Objective: The aim of this study was to identify survival rates and potential prognostic factors of ovarian squamous cell carcinoma (OSCC), offering valuable insights for clinical decision making.
Methods: Leveraging the Surveillance, Epidemiology, and End Results (SEER) database, we selected 11 078 serous carcinoma (SC) patients and 198 OSCC patients based on predetermined criteria diagnosed from 2000 to 2020. We compared the overall survival (OS) and cancer-specific survival (CSS) before and after propensity score matching (PSM) in two groups. Prognostic differences were also compared between OSCC and SC groups at different stages. Univariate and multivariate Cox regression analyses were performed to investigate the impact of clinical and pathologic variables on the survival of patients with OSCC. Finally, we developed and validated a nomogram predictive model.
Results: OSCC tumors exhibited distinct characteristics, being relatively larger, more frequently unilateral, and better differentiated than SC tumors. After PSM, Kaplan-Meier analysis revealed significantly lower survival rates for OSCC patients in Stages IIB-IV, while Stages IA-IC displayed comparable survival. Independent risk factors for OSCC patients included advanced age, single marital status, higher tumor stage, and increased tumor size. Conversely, higher median household income and chemotherapy emerged as independent protective factors. Our predictive model and nomogram accurately forecasted patient survival rates in both SEER and internal validation datasets.
Conclusion: OSCC patients face significantly poorer prognosis than their SC counterparts, except in the very early stages. Higher median household income was associated with better OSCC survival.
Keywords: median household income; nomogram; ovarian squamous cell carcinoma; prognosis; propensity score matching.
© 2024 International Federation of Gynecology and Obstetrics.