Pd29-07 the Role of Ethnicity in Shaping Prostate Cancer Treatment Trends and Impacting Outcomes: A Study on Asian Subpopulations

You have accessJournal of UrologyProstate Cancer: Epidemiology & Natural History I (PD29)1 May 2024PD29-07 THE ROLE OF ETHNICITY IN SHAPING PROSTATE CANCER TREATMENT TRENDS AND IMPACTING OUTCOMES: A STUDY ON ASIAN SUBPOPULATIONS Edoardo Beatrici, David-Dan Nguyen, Hari S. Iyer, Zhiyu Qian, Stuart R. Lipsitz, Filippo Dagnino, Muhieddine Labban, Dejan K. Filipas, Alexander P. Cole, and Quoc-Dien Trinh Edoardo BeatriciEdoardo Beatrici , David-Dan NguyenDavid-Dan Nguyen , Hari S. IyerHari S. Iyer , Zhiyu QianZhiyu Qian , Stuart R. LipsitzStuart R. Lipsitz , Filippo DagninoFilippo Dagnino , Muhieddine LabbanMuhieddine Labban , Dejan K. FilipasDejan K. Filipas , Alexander P. ColeAlexander P. Cole , and Quoc-Dien TrinhQuoc-Dien Trinh View All Author Informationhttps://doi.org/10.1097/01.JU.0001008736.23117.7f.07AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Using population-based registry data, this study examines prostate cancer (PC) outcomes among Asian American (AsA) subgroups. While AsA overall might have lower cancer mortality than Non-Hispanic Whites (NHWs), this may vary among AsA ethnicities. METHODS: Using the Surveillance, Epidemiology, and End Results (SEER) database (2010-2020), we analyzed men diagnosed with PC, focusing on PC-specific mortality. Men were tracked from diagnosis to death (PC-specific or other causes) or last follow-up. Only men eligible for definitive treatment according to the National Comprehensive Cancer Network guidelines were considered. Race/ethnicity was the primary predictor. The AsA group, based on SEER data, was divided into: Vietnamese, Filipino, Chinese, Japanese, Korean, Asian Indian, Asian Indian/Pakistani NOS, Pakistani, Thai, Hmong, Kampuchean, Laotian, and Other Asian. Mortality outcomes were examined using competing risk regression model. Cumulative Incidence Function (CIF) curves stratified by race and reporting PC-specific mortality were generated. RESULTS: Of 219,946 men analyzed, 6.8% were classified as AsAs. Compared to NHWs, AsAs demonstrated higher rates of advanced PC stages at diagnosis (p<0.001). While, compared to NHWs, the aggregate AsA cohort showed lower cancer-specific mortality rates (aSHR 0.80; p<0.001), upon examining individual AsA ethnicities, only Chinese (aSHR 0.72; p=0.01), Japanese (aSHR 0.66; p=0.01) and Other Asian (aSHR 0.49; p<0.001) reported better outcomes. No significant difference was reported for all other AsA ethnicities (all p>0.05). Likelihood ratio tests (chi-squared=23.50; df=12; p=0.02) consistently indicated enhanced model fit when using disaggregated versus aggregated AsA subgroups. The CIF curves are depicted in Figure 1. CONCLUSIONS: Although overall AsA data indicated superior PC oncological outcomes compared to NHWs, a closer look at specific AsA subgroups revealed inconsistencies. This highlights the pitfalls of using broad racial categories to understand health disparities. Delving deeper than standard census categories in cancer surveillance databases is crucial to truly grasp the root causes of AsA disparities. Download PPT Source of Funding: None © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e621 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Edoardo Beatrici More articles by this author David-Dan Nguyen More articles by this author Hari S. Iyer More articles by this author Zhiyu Qian More articles by this author Stuart R. Lipsitz More articles by this author Filippo Dagnino More articles by this author Muhieddine Labban More articles by this author Dejan K. Filipas More articles by this author Alexander P. Cole More articles by this author Quoc-Dien Trinh More articles by this author Expand All Advertisement PDF downloadLoading ...