Abstract PS1-04-28: Treatment Cascade Disruption in Breast Cancer: Socioeconomic Predictors of Sequential Delays in a Southeast Texas Cohort

Abstract Background: Sequential, timely delivery of multimodal treatment is essential to optimal outcomes in breast cancer. The majority of previous studies determine delays in treatment in isolation, without including disruptions across the entire treatment cascade (surgery → chemotherapy → radiation → hormone/immunotherapy). This study examines socioeconomic predictors of sequential and cumulative delays in the treatment of breast cancer. Methods: We conducted a retrospective cohort study on registry data from 609 breast cancer patients treated between 2018 and 2023 at a Southeast Texas multi-hospital system. Delay was classified as determined by modality-specific time thresholds as defined. Patients were classified as having 0, 1, 2, 3, or ≥4 modality delays. Logistic regression examined associations with demographic, insurance, and tumor characteristics. Results: 53% of patients experienced one or more modality delays; 19% had ≥2 modality delays. Medicaid insurance (OR: 2.89, 95% CI: 1.70-4.92), age <50 (OR: 2.15, CI: 1.30-3.54), and unmarried status (OR: 1.76, CI: 1.22-2.54) were independent predictors of cumulative delay. Triple-negative patients (subset analysis, n = 98) with ≥2 delays had higher stage progression rates than on-time-treated counterparts (p = 0.03). Cascade analysis showed the greatest drop-off rate was after surgery (not initiating adjuvant chemotherapy or radiation). Conclusion: Delays in breast cancer care are not isolated events. Medicaid status, younger age, and social isolation are predictors of cumulative care disruption. Interventions must address continuity of all treatment cascade steps, especially among socioeconomically disadvantaged groups. Citation Format: N. Ganatra, A. Jamal, P. Jain, J. Doshi, S. Patel. Treatment Cascade Disruption in Breast Cancer: Socioeconomic Predictors of Sequential Delays in a Southeast Texas Cohort [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 PS1-04-28.

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Journal
Clinical Cancer Research
Published
2026-02-17
DOI
https://doi.org/10.1158/1557-3265.sabcs25-ps1-04-28
Primary Topic
Economic and Financial Impacts of Cancer
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article
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article

Abstract PS1-04-28: Treatment Cascade Disruption in Breast Cancer: Socioeconomic Predictors of Sequential Delays in a Southeast Texas Cohort

Nency Ganatra, Pragya Jain, Abdullah Jamal, S. Patel et al.
Clinical Cancer Research
Economic and Financial Impacts of Cancer
article

Abstract PS1-04-28: Treatment Cascade Disruption in Breast Cancer: Socioeconomic Predictors of Sequential Delays in a Southeast Texas Cohort

Nency Ganatra, Pragya Jain, Abdullah Jamal, S. Patel, J. Doshi
article en

Abstract

Abstract Background: Sequential, timely delivery of multimodal treatment is essential to optimal outcomes in breast cancer. The majority of previous studies determine delays in treatment in isolation, without including disruptions across the entire treatment cascade (surgery → chemotherapy → radiation → hormone/immunotherapy). This study examines socioeconomic predictors of sequential and cumulative delays in the treatment of breast cancer. Methods: We conducted a retrospective cohort study on registry data from 609 breast cancer patients treated between 2018 and 2023 at a Southeast Texas multi-hospital system. Delay was classified as determined by modality-specific time thresholds as defined. Patients were classified as having 0, 1, 2, 3, or ≥4 modality delays. Logistic regression examined associations with demographic, insurance, and tumor characteristics. Results: 53% of patients experienced one or more modality delays; 19% had ≥2 modality delays. Medicaid insurance (OR: 2.89, 95% CI: 1.70-4.92), age <50 (OR: 2.15, CI: 1.30-3.54), and unmarried status (OR: 1.76, CI: 1.22-2.54) were independent predictors of cumulative delay. Triple-negative patients (subset analysis, n = 98) with ≥2 delays had higher stage progression rates than on-time-treated counterparts (p = 0.03). Cascade analysis showed the greatest drop-off rate was after surgery (not initiating adjuvant chemotherapy or radiation). Conclusion: Delays in breast cancer care are not isolated events. Medicaid status, younger age, and social isolation are predictors of cumulative care disruption. Interventions must address continuity of all treatment cascade steps, especially among socioeconomically disadvantaged groups. Citation Format: N. Ganatra, A. Jamal, P. Jain, J. Doshi, S. Patel. Treatment Cascade Disruption in Breast Cancer: Socioeconomic Predictors of Sequential Delays in a Southeast Texas Cohort [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 PS1-04-28.

Clinical Cancer ResearchVol. 32(4_Supplement)
Northeast Baptist Hospital (US)
Openalex Percentile: Top 57%
Economic and Financial Impacts of Cancer
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