Identifying women at high-risk for breast cancer using data from the electronic health record compared to self-report.

Abstract

e13044 Background: One of the barriers to chemoprevention uptake among high-risk women is the lack of routine breast cancer risk assessment in the primary care setting. We calculated breast cancer risk using the Breast Cancer Surveillance Consortium (BCSC) model, which accounts for age, race/ethnicity, first-degree family history of breast cancer, benign breast disease, and mammographic density, using data collected from the electronic health record (EHR) compared to self-report. Methods: Among women undergoing screening mammography, we collected breast cancer risk information from the EHR and a self-administered survey. Eligibility criteria for calculating 5-year invasive breast cancer risk using the BCSC model included age 35-74, no prior history of breast cancer, mastectomy, or breast augmentation. We extracted data on demographics, structured first-degree family history, breast radiology and pathology reports from the EHR. We assessed agreement in breast cancer risk information between the EHR and self-report data. Results: Among 13,735 women with EHR data for BCSC risk calculation, 2708 women (20%) met high-risk criteria, based upon a 5-year breast cancer risk ≥1.67%. Among high-risk women, 2% were age 40-49, 23% age 50-59, 48% age 60-69, and 26% age 70-74. From the EHR, data was missing on 31% for race/ethnicity and 85% for family history. Among 2320 women with both EHR and self-report data, more complete information was available for race/ethnicity, family history, and breast biopsies in the surveys. More first-degree family history (14% vs. 3%) and prior breast biopsies (18% vs. 11%) were identified by self-report vs. EHR, respectively. However, more women with atypia and lobular carcinoma in situwere identified from the EHR. More high-risk women (20% vs. 16%) were identified with EHR vs. survey data, respectively, with correlation of 0.82. Conclusions: Among women undergoing screening mammography, we identified 20% who met high-risk criteria according to the BCSC model based upon EHR data, despite missing information on race/ethnicity, family history, and prior breast biopsies. This may serve as an initial screen for identifying women eligible for breast cancer chemoprevention.