Cervical cancer geographical burden analyzer: An interactive, open-access tool for understanding geographical disease burden in patients with recurrent or metastatic cervical cancer

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Gynecologic Oncology


Objective: Cervical cancer (CC) disproportionately affects women based on socioeconomic status and racial/ethnic background. There is limited research in quantifying and visualizing whether substantial geographical disparities in the US exist with respect to CC burden, and especially with respect to recurrent or metastatic CC (r/mCC) disease burden. Identifying regions with higher r/mCC burden may help inform effective healthcare resource allocation and navigating patients to appropriate care. Methods: We conducted a retrospective analysis of the 2015–2020 MarketScan® Commercial and Supplemental Medicare claims data; r/mCC burden was estimated as the number of patients initiating r/mCC systemic therapy over CC-diagnosed patients for each of the 410 metropolitan statistical areas (MSAs) considered. We developed a public, web-based tool, the Cervical Cancer Geographical Disease Burden Analyzer (Cervical Cancer Geo-Analyzer, http://www.geo-analyzer.org), that allows users to visualize r/mCC burden across MSAs over multiple years. Results: There was considerable variation in r/mCC burden across MSAs, with a range of 0–83.3%. Burden increased in Boston-Cambridge-Newton, MA (r/mCC to CC ratio: 41% in 2018 to 50% in 2020), and Sacramento-Roseville-Arden-Arcade, CA (33% in 2018 to 50% in 2020). On the other hand, while r/mCC burden remained high, it decreased in Grand Rapids, MI (55% in 2018 to 31% in 2020) and San Francisco-Oakland-Hayward, CA (40% in 2018 to 26% in 2020). There were regions with sparse or no data, suggesting a need for more representative data capture. Conclusion: The Cervical Geo-Analyzer is a tool to visualize areas with high need for CC interventions. It also builds the foundation for further work to understand local risk factors of disease burden, identify populations of interest, characterize health disparities of CC or r/mCC and inform targeted interventions.

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