Nomograms for Predicting Overall Survival and Cancer-Specific Survival of Young Patients with Epithelial Ovarian Cancer: Analysis Based on SEER Program

Introduction Currently, there is no clinical prediction model for young patients (≤ 45 years old) with epithelial ovarian cancer (EOC) based on large samples of clinical data. The purpose of this study was to construct nomograms using data extracted from the Surveillance, Epidemiology, and End Results (SEER) Program to predict the overall survival (OS) and cancer-specific survival (CSS) of patients and to further guide the choice of clinical treatment options. Methods Data from a total of 6376 young patients with EOC collected from 1998 to 2016 were selected from the SEER database. These patients were randomly divided (7:3) into a training cohort ( n = 4465) and a validation cohort ( n = 1911). Cox and least absolute shrinkage and selection operator (LASSO) analyses were used to select the prognostic factors affecting OS and CSS, and the nomograms of OS and CSS were established. The performance of the nomogram models was assessed by C-index, area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Sample were chosen from patients who underwent surgery in Shengjing Hospital to set external validation. Kaplan–Meier curves were plotted to compare survival outcomes between subgroups. Results Nomograms showed good predictive power and clinical practicality. The internal and external validation indicated better performance of the nomograms than the American Joint Committee on Cancer (AJCC) staging system and tumor grade system. Significant differences were observed in the survival curves of different risk subgroups. Conclusions We constructed predictive nomograms to evaluate the OS and CSS of young patients with EOC. The nomograms will provide an individualized evaluation of OS and CSS for suitable treatment of young patients with EOC.