A Nomogram for Predicting Cancer-Specific Survival in Patients With Stage I Vulvar Squamous Cell Carcinoma: A Study Based on the SEER Database and External Validation.

Abstract

IntroductionVulvar squamous cell carcinoma (VSCC) is a rare but increasingly prevalent gynecological malignancy. This study aimed to identify risk factors for stage I VSCC, which accounts for approximately 70% of VSCC patients, and to develop a nomogram to predict cancer-specific survival (CSS) for this large subgroup.MethodsThis study analyzed the datasets consisting of public training and independent external validation sets of patients diagnosed with stage I VSCC between 2010 and 2019. Prognostic factors were discerned through Cox regression analyses and the least absolute shrinkage and selection operator (LASSO) method. A nomogram for CSS was developed and evaluated using the C-index, Kaplan-Meier curves, and decision curve analysis (DCA) plots.ResultsOur analysis revealed variations in predictors of CSS and overall survival (OS) in stage I VSCC cases from the Surveillance, Epidemiology, and End Results (SEER) database. The multivariate Cox model suggested associations between CSS and age, grade, and number of tumors (NMT), while the LASSO model indicated potential roles for age, stage, invasion depth, NMT, and surgical method. The nomogram showed reasonable discriminative ability in the training (C-index: 0.785) and validation cohorts (C-index: 0.729), with supporting Kaplan-Meier and DCA analyses.ConclusionThis study proposes a prognostic model for CSS in stage I VSCC, identifying exploratory associations with multifocal tumors and surgical extent. Further prospective studies are needed to validate these findings and clarify their clinical implications.