Abstract
BACKGROUND: Surgery is the preferred approach for treating endometrial cancer (EC). However, the prognosis of young women undergoing surgery has not been thoroughly evaluated. This study aims to establish a prognostic nomogram for predicting overall survival (OS) in postoperative patients with early-onset endometrial cancer (EOEC), facilitating risk stratification for high-risk patients. METHODS: Patients diagnosed with EOEC during 2004-2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The nomogram of OS was established according to the multivariate Cox regression analyses. The prediction accuracy and clinical net benefit of the model were assessed by the concordance index (C-index), receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Additionally, external validation was performed with 230 EOEC patients who underwent primary surgical treatment at the First Affiliated Hospital of Chongqing Medical University from 2013 to 2018. RESULTS: The mean survival period in the surgical group of EOEC was 87.62 months (range: 86.92-88.32), compared to 64.00 months (range: 55.05-72.96) in the non-surgical group. Compared with the non-surgical group, patients who underwent surgery had better outcomes. A total of 4345 eligible postoperative patients with EOEC were identified and enrolled in this study. Multivariate Cox analysis showed that age, race, grade, T stage, tumor size, and lymphadenectomy were significantly associated with the prognosis of EOEC, which were further incorporated to construct a nomogram. C-index and DCA showed the predictive capability and the clinical applicability of the nomogram was superior over the TNM stage and SEER stage. Furthermore, the external validation using the FAHCQMU cohort consistently demonstrated good predictive accuracy. CONCLUSIONS: Generally, we developed a novel nomogram model by comprehensively integrating multiple risk factors, which accurately predicts the clinical prognosis of EOEC patients after surgery.