Cross-sectional analysis of skin cancer stages reveals regional differences in diagnosis and socioeconomic factors.
Background/Aim: Skin cancer is the most common malignancy in the United States; however, regional variation in patient demographics, socioeconomic factors, and stage at diagnosis remains incompletely characterized. Defining these disparities is essential to inform targeted prevention and early detection strategies. Patients and Methods: We performed a cross-sectional analysis of the National Cancer Database (NCDB), including patients diagnosed with skin cancer between 2004 and 2020. Patients were stratified into six United |States geographic regions based on reporting facility location. Demographic, socioeconomic, and clinical variables, including age, sex, race and ethnicity, insurance status, income, urban-rural residence, and American Joint Committee on Cancer (AJCC) stage, were analyzed descriptively. Results: Among 1,048,575 patients (mean age, 70.8 years; 60.3% male), notable regional differences were observed. White patients were 92.5% of the cohort, with the highest representation in the Mountain region (96.2%), whereas Black patients were most prevalent in the Southeast (8.6%). Socioeconomic disparities varied by region; uninsured rates were highest in the Southwest (3.2%) and Southeast (2.1%), while lower-income households predominated in these regions (81.4% and 71.8%). In contrast, higher-income patients were most common in the Northeast (54.7%). The proportion of advanced-stage (III-IV) disease was highest in the Mountain (29.9%) and Pacific (27.6%) regions and lowest in the Midwest (22.0%). Conclusion: Geographic disparities in socioeconomic conditions and healthcare access are associated with variation in stage at diagnosis among patients with skin cancer. These findings highlight the role of structural barriers in delayed presentation and support the need for targeted interventions, including improved insurance coverage, expanded access to dermatologic care, and enhanced early detection strategies, to improve equity in outcomes.
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DEMIRORS et al. (2026) studied this question.
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