Validation of predictors for lymph node status in penile cancer: Results from a population-based cohort

Abstract

Introduction: The ability to predict lymph node (LN) status is essential in the management of men with localized squamous cell carcinoma (SCC) of the penis. There has been limited external validation of available risk stratification tools, particularly in routine clinical care. The objective of this study was to evaluate the predictive variables of LN metastases within a large population-based cohort of patients.Methods: In this population-based cohort study, surgical pathology reports were linked to the population-based Ontario Cancer Registry to identify all patients who were diagnosed with penile cancer in Ontario, Canada. Multivariable analyses were performed to evaluate predictive variables for LN involvement. Three contemporary risk stratification schemes used to predict LN status were analyzed by logistic regression.Results: The study included 380 localized penile SCC cases treated between 2000 and 2010. Sixty-three (17%) had pathologically confirmed LN metastases. Among these, 35 (56%) were diagnosed within three months of the initial penile SCC diagnosis and these patients had a worse five-year disease-specific survival (43%; 95% confidence interval [CI] 26–64) compared to patients who were diagnosed at a delayed LN dissection. On multivariable analysis, age (odds ratio [OR] 0.68; 95% CI 0.52–0.88), pathological stage (≥pT1b; OR 3.32; 95% CI 1.38–8.01), and tumour grade (Grade 2 OR 2.98; 95% CI 1.26–7.62; Grade 3 OR 3.97; 95% CI 1.32–11.9) were associated with an increased risk of LN metastases. Candidate risk stratification schemes demonstrated moderate to good property, with C-statistics ranging from 0.662–0.747.Conclusions: Using a population-based cohort of penile cancer patients with a relatively low proportion of patients with pathologically confirmed LN involvement, we confirm and externally validate the importance of age, stage, and grade of the primary tumour in predicting nodal status.