Geographic Variations in Demographics, Socioeconomic Status, and Stage at Diagnosis Among Hormone Receptor–positive Invasive Ductal Carcinoma: An NCDB Analysis (2004-2020)

Discussion

In this national cross-sectional analysis of more than 136,000 patients with HR+ IDC, substantial geographic heterogeneity was identified in demographic, SES, and stage distributions across U.S. regions. The Southeast and Southwest regions exhibited higher proportions of Black and Hispanic patients, lower median household income, greater uninsured rates, and higher prevalence of advanced-stage (stage III-IV) disease. Similarly, patients in the Midwest and Mountain regions demonstrated a higher prevalence of advanced-stage presentation, potentially caused by barriers related to geographic access and regional healthcare disparities. These findings align with prior analyses showing that socioeconomic disadvantage, rural residence, and limited healthcare infrastructure are associated with delayed diagnosis of BC (7, 8).

Conversely, patients in the Pacific region demonstrated greater socioeconomic advantage and the highest proportion of urban residency, which corresponded with a higher possibility of earlier-stage detection. A recent study by Huang et al. demonstrated that patients with better healthcare access, higher area-level education, and more prior screening mammography had 54% lower odds of advanced-stage BC diagnosis and a 36% lower hazard of BC-specific death. However, racial and ethnic disparities were not correlated with screening history in that cohort (9). There are also similar studies with different age groups of patients that highlighted that the prior screening programs are a major determinant of early detection (10, 11). These findings suggest that healthcare access, education, and participation in screening are critical drivers of earlier-stage presentation in BC. Geographic variation in mammography facility distribution, oncology providers’ availability, and insurance coverage may explain the regional disparity.

Beyond individual and behavioral factors, structural and healthcare-system determinants play a pivotal role in improving BC outcomes overall. Regional differences in mammography facility density, oncology provider distribution, and travel distance to care centers have been strongly associated with treatment adherence and early detection rates. Webster et al. identified pronounced geographic inequities, finding that areas with higher proportions of Black residents had substantially fewer mammography facilities, 68% fewer statewide and up to 89% fewer in New Castle County, Delaware (12). Similarly, Hashtarkhani et al. utilized machine learning and geospatial modeling to demonstrate that mammography facility density and availability were among the most influential predictors (10). Further, consuming nutrient-poor diets may contribute to poor BC outcomes, especially in dense low-SES patient areas and ethnic minority areas (13). Another multi-ethnic study found that neighborhood-level disadvantages, such as overcrowding or food insecurity, were significantly associated with screening adherence (14). Collectively, ensuring equitable geographic access rather than patient awareness alone remains a major factor in closing breast cancer disparities observed by race and rurality.

Future efforts to mitigate these regional and racial disparities should address the structural and policy barriers and integrate geographic data into predictive models of screening and diagnosis. Expanding insurance coverage, particularly through Medicaid expansion and affordability initiatives, has been linked to higher early-stage diagnosis rates, greater use of preventive services, and reduced cancer mortality. Randomized trials showed that patient navigation programs increase BC screening rates by up to 50% and improve the timeliness of diagnosis and treatment completion. Another, deploying mobile and geographically targeted screening programs can overcome access barriers. Removing financial barriers to advanced imaging modalities and integrating social-needs navigation to address transportation or food insecurity may enhance participation among socioeconomically vulnerable groups. Finally, integrating social determinants of health into national cancer surveillance systems will help health agencies to identify high-risk regions, optimize resource allocation, and monitor the real-world impact of these interventions.

Study limitations. The NCDB captures approximately 70% of newly diagnosed malignancies from CoC-accredited hospitals but does not include non-CoC facilities, which tend to be smaller, more rural, and underserved communities. Most of the non-CoC hospitals have fewer oncology resources, reduced access to screening programs, and greater socioeconomic barriers. As a result, patients may present with more advanced disease than those included in the NCDB. This exclusion may lead to underrepresentation of rural, low-income, uninsured, and minority populations and may underestimate the true magnitude of geographic disparities. The cross-sectional design limits our capacity to establish causality; temporal changes are not available, so survival or treatment outcomes were not assessed. Certain variables, including income and insurance, contained missing data, and geographic categorization was based on reporting facility location, which may not always reflect patients’ true residential environment. Additionally, temporal trends could be influenced by changes in diagnostic or reporting practices during the study period.