Abstract PS3-02-16: Delays in breast cancer diagnosis and treatment in young women

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.

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Clinical Cancer Research
Published
2026-02-17
DOI
https://doi.org/10.1158/1557-3265.sabcs25-ps3-02-16
Primary Topic
Cancer Risks and Factors
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article

Abstract PS3-02-16: Delays in breast cancer diagnosis and treatment in young women

Y. Zheng, A. H. Partridge, G. J. Kirkner, K. J. Ruddy et al.
Clinical Cancer Research
Cancer Risks and Factors
article

Abstract PS3-02-16: Delays in breast cancer diagnosis and treatment in young women

Y. Zheng, A. H. Partridge, G. J. Kirkner, K. J. Ruddy, T. Sella, K. D. Brantley, V. F. Borges, L. Schapira, S. M. Rosenberg, S. E. Come, B. X. Zhang, J. Peppercorn
article en

Abstract

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.

Clinical Cancer ResearchVol. 32(4_Supplement)
Brigham and Women's Hospital (US), Beth Israel Deaconess Medical Center (US), Cornell University (US), Sheba Medical Center (IL), Massachusetts General Hospital (US), Dana-Farber Cancer Institute (US), Mayo Clinic in Arizona (US), University of Colorado Cancer Center (US), University of Colorado Denver (US), Stanford University (US)
Good health and well-being
Openalex Percentile: Top 46%
Cancer Risks and Factors
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