What question did this study set out to answer?

February 19, 2026Clinical Cancer Research0 citations

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

NGNency GanatraSaint Thomas Midtown Hospital AJAbdullah JamalNortheast Baptist Hospital PJPragya JainMedical College of Wisconsin

Key Points

To identify socioeconomic predictors of sequential and cumulative delays in the breast cancer treatment cascade.
Conducted a retrospective cohort study using registry data from 609 breast cancer patients treated between 2018 and 2023.
Classified delays based on modality-specific time thresholds.
Used logistic regression to examine associations with demographic, insurance, and tumor characteristics.
53% of patients experienced one or more modality delays; 19% had ≥2 delays.
Medicaid insurance, age <50, and unmarried status were independent predictors of cumulative delay.
Triple-negative patients with ≥2 delays had higher stage progression rates compared to those treated on-time.

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.

Demander à l'IA

Bookmark

View Full Paper