e22595 Background: Cervical cancer remains a preventable cause of morbidity and mortality in the United States, with available vaccination and screening modalities. However, nationally, disparities in outcomes persist across racial and socioeconomic groups. In Wisconsin, these disparities have been insufficiently characterized. Detailed local data is needed to inform policy, planning, and targeted intervention. As such, our study aims to evaluate cervical cancer metrics across race, ethnicity, socioeconomic indicators, and geography using statewide registry data. Methods: Our study utilizes Wisconsin Cancer Reporting System (WCRS) data from 2014–2021. Descriptive statistics summarized demographics and clinical characteristics. Age-adjusted statewide incidence rates were calculated. Cox proportional hazards models examined predictors of cervical cancer survival. Neighborhood-level poverty (American Community Survey) and Rural-Urban Community codes (United States Department of Agriculture) were linked using patient census tract data. Adaptive spatial filtering was used to map geographic variation in cervical cancer incidence across Wisconsin. Results: A total of 1,429 cases were identified in Wisconsin from 2014–2021. Incidence was highest among Black (80.1) and Hispanic (73.0) women, compared with White women (45.7 per 100,000). The median age at diagnosis was 50 years, with Hispanic patients diagnosed at a younger median age of 43 years. Black patients resided in tracts with higher mean poverty (24.9%) than white (8.4%) patients. In Cox models, patients insured primarily by Medicaid (HR = 1.71, p = 0.005) and Medicare (HR = 2.34, p < 0.001) succumbed to cervical cancer earlier than those privately insured. Spatial analyses demonstrated elevated incidence in southern urban areas and northeastern regions of Wisconsin. Conclusions: Marked disparities in cervical cancer incidence and survival persist in Wisconsin. These findings underscore the need for targeted screening, early detection, and care navigation efforts to improve outcomes across populations.
Shah et al. (Thu,) studied this question.