Abstract 222P
Background
Penile cancer is now a rare condition and the low incidence of disease makes 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 CSM free rates in patients with primary penile squamous cell carcinoma of 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 the tumor grade (TG). CSM free rates were determined. Univariate and multivariate Cox regression model was used to test prediction of the CSM free rate. p-value was adjusted as per Bonferroni corrections. The predictive rule accuracy was created using receiver operating characteristic curve.
Results
The clinic-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 localized in most patients (n = 777, 59.6%). Majority (n = 719, 55.1%) underwent partial penectomy followed by local tumor excision (n = 372, 28.5%). Most common pathological T stage was T1 (56.7%, n = 740), N stage was N0 (n = 1055, 80.9%) & M stage was M0 (n = 1269, 97.3%). Most commonly diagnosed AJCC was stage I (n = 670, 51.4%). 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
This study concludes that though TNM stage with TG, and AJCC stage with TG appear to have comparable accuracy to predict the CSM free rate in patients with PPSCC, TNM stage with TG is the most accurate (75%) method to predict the CSM free rates. Addition of TG variable definitely improved the accuracy of these prognostic models.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
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