measure density model had a slightly increased accuracy than the one-measure density model (AUC, 0.640 vs. 0.635). A specific group (15.4%) of women had their density decreased from heterogeneous or extremely dense to a lessened density with one other risk factor.
The 20,741 women had a clinically significant increase in 5-year risk with the one-measure density model compared to the two-measure density model (<1.67% to ≥1.67%, respectively).
The study suggests that a two-measure density model be considered for women whose breast density decreases when calculating breast cancer risk.
Two Breast Imaging Reporting and Data System density measures were found to produce similar results for cancer risk.
One measure of Breast Imaging Reporting and Data System (BI-RADS) breast density improves 5-year breast cancer risk prediction, but the value of sequential measures is unknown.