Abstract
BACKGROUND: Urachal carcinoma (UrC) is a rare, aggressive cancer with a poor prognosis that is frequently diagnosed in advanced stages. Due to its rarity, the current staging systems, namely Sheldon, Mayo, and Ontario were established based on relatively small patient cohorts, necessitating further validation. We used a large patient population from the National Cancer Database to model a novel staging system based on the Tumor (T), Node(N), and Metastasis (M) (TNM) staging system and compared it to established staging systems. METHODS: We identified patients diagnosed with UrC between the years of 2004-2016. To determine median overall survival (OS), a Kaplan-Meier (KM) curve was generated using the Sheldon, Mayo, Ontario, and TNM staging system. A cox proportional-hazards regression model was developed to highlight predictors of overall survival. RESULTS: A total of 626 patients were included in the analysis. The OS for the entire cohort was 58.2 months (50.1-67.8) with survival rates at 12, 24, and 60 months of 83%, 70%, and 49%, respectively (p < 0.0001). As compared to the Sheldon, Mayo, and Ontario staging system, our TNM staging system had a more balanced sample and survival distribution per stage and no overlap among stages on KM survival curves. The Mayo, Ontario, and TNM staging systems were more accurate in terms of stage-survival correlation than the Sheldon staging system (p < 0.05 for all stages). CONCLUSIONS: The proposed novel TNM staging system for UrC has a more balanced sample distribution and a more accurate stage-survival correlation than the traditional Mayo, Sheldon, and Ontario staging systems. It is clinically applicable and enables better risk stratification, prognosis, and therapeutic decision-making.