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Veteran oropharyngeal cancer outcomes in the modern era: a multi-institutional retrospective analysis

Little, Samantha; Williams, Margaret F; Gilkey, Michael; Perez-Bello, Dannelys; Amadio, Grace; Klein, Mark; Block, Alec; Gore, Elizabeth; Chang, Michael; Duvvuri, Umamaheswar; Nance, Melonie A; Becker, Daniel J; Takiar, Vinita; Flanagan, Carrie E; Schwartzman, Larisa; Madabhushi, Anant; Sandulache, Vlad C
OBJECTIVE:To define oncologic outcomes in Veterans in the modern era using a multi-institutional cohort designed to support development and validation of prognostic and predictive biomarkers for oropharyngeal squamous cell carcinoma (OPSCC). METHODS:A retrospective analysis was conducted including adult OPSCC patients treated at one of nine Veterans Affairs Medical Centers between 2000 and 2024; inclusive of 597 HPV-associated and 197 HPV-independent tumors. All patients were treated with curative intent external beam radiotherapy (100%) with (90%) or without concurrent chemotherapy. RESULTS:A total of 894 adult patients (mean age, 64 years; 881 (99.5%) male) were included in the study; 22% of patients self-identified as Black. The estimated 2- and 5-year OS rates for the entire cohort were 71% and 54%, respectively and lagged substantially behind locoregional control (LRC) and distant metastatic control (DMC). For Veterans with HPV-associated OPSCC, LRC and DMC at 5 years were 87% and 87% respectively. The strongest drivers of OS and LRC were T-classification and chemotherapy choice on univariate and multivariate analysis. CONCLUSIONS:Although LRC and DMC rates among Veterans track well with recently completed clinical trial outcomes, OS rates lag substantially suggestive of higher rates of non-cancer-specific mortality. Together, these data suggest that predictive biomarker strategies focused on treatment effectiveness should be predicated on LRC and DMC rather than OS. This multicenter study is the first step in providing a robust dataset capable of developing and optimizing artificial intelligence (AI)-informed prognostic and predictive strategies essential to a precision oncology approach to OPSCC.
PMID: 41855673
ISSN: 1879-0593
CID: 6017022

Da Vinci 5 in transoral robotic surgery: first impression

Naruekon, J; Duvvuri, U; Prince, Andrew C; Pujol, G; Vaezi, A; Nance, M; Jacobson, A
PMID: 41188659
ISSN: 1863-2491
CID: 5959762