Predictors of Inguinal Lymph Node Metastasis in Penile Squamous Cell Carcinoma: Insights from a Single-Center Retrospective Study

<b>Background:</b> Squamous cell carcinoma (SCC) of the penis accounts for approximately 95% of penile cancers and is associated with substantial morbidity and mortality. SCC typically develops in uncircumcised men, most commonly affecting the foreskin or glans. While slow-growing, early detection is crucial to improve survival outcomes. Risk factors include advanced age, lack of circumcision, poor hygiene, HPV infection (types 16 and 18), chronic inflammation, and smoking. <b>Methods:</b> We conducted a retrospective, single-center study at IRCCS Hospital "G. Pascale" of Naples, Italy, involving 59 patients treated between January 2015 and January 2023. The inclusion criteria were surgically treated primary tumors, confirmed SCC pathology, and pathologically verified inguinal lymph node metastasis (ILNM). We analyzed clinical variables including lymph node involvement, lymphovascular invasion (LVI), spongiosum corpus involvement (SCI), HPV infection, and tumor differentiation. Univariate and multivariate logistic regression analyses were performed to determine independent predictors of ILNM. <b>Results:</b> The mean age of patients was 66.67 ± 13.97 years. ILNM was confirmed in 24 patients (40.6%), while 35 (59.3%) had no lymph node involvement. Univariate analysis identified lymph node involvement at diagnosis (<i>p</i> = 0.005), LVI (<i>p</i> = 0.003), and SCI (<i>p</i> = 0.003) as significant predictors of ILNM. These factors were confirmed in the multivariate analysis, with lymph node involvement (<i>p</i> = 0.004), LVI (<i>p</i> = 0.025), and SCI (<i>p</i> = 0.028) as independent predictors. <b>Conclusions:</b> Lymph node status, LVI, and SCI are significant predictors of ILNM in penile SCC. Identifying these factors can aid in risk stratification, optimizing surgical decisions, and potentially reducing unnecessary morbidity. Further large-scale studies are recommended to validate these findings and refine prognostic models.