Kerlikowske K, et al. – This study combined quantitative and qualitative breast density measures to assess breast cancer risk. As compared to risk models with either measure alone, risk models with automated dense breast volume combined with Breast Imaging Reporting and Data System [BI–RADS] breast density seemed to better identify women with dense breasts at high breast cancer risk.

Methods

• A case-control study of 1720 women with invasive cancer and 3686 control subjects, was performed.
• ORs and 95% CIs were appraised for the effect of BI-RADS breast density and Volpara automated dense breast volume on invasive cancer risk, adjusting for other BCSC risk model factors plus body mass index (BMI).
• Analysts compared C-statistics between models.
• BCSC 5-year breast cancer risk, incorporating the adjusted ORs associated with dense breast volume, was measured.

Results

• Women with BI-RADS extremely dense breasts and third- or fourth-quartile dense breast volume (75% of women with extremely dense breasts) had high breast cancer risk (OR 2.87, 95% CI 1.84–4.47, and OR 2.56, 95% CI 1.87–3.52, respectively), than women with BI-RADS scattered fibroglandular densities and second-quartile dense breast volume.
• On the other hand, women with extremely dense breasts and first- or second-quartile dense breast volume were not at significantly increased breast cancer risk (OR 1.53, 95% CI 0.75–3.09, and OR 1.50, 95% CI 0.82–2.73, respectively).
• Moreover, adding continuous dense breast volume to a model with BCSC risk model factors and BMI increased discriminatory accuracy compared with a model with only BCSC risk model factors (C-statistic 0.639, 95% CI 0.623–0.654, vs. C-statistic 0.614, 95% CI 0.598–0.630, respectively; P<0.001).
• Investigation indicated a BCSC 5-year risk of 2.5% in women with dense breasts and fourth-quartile dense breast volume.
• However, women with dense breasts and first-quartile dense breast volume had a 5-year risk≤1.8%.