Abstract 5299: Validation of the BCSC model within the Mayo Benign Breast Disease Cohort
Authors: Ryan D. Frank, Celine M. Vachon, Stacey J. Winham, Robert A. Vierkant, Marlene H. Frost, Derek C. Radisky, Daniel W. Visscher, Amy C. Degnim
Journal: Cancer Research (2017)

Abstract Background: The Breast Cancer Surveillance Consortium (BCSC) model predicts invasive breast cancer risk in women with Benign Breast Disease (BBD), and recently incorporated BBD histology into the model. The BCSC has been validated in the Mayo Mammography Health Study, but has yet to be examined in Mayo Clinic’s BBD cohort. The Benign Breast Disease to Breast Cancer (BBD-BC) model predicts risk of both invasive and in situ breast cancer. Here we compare the performance of the BCSC and BBD-BC in Mayo Clinic’s BBD cohort. Methods: Eligible women underwent a breast biopsy with benign findings at the Mayo Clinic between years 1997-2001 and had a 4-view screening mammogram within six months of biopsy. Clinical BI-RADS density assessments using the 4th edition American College of Radiology were available on all mammograms, and were coded as almost entirely fat, scattered fibroglandular densities, heterogeneously dense, and extremely dense. Risk at 5 and 10 years of invasive cancer only (BCSC model) or both invasive and in situ cancer (BBD-BC model) were estimated. In situ cancers were censored at time of diagnosis for both models. Concordance statistics, i.e. model discrimination (higher is better), for each model were calculated using a Cox proportional hazards model with predicted risk as the sole predictor, and were compared using permutation tests. The ratio of total predicted (sum of predicted risk) to observed number of invasive breast cancers was used to assess model calibration. Calibration was not formally compared across models due to differences in how DCIS was treated in the development of each (BCSC censored; BBD-BC event). Results: 999 women met inclusion criteria. BI-RADS density was categorized as fatty in 46 (4.6%), scattered densities in 372 (37.2%), heterogeneously dense in 423 (42.3%), and extremely dense in 158 (15.8%). 62 invasive cancers occurred over a median 13.3yrs of follow-up, with 16 (25.8%) and 48 (77.4%) of the cancers occurring with-in 5 and 10 years. The concordance of the BCSC at 5 years was 0.550 (95% CI 0.409—0.691), compared to 0.719 (95% CI 0.578—0.860) for the BBD-BC (p-value=0.005). At 10 years the BCSC concordance was not significantly different from the BBD-BC, at 0.624 (95% CI 0.542—0.706) and 0.662 (95% CI 0.580—0.744), respectively (p-value=0.306). The BCSC over predicted the number invasive cancers in the BBD cohort at 5 years (predicted-to-observed=1.54; 95% CI 1.01—2.70), but was well calibrated at 10 years (1.06; 95% CI 0.83, 1.47). Conclusions: The BCSC model performed reasonably well in the BBD Cohort 10 years post-biopsy, but overestimated risk at 5 years. Additional study is needed to improve models for prediction of breast cancer risk among women with BBD. Citation Format: Ryan D. Frank, Celine M. Vachon, Stacey J. Winham, Robert A. Vierkant, Marlene H. Frost, Derek C. Radisky, Daniel W. Visscher, Amy C. Degnim. Validation of the BCSC model within the Mayo Benign Breast Disease Cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5299. doi:10.1158/1538-7445.AM2017-5299