Ruddy, K. J.

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.

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 >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<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<0.001), 9.6% facing financial difficulty (vs. 2.5%, p<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<0.001) and were less likely to obtain a Bachelor's degree or higher (p<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.