Abstract 4337: Identifying risk subgroups of invasive prostate cancer surgical delay using a person-centered approach: The constellation of health determinants using latent class analysis on cancer registry data
Authors: Ishino Francisco Alejandro Montiel , Liu Xiaohui , Salmeron Bonita , Das Rina , Williams Faustine 
Published: September 2020

Abstract
Our purpose was to examine the constellation of health determinants in prostate cancer (PCa) surgical treatment delay using a person-centered approach. PCa is the most common and the second leading cause of death among men in the US. Black men are more likely to have advanced disease, and more than twice as likely to die of PCa than white men. Causes for these disparities are complex and involve multiple determinants of health. Our hypothesis was surgical delay may increase the likelihood of recurrence of disease, influence quality of life and survival in blacks. Methods: We used latent class analysis (LCA), a person-centered methodology to assess health disparities in localized, malignant (ICD-O-3 histology and behavior code) PCa surgical treatment delays while assessing co-occurring risk profiles (i.e., outliers). We used the Tennessee Department of Health cancer registry incidence data from 2005 to 2015 for adults over the age of 18 (N=18,088). We examined the differences in PCa surgical delay, measured in days since diagnosis by multiple determinants of health. Determinants of health used were age groups based on US Preventive Services Task Force recommendations, marital status, race, ethnicity (Hispanic/Latino), county of residence (non-Appalachian or Appalachian) and health insurance (none/self-pay, public, or private). To select the best fitting model, we employed a comparative approach comparing sample size adjusted BIC and entropy; which indicates a reliable separation of classes. Results: The best model was a three-class solution with an entropy of 0.69. The highest surgical delay group (12% of sample) with a 31% likelihood of delaying surgery more than 90 days had the highest conditional probabilities of being black, under 55 years old, living in a non-Appalachian county, and single, with a high probability of having private health insurance. The medium surgical delay group (46% of sample) with a 21% likelihood of delay had the highest conditional probabilities of being 70 and older and having public health insurance, with a high probability of being married, non-Hispanic, white. The lowest surgical delay class (42% of sample) with a 14% likelihood of delay had the high conditional probabilities of being 55-69 years old, non-Hispanic, white, and married, with public health insurance. Conclusion: We identified that even with heath insurance blacks had the highest surgical delay living in non-Appalachian counties, which was almost double that of the whites with lowest delay class. These disparities in PCa surgical delay may explain differences in health outcomes in blacks who are most at-risk; however structural factors, clinical care, and treatment outcomes may play a role in these delay, but were not available for analysis. The use of person-centered approaches can help public health researchers better detect cancer risk subgroups and the underlying determinants that may be overlooked, but needed for tailored interventional programs to address prostate cancer disparities.
Citation Format: Francisco Alejandro Montiel Ishino, Xiaohui Liu, Bonita Salmeron, Rina Das, Faustine Williams. Identifying risk subgroups of invasive prostate cancer surgical delay using a person-centered approach: The constellation of health determinants using latent class analysis on cancer registry data [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4337.