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PURPOSE: Few breast cancer risk assessment models account for the risk profiles of different tumor subtypes. This study evaluated whether a subtype-specific approach improves discrimination. METHODS: Among 3389 women who had a screening mammogram and were later diagnosed with invasive breast cancer we performed multinomial logistic regression with tumor subtype as the outcome and known breast cancer risk factors as predictors. Tumor subtypes were defined by expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) based on immunohistochemistry. Discrimination was assessed with the area under the receiver operating curve (AUC). Absolute risk of each subtype was estimated by proportioning Gail absolute risk estimates by the predicted probabilities for each subtype. We then compared risk factor distributions for women in the highest deciles of risk for each subtype. RESULTS: There were 3,073 ER/PR+ HER2 - , 340 ER/PR +HER2 + , 126 ER/PR-ER2+, and 300 triple-negative breast cancers (TNBC). Discrimination differed by subtype; ER/PR-HER2+ (AUC: 0.64, 95% CI 0.59, 0.69) and TNBC (AUC: 0.64, 95% CI 0.61, 0.68) had better discrimination than ER/PR+HER2+ (AUC: 0.61, 95% CI 0.58, 0.64). Compared to other subtypes, patients at high absolute risk of TNBC were younger, mostly Black, had no family history of breast cancer, and higher BMI. Those at high absolute risk of HER2+ cancers were younger and had lower BMI. CONCLUSION: Our study provides proof of concept that stratifying risk prediction for breast cancer subtypes may enable identification of patients with unique profiles conferring increased risk for tumor subtypes.
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BACKGROUND: Currently, racial disparities exist in access to genetic testing. Recent developments have helped narrow the gap in accessibility. The purpose of this study was to determine whether racial disparities in genetic consultation attendance and completion of genetic testing persist, and, if so, factors that contribute to under-utilization of these resources. METHODS: A single-institution retrospective review of breast patients referred for genetic counseling between 2017 and 2019 was performed. Univariate and multivariate logistic regression evaluated factors associated with genetic counseling attendance and genetic testing. RESULTS: A total of 596 patients were referred for genetic counseling: 433 (72.7%) white; 138 (23.2%) black; and 25 (4.2%) other or unknown. In multivariate analysis, black patients, patients without breast cancer family history, and patients without a current cancer diagnosis, classified as high risk, were significantly less likely to attend their genetics appointment (p = 0.010, p = 0.007, p = 0.005, respectively). Age, insurance type, distance from facility, and need for chemotherapy did not significantly impact consult completion rate. Of the patients who completed a genetic consult, 84.4% (n = 248) had genetic testing and 17.7% (n = 44) had a pathogenic variant. For patients who attended counseling, there were no significant factors that were predictive with receipt of genetic testing. CONCLUSIONS: In this study, there was a significant association between race and attending genetic counseling. Once counseled, most patients went on to receive genetic testing, and racial disparities in testing disappeared, emphasizing the value of providing additional education about the importance and purpose of genetic testing.