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.

Abstract Background: Women younger than 40 generally fall outside the routine screening population for breast cancer (BC). We aimed to understand factors influencing diagnosis and treatment delays in these patients, and the impact of delays on disease-free survival (DFS). Methods: We included women aged ≤ 40 years at diagnosis of stage 0-IV BC enrolled in the Young Women’s BC Study from 2006-2016. Sociodemographics, initial BC symptoms, and disease status were collected via annual surveys. Medical record review was used to capture tumor characteristics and recurrence status. We used logistic regression to estimate associations between patient and tumor factors and three delay types: (1) self-delay (≥ 90 days from first symptom to presentation to a provider), (2) diagnosis delay (≥ 90 days from healthcare visit to diagnosis), and (3) treatment delay (≥ 60 days from diagnosis to first treatment). Odds ratios (OR) and 95 % confidence intervals (CI) were estimated in multivariable models after choosing factors via backwards selection (p≤0.05 retained). Hazard ratios (HR) and 95% CIs for the association between delays and DFS, overall and by stage, were estimated via Cox proportional hazard models, adjusted for tumor and treatment factors. Time to event was measured from diagnosis or treatment to recurrence, death, or last follow-up, whichever occurred first. Results: Of 1,297 patients, 1,071 who completed the long-form baseline survey were included. Median time from first symptom to presentation was 14 days (interquartile range (IQR)=2-45), presentation to diagnosis was 14 days (IQR=7-30), and diagnosis to treatment was 41 days (IQR=25-57). Overall, 14% (n=153) had a self-delay and 11% (n=120) had a diagnosis delay. Of 839 patients with self-detected tumors, 18% had a self-delay and 13% had a diagnosis delay. Among those with Stage 1-3 BC (N=928), 22% (n=205) had a treatment delay. In univariable models, income <50K (p=0.01), lower financial comfort (p=0.01), and not living with a partner (p=0.03) were associated with higher odds of self-delay, while pregnancy within 1 year pre-diagnosis (p=0.05) and first-degree family history of any cancer (p=0.04) or BC (p=0.03) were associated with lower odds. Self-delays were more likely for women diagnosed with stage 4 BC (p=0.004) or with HER2+ tumors (p=0.03) and less likely for those with triple negative (TN) BC (p<0.001). In the multivariable model, family history of BC (OR=0.40, 95% CI=0.17-0.80), income <50K (OR=1.97, 95% CI=1.22-3.13) and TN subtype (OR v. luminal A=0.30, 95% CI=0.13-0.60) remained associated. Odds of diagnosis delay were higher among women who were younger (p=0.01) or with Stage 4 BC (p=0.004), and lower for those with luminal B (p=0.04), TN (p=0.01), or high grade tumors (p=0.03). In the multivariable model, younger age (OR per 1-year=0.94, 95% CI=0.89-0.99), and subtype (luminal B v. A OR=0.60, 95% CI=0.38-0.95; TN v. luminal A OR=0.35, 95% CI=0.16-0.70) remained associated. Multivariable models for self-and diagnosis delays remained similar when restricted to self-detected patients.Treatment delays were less likely among unemployed individuals (p=0.001), and women with a positive germline BC risk variant (p=0.002), luminal B (p=0.005) or TN (p<0.001) subtypes, and high-grade tumors (p=0.03). Only tumor factors remained significant in the multivariable model, including subtype (luminal B v. A OR=0.59, 95% CI=0.41-0.86, TN v. luminal A OR=0.25, 95% CI=0.13-0.43), and stage (stage 3 v. 1 OR=0.37, 95% CI=0.20-0.65). Overall and by stage at diagnosis, delays were not statistically significantly associated with DFS before or after adjusting for tumor and treatment factors. Conclusions: Delays in breast cancer care are influenced by multiple psychosocial and clinical factors, and disparities exist by socioeconomic status. It is critical to decrease self- and diagnosis delays to prevent stage 4 breast cancer. Citation Format: B. X. Zhang, T. Sella, Y. Zheng, G. J. Kirkner, K. J. Ruddy, S. M. Rosenberg, V. F. Borges, L. Schapira, S. E. Come, J. Peppercorn, A. H. Partridge, K. D. Brantley. Delays in breast cancer diagnosis and treatment in young women [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS3-02-16.

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.

Importance Inherited pathogenic variants (PVs) in known predisposition genes can greatly increase breast cancer risk, but the combined impact of PV status, family history, and other factors on breast cancer risk in the general US population has not been well described. Objective To evaluate population-based breast cancer risk estimates for those with established PVs overall and stratified by first-degree family history of breast cancer and other factors. Design, Setting, and Participants This study used pooled data from 13 US-based breast cancer case-control studies participating in the Cancer Risk Estimates Related to Susceptibility (CARRIERS) consortium. Enrollment for individual studies occurred between 1976 and 2013, and results are based on data released March 2023, with analyses conducted from June 2022 to July 2025. Exposures PVs, breast cancer family history, self-reported race and ethnicity, and established risk factors. Main Outcomes and Measures Breast cancer rate ratios for PVs in 7 genes were estimated from the CARRIERS consortium. PV status and incidence and mortality statistics were combined using the Individualized Coherent Absolute Risk Estimation (iCARE) model to estimate conditional cumulative breast cancer risks and 95% CIs, stratified by family history and standardized to the US population. Models that incorporated population-based data and published estimates for established epidemiologic risk factors were also evaluated. Results A total of 67 692 women were studied, including 33 841 who were diagnosed with breast cancer. PVs in ATM , BRCA1 , BRCA2 , CHEK2 , and PALB2 were strongly associated with breast cancer risk, with BRCA1 and PALB2 PVs showing evidence of heterogeneity by family history. In models considering PVs, family history, and established risk factors, the estimated cumulative risks of breast cancer by age 50 years ranged from 2.4% (95% CI, 2.4-2.4) in women with no PVs and no family history to 35.5% (95% CI, 21.6-55.1) in PALB2 PV carriers with a family history. Among women who have not been diagnosed with breast cancer by age 50 years, the cumulative risk of breast cancer by age 80 years ranged from 11.1% (95% CI, 11.0-11.2) in noncarriers with no family history to 70.5% (95% CI, 52.8-83.5) for PALB2 carriers with a family history. PV-specific cumulative risk estimates varied across subgroups defined by race and ethnicity and potentially modifiable epidemiologic risk factors. Conclusions and Relevance In this study, population-based estimates of cumulative breast cancer risk for established PVs, as informed by the CARRIERS case-control sample, varied by family history and potentially modifiable risk factors. These estimates provide guidance for identifying individuals who will most benefit from enhanced screening and prevention strategies.

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.

Abstract Adolescent and young adults (AYAs) (15-39 years) have a heightened risk of developing a second primary malignancy due to extended periods of survivorship, higher incidence of germline cancer predisposing variants, and increased susceptibility to treatment-induced malignancies. Research on survivors of specific AYA cancer types, including breast cancer (BC) survivors, is limited. Among BC survivors, while much survivorship research focuses on risk of locoregional recurrence or contralateral BC, little is known about overall risk, and risk factors, of developing second non-breast primaries. This prospective cohort study examined women diagnosed with BC from 2006-2016 at age ≤40 years enrolled in the Young Women’s BC Study (YWS) (N=1297). Women were excluded from the analytic cohort if initially diagnosed with Stage IV breast cancer (N=64). To enable investigation of how BC treatments may impact second primary risk, women were also excluded if they reported another cancer before primary BC diagnosis (N=3). Patient characteristics, treatment information, and clinical events were collected via serial surveys. Tumor characteristics and detailed treatment data were obtained from medical record review. Five- and 10-year risk of second non-breast primary was estimated via the cumulative incidence function after applying the Fine-Gray competing risks model with time starting at primary BC diagnosis. Death, metastasis, or diagnosis with a second primary BC were considered as competing events. Univariate and multivariate Fine-Gray sub-distribution models were used to estimate sub-distribution hazard ratios (sHRs) and 95% confidence intervals (CI) for second non-breast primary cancer risk. Risk factors considered included age, race, body mass index, smoking, alcohol use, income, family history of cancer, germline pathogenic variant (PV) carrier status, tumor stage, grade, and ER status, primary surgery type, and receipt of radiation, chemotherapy, or endocrine therapy (yes/no). Multivariate models tested individual associations with additional adjustment for radiation therapy and PV carrier status, as both are consistently associated with second primary in the literature. Over a median follow-up of 10.1 years (inter-quartile range (IQR) =7.9-12.1 y), 47 patients (4%) developed a second non-breast primary cancer. Median age at second non-breast primary was 43 years (IQR=39-46), and median time between primary BC and second non-breast primary was 7.3 years (IQR=4.1-9.3). Second primary types included melanoma (n=10), thyroid (n=10), ovarian (n=4), sarcoma (n=4), uterine (n=3), rectal (n=3), bladder (n=2), cervical (n=2), head and neck (n=2), lung (n=2), lymphoma (n=2), pancreatic (n=2), and kidney (n=1). During the study, 22 patients (2%) developed a second primary BC, 167 (19%) developed metastasis, and 15 (1%) died from causes other than BC. Among the patients who developed a second primary BC, two later developed another non-breast cancer (ovarian and brain cancer). When incorporating competing risks, five and 10-year cumulative incidence of second non-breast primary was 1.4% and 3.2%, respectively. No patient or treatment factors were statistically significantly associated with second non-breast primary in univariate or multivariate models, including radiation and PV carrier status. In this population of young BC survivors, 10-year cumulative incidence of second non-breast primary cancer was 3.2%, with the most common second cancers being melanoma and thyroid cancer. Incidence rates of all second primary cancer types in this cohort were higher than population-based incidence rates for healthy women under 50 years of age, highlighting the importance of long-term surveillance for other cancer events in this young population. While risk of second non-breast primary was not associated with primary BC treatment in this study, cases were limited, and the follow-up interval was relatively short. Citation Format: Bessie Zhang, Kristen Brantley, Shoshana Rosenberg, Gregory Kirkner, Laura Collins, Kathryn Ruddy, Rulla Tamimi, Lidia Schapira, Virginia Borges, Ellen Warner, Steven Come, Eric Winer, Ann Partridge. Second primary non-breast cancers in young breast cancer survivors [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-11-10.

Importance Among women diagnosed with primary breast cancer (BC) at or younger than age 40 years, prior data suggest that their risk of a second primary BC (SPBC) is higher than that of women who are older when they develop a first primary BC. Objective To estimate cumulative incidence and characterize risk factors of SPBC among young patients with BC. Design, Setting, and Participants Participants were enrolled in the Young Women’s Breast Cancer Study, a prospective study of 1297 women aged 40 years or younger who were diagnosed with stage 0 to III BC from August 2006 to June 2015. Demographic, genetic testing, treatment, and outcome data were collected by patient surveys and medical record review. A time-to-event analysis was used to account for competing risks when determining cumulative incidence of SPBC, and Fine-Gray subdistribution hazard models were used to evaluate associations between clinical factors and SPBC risk. Data were analyzed from January to May 2023. Main Outcomes and Measures The 5- and 10- year cumulative incidence of SPBC. Results In all, 685 women with stage 0 to III BC (mean [SD] age at primary BC diagnosis, 36 [4] years) who underwent unilateral mastectomy or lumpectomy as the primary surgery for BC were included in the analysis. Over a median (IQR) follow-up of 10.0 (7.4-12.1) years, 17 patients (2.5%) developed an SPBC; 2 of these patients had cancer in the ipsilateral breast after lumpectomy. The median (IQR) time from primary BC diagnosis to SPBC was 4.2 (3.3-5.6) years. Among 577 women who underwent genetic testing, the 10-year risk of SPBC was 2.2% for women who did not carry a pathogenic variant (12 of 544) and 8.9% for carriers of a pathogenic variant (3 of 33). In multivariate analyses, the risk of SPBC was higher among PV carriers vs noncarriers (subdistribution hazard ratio [sHR], 5.27; 95% CI, 1.43-19.43) and women with primary in situ BC vs invasive BC (sHR, 5.61; 95% CI, 1.52-20.70). Conclusions Findings of this cohort study suggest that young BC survivors without a germline pathogenic variant have a low risk of developing a SPBC in the first 10 years after diagnosis. Findings from germline genetic testing may inform treatment decision-making and follow-up care considerations in this population.

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.

10503 Background: Prior data suggests that the risk of second primary breast cancer (SPBC) is higher among women diagnosed with primary breast cancer (BC) before age 40. There is evidence that risk differs by primary tumor characteristics, cancer treatments, and genetic predisposition. However, studies investigating risk of SPBC by clinical risk factors are often limited by low numbers of young women and lack of complete patient data, particularly regarding germline genetic risk. Methods: Using the Young Women’s BC Study (YWS), a prospective cohort of 1,302 women ≤40 years diagnosed with BC from 2006-2016, we sought to compare clinical and treatment characteristics among women who developed an SPBC vs. those who did not. The analytic cohort included women diagnosed with Stage 0-III BC who did not undergo bilateral mastectomy (N = 685). Demographics, genetic testing and results, clinical events, and treatment data were collected through self-report on baseline and follow-up surveys (every 6 months for 3 years, then annually). Detailed tumor and treatment information, confirmation of genetic testing results, and new and recurrent cancer events were obtained through regular and triggered medical record review. Univariate and multivariate Cox proportional hazards models were used to examine associations of age, race, genetic testing results, hormone receptor status, stage, and grade of primary tumor, and cancer treatments with SPBC. Participants were censored at the time of local recurrence, metastasis, death, or loss of follow-up. Results: At a median follow-up time of 9.9 years [inter-quartile range (IQR) = 6.6-12.0 y], 17 patients developed an SPBC (2.5%), in whom 3 occurred in the ipsilateral breast after lumpectomy as primary BC surgery. Median time from primary BC diagnosis to SPBC diagnosis was 4.2 years (IQR = 3.3-5.6 y). Compared to those who did not develop an SPBC, a greater percentage of women who developed an SPBC had in situ disease as their primary BC (24% v. 6%) and were of Ashkenazi descent (12% v. 5%). In the 577 women who had had genetic testing, 544 (94%) were non-carriers of pathogenic variants. Risk of SPBC was 2.2% (N = 12) in non-carriers and 9.1% (N = 3) in the 33 carriers. In Cox univariate analyses, carriers had a 4.1 times higher risk of SPBC compared to non-carriers (HR = 4.14, 95% confidence interval (CI) = 1.67-14.66, p = 0.03), and primary diagnosis with in situ BC was associated with a 5-fold increased risk of SPBC (HR = 5.02, 95% CI = 1.63-15.41, p = 0.005). Both factors remained strongly associated with SPBC when tested together in a multivariate model. Conclusions: This prospective study demonstrated a low risk of SPBC in the first 10 years after diagnosis of early BC in young women who are not germline pathogenic variant carriers. The finding that risk of SPBC was higher after in situ primary BC at a young age warrants further investigation. These findings have important implications for the treatment and follow-up care of young women with BC.

Abstract Background: Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. Methods: We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values<5x10-8 as genome-wide significant, and p-values<1x10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants.Results: None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values<1x105. The strongest evidence was found for rs4674019 (p-value=2.27x10-7), which showed genome-wide significant interaction (p-value=3.8x10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. Conclusions: In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT–breast cancer risk association.