Abstract
Background/Aims Women at increased risk for breast cancer (BC) are eligible to take selective estrogen receptor modulators (SERMs) to reduce their risk; Food and Drug Administration (FDA) approval of tamoxifen or raloxifene for BC risk reduction and American Society of Clinical Oncology guidelines for the use of SERMs recommend the two drugs for any woman over the age of 35 years with a 5-year risk of 1.67% or greater, but identifying those women can be both challenging and costly. Fortunately, the National Cancer Institute (NCI) has developed an open source Breast Cancer Risk Assessment Macro (BrCa RAM) that can be run using SAS software. By leveraging the Geisinger Health System (GHS) Electronic Health Record (EHR - EpicCare), the Department of Radiology’s software (Centricity RIS-IC), and Department of Pathology’s software (CoPath), we were able to calculate 5-year and lifetime risk of developing invasive BC.
Methods BrCa RAM calculates risk based on patient age, number of biopsies, if a biopsy ever displayed atypical hyperplasia (Yes/No), age at menarche, age at first live birth, number of first degree relatives with breast cancer, and patient race. We were able to extract and format these elements from EpicCare, RIS-IC, and CoPath. Demographic information (age, race, sex) was obtained from EpicCare, pathology information (number of biopsies, atypical hyperplasia) was obtained from CoPath, and personal history (number of first degree relatives with breast cancer, age at menarche, and age at first live birth) was obtained from RIS-IC.
Results We found 91,692 women between the ages of 35–90 in the RIS-IC database who had ever received a screening mammogram. We identified 9,021 patients with a calculated 5-year breast cancer risk 2% or greater and the mean age was 59.7 years. The numbers of patients by 5-year risk score category were: 2–2.5% (n = 3,551); 2.5–3% (n = 1,946); 3%+ (n = 3,524).
Conclusions The BrCa RAM is a powerful tool that enabled GHS to calculate breast cancer risk for our entire population. Using this macro, we were able to identify patients for prophylactic SERM treatment which can potentially prevent or delay a woman’s risk of developing BC.
