Citations

BACKGROUND: Anthracyclines are a widely used and effective class of chemotherapy. However, a major limitation for their use is cardiotoxicity, manifesting as systolic dysfunction, congestive heart failure, and arrhythmias. The objective of this study was to identify genes and genetic risk variants for doxorubicin-induced arrhythmia. METHODS: We performed genome-wide association studies and meta-analysis across 2 independent nonoverlapping, genetically homogenous data sets from the Molecular Epidemiology Resource (cases N=77, controls N=1184) and Tapestry (cases N=13, controls N=172). Doxorubicin-related arrhythmia was the primary cardiac outcome, followed by investigation of a broader phenotype of cardiac events. Effects of doxorubicin on top-associated genes were assessed by quantitative polymerase chain reaction on RNA extracted from human cardiomyocytes following treatment with doxorubicin and by echocardiography in a zebrafish model of doxorubicin-induced cardiomyopathy. RESULTS: In the meta-analysis, rs12151014 at the KCTD15 locus was associated with doxorubicin-related arrhythmia at the genome-wide significance (minor allele frequency in Molecular Epidemiology Resource cases 0.195 versus 0.069 in controls; Tapestry cases 0.192 versus 0.079 in controls) P =9.01×10 −9 ; odds ratio, 3.61. MMP 16 rs1094199 was associated with the broader phenotype of arrhythmia and heart failure (minor allele frequency in Molecular Epidemiology Resource cases 0.079 versus 0.019 in controls; Tapestry cases 0.038 versus 0.015) P =1.98×10 − 8 ; odds ratio=6.15. In human cardiomyocytes, MMP16 and KCTD15 gene expression was significantly downregulated by doxorubicin, and in a zebrafish MMP16 knockout was protective of doxorubicin-induced decline in left ventricular ejection fraction. CONCLUSIONS: Genetic variants at KCTD15 and MMP16 are associated with doxorubicin-related arrhythmia and cardiac events. MMP16 is a potential cardioprotective therapeutic target.

Abstract Rationale Idiopathic Pulmonary Fibrosis (IPF) is characterized by chronic progressive pulmonary fibrosis and high mortality. Genetic markers, summarized into a polygenic risk score (PRS), associate with IPF in well-phenotyped research cohorts. Objectives To evaluate the performance of the PRS using real-world data from routinely captured electronic healthcare records. Methods We conducted an observational study evaluating the association of a PRS for IPF with electronic healthcare record diagnosis of IPF as well as lung transplant-free survival in four independent cohorts; the Mass General Brigham Biobank (MGBB), Mayo Clinic Biobank (MCBB), Mayo Clinic Tapestry Cohort (Tapestry), and U.K. Biobank (UKBB). We used multivariable logistic regression and multivariable Cox proportional hazards models adjusting for age, gender, and principal components of ancestry. The cohorts then underwent fixed and random effects meta-analysis. Measurements and Main Results Of 37,709; 44,195; 43,202; and 447,422 participants from MGBB, MCBB, Tapestry and UKBB respectively, 1,015 (2.7%) 2,879 (6.5%), 1,310 (3.0%), and 2,742 (0.6%) participants had an IPF diagnosis. Meta-analysis demonstrated a high-risk PRS associated with IPF diagnosis, OR 2.88 (95%CI 2.41-3.44) compared to all other individuals. A high-risk PRS also associated with the composite endpoint of mortality or lung transplant among those with an IPF diagnosis, HR 1.23(95%CI 1.11-1.35) compared to all other individuals. Conclusions A PRS can identify those at risk for an IPF diagnosis and mortality in biobank-scale data, which may have implications for clinical decisions. Further work is necessary to evaluate the utility of adding genetics in clinical settings.

ABSTRACT Background Alcohol intake is a modifiable risk factor for breast cancer, yet patterns of alcohol intake in women with breast cancer remain underexplored. This study evaluates demographic and clinical predictors of alcohol intake in patients with breast cancer. Methods Patients at Mayo Clinic Rochester diagnosed with breast cancer (Stage 0–3) between July 2014 to March 2022 were surveyed about their average alcohol intake over the 10 years prior to their diagnosis. Alcohol intake was categorized as < 1, 1–4, 5–14, and ≥ 15 drinks per week. Demographic, behavioral, and clinical data were analyzed using univariate Fisher exact tests and multivariate multinomial logistic regression. Results Of 2030 participants (mean age at diagnosis: 59 years; 99.3% female; 95.9% White), 29% consumed < 1 drink/week, 48% reported 1–4 drinks/week, 20% consumed 5–14 drinks/week, and 3% reported ≥ 15 drinks/week. Older age at diagnosis (≥ 60 years), non‐White race, financial difficulty, and never smoking were associated with less alcohol intake. Patients who reported higher levels of mild–moderate intensity exercise reported more alcohol intake. Tumor stage, tumor receptors, and BRCA mutation status were not associated with alcohol intake. PROMIS‐10 physical health scores correlated with alcohol intake in univariate but not multivariate models. Conclusion Alcohol intake is more common prior to a breast cancer diagnosis for patients who are younger, White, financially secure, exercising, and smoking. These findings may inform alcohol intake‐related breast cancer prevention efforts and highlight patient subgroups who could benefit from targeted counseling at the time of diagnosis.

e12697 Background: Postpartum-associated breast cancer (PABC) has been defined clinically as breast cancer (BC) diagnosed within the first 5 years of the most recent birth. Though generally rare, incidence rates are increasing in conjunction with delayed childbearing and older maternal age at first birth. Currently, there are limited data regarding serial patient-reported outcomes in this patient population compared to non-PABC patients. Methods: Patients with PABC from the Mayo Clinic Breast Disease Registry who completed baseline, 2, and 4-year surveys were matched 1:1 to BC patients whose cancers occurred more than 5 years after their most recent birth (or in the setting of nulliparity) based on age, clinical stage, treatment received, and tumor subtype. Survey results from the Patient Health Questionnaire-2 (PHQ-2), Patient-Reported Outcomes Measurement Information System-10 (PROMIS-10), and Impact of Event Scale-Revised (IES-R) collected at approximately two and four years after diagnosis were compared between PABC and non-PABC patients. Univariable analyses used Wilcoxon rank sum tests, whereas multivariable analyses employed linear regression models adjusting for potential confounding effects. Results: A total of 222 individuals were included (111 with PABC). A higher proportion of individuals in the PABC cohort were married compared to the non-PABC cohort (80% vs. 42%, p < 0.001); otherwise, the groups were well-balanced across multiple categories, including age, gender, race/ethnicity, menopausal status, and germline mutation status. In univariable analyses, the Year 2 composite PHQ-2 score was significantly worse among individuals with non-PABC (p = 0.04), and the non-PABC cohort reported greater difficulty with sleep (p = 0.03) as measured by IES-R at Year 4. Both associations attenuated in a multivariable analysis controlling for marital status. In marital status-adjusted analyses of Year 4 survey results, PABC participants reported greater difficulty in carrying out social activities but were less likely to report emotional distress as evaluated by PROMIS-10 (compared with non-PABC participants). No other variables were significant univariably or multivariably (p > 0.05). Conclusions: In general, quality of life is similar among survivors of PABC compared to those diagnosed with breast cancer outside the postpartum period (or when nulliparous). However, our findings reveal that individuals with PABC are less likely to experience emotional distress 2 and 4 years after the BC diagnosis, which is unexpected, given that postpartum patients typically report higher levels of distress compared to their non-postpartum counterparts. Further investigation into these findings is warranted.

8077 Background: Small cell lung cancer (SCLC) is an aggressive malignancy with poor prognosis. This study evaluates national trends in surgical management of early-stage SCLC using the National Cancer Database (NCDB), aiming to identify factors associated with improved outcomes and assess the survival benefit of surgical resection. Methods: Patients diagnosed with clinical stage T1–T3 N0 M0 SCLC between 2004 and 2022 were identified from the NCDB. Exclusions included non-SCLC histologies, advanced or missing staging, non-lobectomy surgeries, and incomplete survival data. Propensity score matching (1:1) was used to balance surgical and non-surgical cohorts based on demographic, clinical, and socioeconomic variables. Kaplan-Meier and Cox regression analyses were used to evaluate overall survival, stratified by T stage. Results: Among 17,762 patients with early-stage SCLC, 3,234 (18.2%) underwent lobectomy with mediastinal lymph node dissection. Surgical rates increased from 5% in 2004, 17% in 2013 to 24% in 2021. Surgery was more common in T1 (26.5%) than T2 (11.4%) or T3 (4.6%) disease. After matching, surgery was associated with improved survival across all T stages, with no significant interaction between T stage and surgical benefit (p=0.43). Older age, male sex, and higher comorbidity scores predicted worse outcomes. Among surgical patients, 2.3% received neoadjuvant therapy and 71.6% received adjuvant treatment. Systemic therapy-both neoadjuvant (HR 0.63) and adjuvant (HR 0.69)-was significantly associated with improved survival. Conclusions: Lobectomy remains underutilized in early-stage SCLC but is linked to significantly improved survival. Albeit small patient's number, neoadjuvant systemic therapy further enhanced survival, supporting broader use of surgery and multimodal treatment in appropriately selected patients Univariable results 1 Multivariable results 2 Characteristic No. deaths Person-months HR (95% CI) p-value HR (95% CI) p-value Charlson score <0.001 <0.001 0 761 77727 1.00 (ref) 1.00 (ref) 1 623 60483 1.06 (0.95,1.18) 1.07 (0.96,1.20) 2 or more 350 27025 1.30 (1.15,1.48) 1.30 (1.13,1.48) Clinical T-stage 0.011 0.014 cT1N0M0 1266 124916 1.00 (ref) 1.00 (ref) cT2N0M0 406 33924 1.18 (1.06,1.32) 1.20 (1.06,1.35) cT3N0M0 62 6393 0.96 (0.75,1.24) 1.00 (0.76,1.31) Residual disease <0.001 <0.001 No residual tumor 1626 158838 1.00 (ref) 1.00 (ref) Residual tumor 92 4699 1.91 (1.55,2.36) 1.91 (1.52,2.40) Neoadjuvant systemic treatment 0.253 0.034 No 1629 154116 1.00 (ref) 1.00 (ref) Yes 30 3495 0.81 (0.56,1.16) 0.63 (0.41,0.97) Adjuvant radiation 0.067 <0.001 No 1209 118925 1.00 (ref) 1.00 (ref) Yes 452 40471 1.11 (0.99,1.23) 1.33 (1.18,1.51) Adjuvant systemic treatment <0.001 <0.001 No 563 44045 1.00 (ref) 1.00 (ref) Yes 1096 113566 0.75 (0.68,0.83) 0.69 (0.62,0.78)

Abstract Rationale Asthma contributes substantially to healthcare burden and morbidity through frequent exacerbations. Emerging evidence suggests that genetic factors play a crucial role in modulating susceptibility to asthma exacerbations. To better understand the genetic architecture of exacerbations, we conducted a genome-wide association study (GWAS) in the Tapestry cohort. Methods The Tapestry Study, a large-scale, decentralized and clinical grade genomic sequencing study, conducted Exome+® sequencing at Helix, Inc. on 98,075 Mayo Clinic participants. After excluding patients with ≥10 pack-years of smoking and/or emphysema, we performed a GWAS of asthma exacerbations in 3,960 adults with asthma based on ICD codes. Cases (n = 1,059) were defined as individuals who experienced at least two exacerbations between 2020 and 2025; the remaining 2,901 individuals served as controls. Asthma exacerbations were defined by oral or systemic corticosteroid prescriptions with durations ranging from 3 days up to 28 days. Logistic regression models adjusted for age, sex, BMI, and the first six principal components of ancestry. Replication was performed in 1,273 asthma patients (439 African Americans and 834 non-Hispanic Whites) from the NHLBI-sponsored Severe Asthma Research Program (SARP 1-3), with adjustments for age, sex, BMI, and the first 10 principal components of ancestry. Results Based on a minor allele frequency (MAF) threshold of &gt; 0.05, we analyzed 5,256,135 genome-wide variants. Genome-wide significant associations for asthma exacerbations (p &lt; 5.0 × 10⁻8) included loci at a pseudogene in SMPD4P1 (rs680548, MAF = 0.39, OR = 1.37, p = 9.10 × 10⁻9). Additional variants showing suggestive associations included loci within ENDOD1 (rs638776, OR = 0.69, p = 1.20 × 10⁻6), PCSK2 (rs2206454, OR = 1.32, p = 3.53 × 10⁻6), RBFOX1 (rs17667084, OR = 0.60, p = 5.11 × 10⁻6), and CDC42EP3 (rs721660, OR = 1.29, p = 5.68 × 10⁻6). Subthreshold associations in Tapestry including loci at CDC42EP3 (rs4670213, OR = 1.27, p = 1.41x10-5, MAF = 0.36), and SDR39U1 (rs12587663,OR = 0.83, p = 5.86x10-4, MAF = 0.46) were replicated in the SARP longitudinal visit 5 with p-values of 8.523x10-3 (rs4670213, OR = 1.78), and 2.88x10-4 (rs12587663,OR=0.43), respectively. Conclusion Our GWAS for asthma exacerbations in the Tapestry cohort identified variant loci relevant to mitophagy mechanisms (CDC42EP3, PMID: 40783597), immune signaling and RNA splicing regulation (RBFOX1, PMID: 31301374), and neuromodulatory pathways (PCSK2, PMID: 32794589), all previously implicated in asthma pathophysiology. Collectively, these findings highlight potential novel genetic contributors to asthma exacerbations and provide a foundation for improving risk stratification and therapeutic targeting in asthma management. This abstract is funded by: This abstract is funded by: Mayo Clinic Funding: X01 from the NHLBI for TOPMed whole-genome sequencing and NIH grants R01 HL142992, HL69116, HL69167, HL69170, HL69174, U10 HL109164, U10 HL109257, U10 HL109146, U10 HL109172, U10 HL109250, U10 HL109250, U10 HL109250, U10 HL109168, U10 HL109152, U10 HL109086, U10 HL109046.

Objective: To compare 1-year changes in estimated 10-year and lifetime atherosclerotic cardiovascular disease (ASCVD) risk following metabolic and bariatric surgery (MBS) versus glucagon-like peptide-1 receptor agonist (GLP-1RA) therapy among adults with obesity. Summary Background Data: Obesity is a major driver of ASCVD through adverse metabolic and inflammatory pathways. Metabolic and bariatric surgery and GLP-1 receptor agonists represent the most effective contemporary treatments for obesity and are increasingly used to mitigate cardiovascular risk. However, their comparative effects on integrated short-term and lifetime ASCVD risk in real-world clinical practice remain incompletely characterized. Methods: We conducted a retrospective cohort study of adults with obesity (body mass index ≥30 kg/m²) who underwent MBS or initiated GLP-1RA therapy between 2020 and 2023 within a large tertiary health care system in the United States. Participants were identified from electronic health records and followed for 12 months. Primary outcomes were 1-year changes in estimated 10-year and lifetime ASCVD risk. Secondary outcomes included percent total body weight loss, blood pressure, and lipid parameters. Multivariable linear regression models were used to adjust for baseline body mass index and baseline ASCVD risk. Results: The final cohort included 812 patients, of whom 579 underwent MBS and 233 initiated GLP-1RA therapy. At baseline, patients receiving GLP-1RAs were older and had higher estimated ASCVD risk. At 1 year, reductions in 10-year ASCVD risk were similar between groups (−0.8% vs. −1.1%; P =.36). In contrast, lifetime ASCVD risk decreased significantly more following MBS than GLP-1RA therapy (−8.6% vs. −1.7%; P <.001). MBS was associated with greater percent total body weight loss (−27.8% vs. −11.1%; P <.001) and more favorable lipid changes, including larger reductions in low-density lipoprotein cholesterol and greater increases in high-density lipoprotein cholesterol. After adjustment, MBS remained independently associated with a greater reduction in lifetime ASCVD risk compared with GLP-1RA therapy (β −6.92; 95% CI −9.22 to −4.62). Conclusions: In this real-world cohort, both MBS and GLP-1RA therapy were associated with improvements in estimated cardiovascular risk, but MBS conferred substantially greater reductions in lifetime ASCVD risk, accompanied by superior weight loss and lipid improvements. These findings highlight the complementary roles of surgical and pharmacologic therapies in obesity management and may inform strategies to optimize long-term cardiovascular risk reduction.

Abstract Background: Smoking, a known risk factor for numerous cancers, negatively impacts long-term survival in breast cancer (BC) survivors (Parada H Jr et al., 2017; Pierce et al., 2019). This study aims to characterize baseline smoking behaviors among breast cancer patients who self-reported smoking during an initial survey. Objectives: To assess attributes of patients self-reporting as current smokers near BC diagnosis, examining demographics, habits, quality of life, cancer treatments, comorbidities, and finances. Methods: Patients with newly diagnosed BC seen at Mayo Clinic Rochester between 2014-2024 were invited to enroll in the Mayo Clinic Breast Disease Registry. Consenting participants who completed self-reported questionnaires at baseline were included in this study. Smoking status and related variables at the time of survey completion were assessed via a baseline questionnaire, classifying participants as current, former, or never smokers. Of 3,959 participants completing baseline surveys, 3,729 were analyzed after excluding 103 with missing smoking data and 127 with their baseline survey returned &gt;1-year post-diagnosis. Categorical variables were summarized with frequencies and percents, continuous variables with distributional statistics. Univariable associations with current smoking were assessed via two-sample t-tests (continuous) and chi-square or Fisher exact tests (categorical). Significant variables (p&lt;0.05) were included in a multivariable logistic regression model. Results: Among 3,729 BC patients (mean age 58.3 years, SD 12.9), 99.1% were female, 97.1% White, and 98.7% non-Hispanic. Only 2.7% reported financial difficulty, 56.4% had a bachelor's degree or higher, 81.7% were married or equivalent, and 21.7% consumed ≥5 alcoholic drinks/week. Tumor stage distribution was as follows: Stage 0 (13.9%), Stage 1 (43.9%), Stage 2 (28.9%), Stage 3 (8.9%), and Stage 4 (4.5%); 33.8% received chemotherapy, 56.5% radiotherapy, 63.6% endocrine therapy, and 42.2% underwent mastectomy. Current smokers (2.6%, n = 95) had a median diagnosis age of 59.1 (IQR 31.8-87.1),with 32.6% consuming ≥5 drinks/week (vs. 21.5% in non-smokers, univariable p = 0.012), 69.5% with less than a Bachelor’s degree (vs. 42.9%, p&lt;0.001), 9.6% facing financial difficulty (vs. 2.5%, p&lt;0.001), and 10.5% diagnosed within 270-365 days after survey return (vs. 4.2%, p = 0.022). Tumor stage showed 47% with Stage 1 (vs. 43.7%, p = 0.245); 33.7% received chemotherapy, 60.0% radiotherapy, and 58.9% endocrine therapy. Current smokers had a mean smoking initiation age of 19.9 (SD 6.2), smoked 12.5 cigarettes/day (SD 7.9) for 32.8 years (SD 14.1), with mean 22.3 pack-years (SD 17.2).Univariable associations of demographic and clinical characteristics with current smoking showed Compared to never or former smokers, current smokers at the time of survey took a longer time to return their baseline survey (p = 0.022), were more likely to consume five or more alcoholic drinks per week (p = 0.012), were more likely to have difficulty paying their bills (p&lt;0.001) and were less likely to obtain a Bachelor's degree or higher (p&lt;0.001). These associations remained significant after multivariable adjustment. Conclusion: Current smoking (2.6%) soon after a BC diagnosis was independently associated with delayed survey return, higher alcohol use, financial difficulty, and lower education. Assessing smoking status and referring patients to smoking cessation programs are critical for addressing these risk factors and improving health outcomes. These findings highlight distinct socioeconomic and behavioral profiles among current smokers, suggesting potential targets for tailored interventions. Citation Format: S. Hirani, R. A. Vierkant, N. L. Larson, S. D. D’Andre, F. J. Couch, J. E. Olson, K. J. Ruddy. Identifying Smoking-Related Factors in Breast Cancer Patients: Mayo Clinic Registry Insight [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 PS1-04-18.

Abstract Benign breast disease (BBD) confers elevated risk for breast cancer, yet current tools lack precision in identifying lesions likely to progress. Immune mechanisms may influence progression, but the spatial and molecular features of immune responses in BBD versus invasive cancer remain poorly characterized. We applied Digital Spatial Proteomics (DSP) to evaluate immune-related protein expression across 1,540 regions of interest (ROIs) from breast tumors (n=58, Carolina Breast Cancer Study [CBCS]), a UNC BBD cohort (n=20), and a Mayo BBD cohort (n=177). Using Consensus Clustering in CBCS and UNC BBD, we identified two stable immune phenotypes: “High Immune,” enriched in tumors and high-risk benign lesions, and “Quiet Immune,” predominant in low-risk BBD. ROIs were classified by immune marker expression, and patients were labeled as “High” if ≥50% of their ROIs were High Immune. In CBCS, High Immune profiles were associated with ER-negative status (OR=2.92 [0.99-8.65] participant-level; OR=3.28 [1.34-8.04] ROI-level). In BBD, High Immune profiles trended toward higher odds of high-risk lesions (OR=1.00 [0.15-6.70] participant-level; OR=1.68 [0.57-4.97] ROI-level), though this pattern was not replicated in the Mayo cohort. BBD samples exhibited substantial spatial heterogeneity in immune expression (40% within-patient ROI agreement vs. 74% in tumors), potentially limiting biomarker reliability. Nonetheless, four immune proteins (CD44, CD80, CD14, CD66b) were significantly associated with future cancer development in the Mayo cohort, though these findings require validation due to within-person variability. Our findings highlight the challenges posed by spatial heterogeneity in assessing immune biomarkers in BBD and suggest that immune activation may emerge later in disease progression. These results raise important questions about the timing and consistency of immune responses in the natural history of breast cancer. Citation Format: A. Zhang, A. Cozzo, L. Olsson, E. Kirk, X. Gao, S. Nyante, B. Calhoun, R. Vierkant, M. Sherman, M. Troester. Immune Heterogeneity in Breast Cancer Natural History: Benign Breast Disease to Breast Cancer [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 PS2-05-23.

Abstract Background: Artificial intelligence (AI) algorithms based on deep learning approaches show promise in improving breast cancer (BC) detection on mammography and may also improve prediction of future BC risk compared with clinical risk prediction models. Historical clinical risk prediction models underperform among women with BBD; however, AI models for BC detection on mammography have not been tested among women at elevated BC risk due to benign breast disease (BBD). We evaluated if an AI cancer detection algorithm can aid BC risk prediction among women with BBD. Methods: We examined women without a prior BC who had an initial BBD biopsy at Mayo Clinic, Rochester, between 2002 and 2013. Incident BC occurring after BBD was identified using the Mayo Tumor Registry and supplemented by follow-up questionnaires. Only women with a full field digital mammogram at least 2 years prior to BC diagnosis were eligible. A breast pathologist evaluated BBD according to increasing severity, as non-proliferative (NP), proliferative disease without atypia (PDWA) or atypical hyperplasia (AH). AI malignancy scores derived from the Transpara detection algorithm (1-10) and volumetric percent density (VPD) from Volpara (per one standard deviation, SD) were assessed from mammograms close to BBD diagnosis. Cox proportional hazards regression models were applied to estimate hazard ratios (HRs) with 95% Confidence Intervals (CIs), adjusted for age and BMI. C-statistics were estimated to assess the contribution of each factor to BC risk prediction. Likelihood ratio tests (LRTs) and bootstrapping methods were used to compare model performance with the addition of AI malignancy score. Results: The BBD cohort with mammography consisted of 3,125 women followed for a median 12.9 years, with 250 incident BC. Of these, 221 BC occurred at least two years after the mammogram and were used in analyses. As expected, increased BC risk was associated with BBD severity [for AH HR=3.18 (95%CI: 2.04, 4.95) and for PDWA HR=1.59 (95%CI: 1.17, 2.14) compared to NP] and with higher VPD [HR=1.24 per SD (95% CI: 1.05, 1.45)] (Table ). The AI-malignancy score alone was also associated with BC risk [HR=1.16 per 1 unit score (95%CI: 1.09,1.23)] and showed similar discriminatory accuracy [C-statistic=0.626 (95%CI: 0.586, 0.665)] as the model with BBD severity and VPD combined [C-statistic=0.627, (95%CI: 0.585, 0.669)] (Table ). In models with BBD severity and VPD, the AI-malignancy score was an independent risk factor for BC [HR=1.14 (95%CI: 1.07, 1.21); PLRT&lt;0.001] but only achieved a marginally significant improvement in discriminatory accuracy [C-statistic=0.651 (0.609, 0.693), ΔC-statistic=0.024 (95% CI: 0.000, 0.047)]. Conclusion: In this preliminary study, an AI BC detection algorithm achieved similar performance in predicting future BC risk compared to established risk factors. Citation Format: C. M. Vachon, S. Winham, M. Jensen, D. Hursh, L. Pacheco-Spann, A. Norman, J. Fischer, S. Schrup, L. Seymour, D. Gehling, S. Nyante, M. Troester, N. Karssemeijer, R. Vierkant, D. Radisky, C. Scott, S. I. Maimone, A. Degnim, M. Sherman. An AI algorithm for breast cancer detection improves future BC risk prediction among women with benign breast disease [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 PD4-02.