Zip-Code Level Disadvantage as a Predictor of Metastatic Breast Cancer at Diagnosis and Delayed Treatment Initiation.
Publication/Presentation Date
3-1-2026
Abstract
BACKGROUND: Metastatic breast cancer remains a significant public health issue, associated with worse outcomes and limited treatment options. While tumor biology influences disease progression, social and geographic disparities also contribute to late-stage diagnosis. The Distressed Communities Index (DCI), a zip-code level measure of economic hardship, captures structural disadvantage more comprehensively than traditional socioeconomic indicators. This study evaluates whether higher DCI scores are associated with metastatic stage and treatment delays, independent of clinical and demographic factors.
PATIENTS AND METHODS: We conducted a retrospective cohort study of women aged ≥ 18 years diagnosed or treated for in situ (DCIS) and invasive breast cancer (2018-2022) at a comprehensive cancer center. Zip codes were linked to DCI scores. Multinomial logistic regression, adjusted for age, race, ethnicity, insurance status, tumor subtype, and clinical palpable mass, assessed the association between DCI and cancer stage. Analysis of covariance compared time with treatment across DCI groups.
RESULTS: Among 2024 women (38% Black, 39% Hispanic), 76.8% resided in high DCI areas. High DCI was associated with twice the likelihood of metastatic disease at diagnosis compared with localized stage (ref: low DCI, aOR 2.16, 95% CI 2.00-2.34, p < 0.001) after adjustment. High DCI patients also experienced longer time to treatment initiation, including adjuvant chemotherapy (119 versus 137 days, p = 0.024), radiation (103 versus 133 days, p < 0.001), and surgery (71.2 versus 87.4 days, p < 0.001), after adjustment for stage.
CONCLUSIONS: Leveraging DCI may help identify high-risk zip codes and guide targeted screening to reduce disparities in outcomes.
Volume
33
Issue
3
First Page
2306
Last Page
2315
ISSN
1534-4681
Published In/Presented At
Parmar, P., Lin, J., Bhimani, F., Jao, L., Sheckley, M., Giron, A., Chen, Y., Jindani, R., Entenberg, D., Oktay, M., Ravetch, E., Gupta, A., Pastoriza, J., McEvoy, M., & Feldman, S. (2026). Zip-Code Level Disadvantage as a Predictor of Metastatic Breast Cancer at Diagnosis and Delayed Treatment Initiation. Annals of surgical oncology, 33(3), 2306–2315. https://doi.org/10.1245/s10434-025-18693-9
Disciplines
Medicine and Health Sciences
PubMedID
41326887
Department(s)
Fellows and Residents
Document Type
Article