Document Type
Article
Publication Date
1-1-2021
Description
Context: Colorectal cancer (CRC) surgical treatment delay (TD) has been associated with mortality and morbidity; however, disparities by TD profiles are unknown. Objectives: This study aimed to identify CRC patient profiles of surgical TD while accounting for differences in sociodemographic, health insurance, and geographic characteristics. Design: We used latent class analysis (LCA) on 2005-2015 Tennessee Cancer Registry data of CRC patients and observed indicators that included sex/gender, age at diagnosis, marital status (single/married/divorced/widowed), race (White/Black/other), health insurance type, and geographic residence (non-Appalachian/Appalachian). Setting: The state of Tennessee in the United States that included both Appalachian and non-Appalachian counties. Participants: Adult (18 years or older) CRC patients (N = 35 412) who were diagnosed and surgically treated for in situ (n = 1286) and malignant CRC (n = 34 126). Main Outcome Measure: The distal outcome of TD was categorized as 30 days or less and more than 30 days from diagnosis to surgical treatment. Results: Our LCA identified a 4-class solution and a 3-class solution for in situ and malignant profiles, respectively. The highest in situ CRC patient risk profile was female, White, aged 75 to 84 years, widowed, and used public health insurance when compared with respective profiles. The highest malignant CRC patient risk profile was male, Black, both single/never married and divorced/separated, resided in non-Appalachian county, and used public health insurance when compared with respective profiles. The highest risk profiles of in situ and malignant patients had a TD likelihood of 19.3% and 29.4%, respectively. Conclusions: While our findings are not meant for diagnostic purposes, we found that Blacks had lower TD with in situ CRC. The opposite was found in the malignant profiles where Blacks had the highest TD. Although TD is not a definitive marker of survival, we observed that non-Appalachian underserved/underrepresented groups were overrepresented in the highest TD profiles. The observed disparities could be indicative of intervenable risk.
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This work is licensed under a Creative Commons Attribution 4.0 International License.
Citation Information
Ishino, Francisco A. M.; Odame, Emmanuel A.; Villalobos, Kevin; Whiteside, Martin; Mamudu, Hadii; and Williams, Faustine. 2021. Applying Latent Class Analysis on Cancer Registry Data to Identify and Compare Health Disparity Profiles in Colorectal Cancer Surgical Treatment Delay. Journal of Public Health Management and Practice. https://doi.org/10.1097/PHH.0000000000001341 ISSN: 1078-4659
Copyright Statement
This article is open access.