BACKGROUND: A long-term objective is to refine patient diagnosis and prognosis to address heterogeneity in head and neck squamous cell carcinoma (HNSCC) through incorporation of patient and tumor factors. This study examined histopathology and demographic variables at primary diagnosis (early vs. late stage) in a HNSCC patient population with a higher than usual percentage of African American (AA) subjects. METHODS: The primary HNSCC cohort was drawn from a diverse patient population and constructed through re-review of the primary biopsy. Nine specific histopathology and patient factors (race, gender, age) at primary HNSCC diagnosis were evaluated. Logistic regression analyses incorporated univariate and multivariable modeling. RESULTS: Race, gender, pattern of invasion, tumor necrosis, perineural invasion, site, and tumor grade were included in the first multivariable model. The final multivariable model retained gender, race, grade, site, and perineural invasion as independent risk factors for late stage with goodness-of-fit, the area under the curve (AUC), as 0.691. CONCLUSIONS: This report emphasizes patient and tumor characteristics of race, gender, site, perineural invasion, grade, and pattern of invasion as independent factors of advanced stage HNSCC. Pattern of invasion and necrosis are also important tumor characteristics of late stage disease. These factors may offer clinical perspectives when evaluating patients with indeterminate stage.
BACKGROUND: A long-term objective is to refine patient diagnosis and prognosis to address heterogeneity in head and neck squamous cell carcinoma (HNSCC) through incorporation of patient and tumor factors. This study examined histopathology and demographic variables at primary diagnosis (early vs. late stage) in a HNSCC patient population with a higher than usual percentage of African American (AA) subjects. METHODS: The primary HNSCC cohort was drawn from a diverse patient population and constructed through re-review of the primary biopsy. Nine specific histopathology and patient factors (race, gender, age) at primary HNSCC diagnosis were evaluated. Logistic regression analyses incorporated univariate and multivariable modeling. RESULTS: Race, gender, pattern of invasion, tumor necrosis, perineural invasion, site, and tumor grade were included in the first multivariable model. The final multivariable model retained gender, race, grade, site, and perineural invasion as independent risk factors for late stage with goodness-of-fit, the area under the curve (AUC), as 0.691. CONCLUSIONS: This report emphasizes patient and tumor characteristics of race, gender, site, perineural invasion, grade, and pattern of invasion as independent factors of advanced stage HNSCC. Pattern of invasion and necrosis are also important tumor characteristics of late stage disease. These factors may offer clinical perspectives when evaluating patients with indeterminate stage.
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