Brantley, Kristen D

Background: Several breast cancer (BC) risk prediction models have been developed to provide personal risk assessments. Though individually validated, their performance has not been systematically evaluated across a wide range of populations or ages. Methods: We harmonized individual-level baseline questionnaire data and incident BC diagnoses from 21 cohorts from North America, Europe, and Australia participating in the Breast Cancer Risk Prediction Project. Five-year absolute risk of invasive BC was estimated for five established risk prediction models using classical risk factors only. Discrimination was evaluated by area under the curve (AUC). Calibration was assessed using average and risk-decile specific expected to observed (E/O) ratios. Performance metrics were meta-analyzed across cohorts and models. Metaregression tested associations between cohort characteristics and performance metrics. Results: This analysis included 1,595,977 women aged 20-75 years, enrolled in studies between 1976-2015, with 19,062 (1.2%) invasive BC cases ascertained within 5 years from exposure assessment. Age-adjusted AUCs were similar across models and cohorts (pooled AUCs by model: 0.57-0.58), while E/O ratios varied substantially (pooled E/O ratios by model: 0.83-1.25). Overestimation was common among predicted high-risk individuals (>3%). No appreciable differences in model performance by cohort age, birth year, race, and variable missingness emerged. Calibration improved after assigning race-specific incidence rates. Conclusion: Existing BC risk prediction models provided similar risk discrimination across multiple cohorts, although there was overestimation of risk for high-risk individuals. Performance variation across cohorts was not driven by specific characteristics, which supports development of a unified risk model for diverse populations that leverages appropriate incidence rates.

Background: Breast cancer polygenic risk scores (PRS) and traditional risk models (e.g., the Gail model [Gail]) are known to contribute largely independent information, but it is unclear how the overlap varies by ancestry, age, disease type (invasive breast cancer, DCIS), and risk threshold. Methods: In a retrospective case–control study, we evaluated risk prediction performance in 180,398 women (161,849 of European ancestry; 18,549 of Asian ancestry). Odds ratios (ORs) from logistic regression models and the area under the receiver operating characteristic curve (AUC) were estimated. Results: PRS for invasive disease showed a stronger association in younger (<50 years) women (OR = 2.51, AUC = 0.622) than in women ≥ 50 years (OR = 2.06, AUC = 0.653) of European ancestry. PRS performance in Asians was lower (OR range = 1.62–1.64, AUC = 0.551–0.600). Gail performance was modest across groups and poor in younger Asian women (OR = 0.94–0.99, AUC = 0.523–0.533). Age interactions were observed for both PRS (p < 0.001) and Gail (p < 0.001) in Europeans, whereas in Asians, age interaction was observed only for Gail (invasive: p < 0.001; DCIS: p = 0.002). PRS identified more high-risk individuals than Gail in Asian populations, especially ≥50 years, while Gail identified more in Europeans. Overlap between PRS, Gail, and family history was limited at higher thresholds. Calibration analysis, comparing empirical and model-based ROC curves, showed divergence for both PRS and Gail (p < 0.001), which indicates miscalibration. In Europeans, family history and prior biopsies drove Gail discrimination. In younger Asians, age at first live birth was influential. Conclusions: PRS adds value to risk stratification beyond traditional tools, especially in younger women and Asian ancestry populations.

Abstract Purpose: To determine the relationship between germline pathogenic variants (PV) in cancer predisposition genes and the risk of ductal carcinoma in situ (DCIS). Experimental Design: Germline PV frequencies in breast cancer predisposition genes (ATM, BARD1, BRCA1, BRCA2, CDH1, CHEK2, PALB2, RAD51C, and RAD51D) were compared between DCIS cases and unaffected controls and between DCIS and invasive ductal breast cancer (IDC) cases from a clinical testing cohort (n = 9,887), a population-based cohort (n = 3,876), and the UK Biobank (n = 2,421). The risk of contralateral breast cancer (CBC) for DCIS cases with PV was estimated in the population-based cohort. Results: Germline PV were observed in 6.5% and 4.6% of women with DCIS in the clinical testing and population-based cohorts, respectively. BRCA1, BRCA2, and PALB2 PV frequencies were significantly lower among women with DCIS than those with IDC (clinical cohort: 2.8% vs. 5.7%; population-based cohort: 1.7% vs. 3.7%), whereas the PV frequencies for ATM and CHEK2 were similar. ATM, BRCA1, BRCA2, CHEK2, and PALB2 PV were significantly associated with an increased risk of DCIS (OR &gt; 2.0), but only BRCA2 PV were associated with high risk (OR &gt; 4) in both cohorts. The cumulative incidence of CBC among carriers of PV in high-penetrance genes with DCIS was 23% over 15 years. Conclusions: The enrichment of PV in ATM, BRCA1, BRCA2, CHEK2, and PALB2 among women with DCIS suggests that multigene panel testing may be appropriate for women with DCIS. Elevated risks of CBC in carriers of PV in high-penetrance genes with DCIS confirmed the utility of testing for surgical decision-making.

PURPOSE There is strong evidence that leisure-time physical activity is protective against postmenopausal breast cancer risk but the association with premenopausal breast cancer is less clear. The purpose of this study was to examine the association of physical activity with the risk of developing premenopausal breast cancer. METHODS We pooled individual-level data on self-reported leisure-time physical activity across 19 cohort studies comprising 547,601 premenopausal women, with 10,231 incident cases of breast cancer. Multivariable Cox regression was used to estimate hazard ratios (HRs) and 95% CIs for associations of leisure-time physical activity with breast cancer incidence. HRs for high versus low levels of activity were based on a comparison of risk at the 90th versus 10th percentiles of activity. We assessed the linearity of the relationship and examined subtype-specific associations and effect modification across strata of breast cancer risk factors, including adiposity. RESULTS Over a median 11.5 years of follow-up (IQR, 8.0-16.1 years), high versus low levels of leisure-time physical activity were associated with a 6% (HR, 0.94 [95% CI, 0.89 to 0.99]) and a 10% (HR, 0.90 [95% CI, 0.85 to 0.95]) reduction in breast cancer risk, before and after adjustment for BMI, respectively. Tests of nonlinearity suggested an approximately linear relationship ( Pnonlinearity = .94). The inverse association was particularly strong for human epidermal growth factor receptor 2–enriched breast cancer (HR, 0.57 [95% CI, 0.39 to 0.84]; Phet = .07). Associations did not vary significantly across strata of breast cancer risk factors, including subgroups of adiposity. CONCLUSION This large, pooled analysis of cohort studies adds to evidence that engagement in higher levels of leisure-time physical activity may lead to reduced premenopausal breast cancer risk.