The Prognostic Ability of Staging System in Men with Penile Cancer: An Analysis of SEER Database - Jalan, Aditya; Kanodia, Ravi; Gurung, Sarita Rana; Malhotra, Rajeev Kumar; Nepal, Umesh; Pokhrel, Gyan Prasad; Lamichhane, Nirmal (Nepalese Journal of Cancer, 2020)
Background: Penile cancer is now a rare condition. The low incidence of the disease makes a valid estimation of its prognosis difficult. In this study, we made an attempt and propose a nomogram to develop a prognostic rule that could predict the Cancer-Specific Mortality (CSM) free rates in patients with primary penile squalors cell carcinoma of the penis (PPSCC).Methods: This study included 1304 patients diagnosed with PPSCC between the years 2004 & 2011 and treated with penile tumor excision. Subjects were staged as per Surveillance, Epidemiology & End Results stage (SEER), American Joint Committee on Cancer (AJCC), TNM classification and tumor grade (TG). CSM free rates were determined. Univariate and multivariate Cox regression model was used to test the prediction of the CSM free rate. The predictive rule accuracy was created using the receiver operating characteristic curve. Results: The clinico-pathological profile depicts a mean age of 64.66 ± 14.38 yrs. The most common primary site involved was glans penis (n= 483, 37%) and the disease was most commonly diagnosed at AJCC stage I (n= 670, 51.4%) disease. The cumulative 5-year CSM free rates according to Fine & Gray, & Kaplan-Meier methods were 81.8% and 79.8%, respectively. The predictive accuracy as per SEER stage, AJCC stage, TNM stage alone were 68.8%, 70.3%, 72.3%, respectively. When TG was combined, the predictive accuracy increased to 72.8%, 73.1%, and 75.0%, respectively. TNM stage with TG was most accurate in predicting CSM free rate compared to other models. Conclusions: TNM stage with TG and AJCC stage with TG appear to have comparable accuracy to predict the CSM free rate in patients with PPSCC, the TNM stage with TG is the most accurate (75%) method to predict the CSM free rates. The addition of the TG variable improved the accuracy of these prognostic models.