Prognostic Factors and a Predictive Nomogram of Cancer-Specific Survival of Epithelial Ovarian Cancer Patients with Pelvic Exenteration Treatment

Ting Wang & Fang Wang · 2023-08-17

Objective. The aim of this study was to explore prognostic factors, develop and internally validate a prognostic nomogram model, and predict the cancer-specific survival (CCS) of epithelial ovarian cancer (EOC) patients with pelvic exenteration (PE) treatment. Methods. A total of 454 EOC patients from the Surveillance, Epidemiology, and End Results (SEER) database were collected according to the inclusion criteria and randomly divided into the training (n = 317) and validation (n = 137) cohorts. Prognostic factors of EOC patients with PE treatment were explored by univariate and multivariate stepwise Cox regression analyses. A predictive nomogram was constructed based on selected risk factors. The predictive power of the constructed nomogram was assessed by the time-dependent receiver operating characteristic (ROC) curve. Kaplan–Meier (KM) curve stratified by patients’ nomoscore was also plotted to assess the risk stratification of the established nomogram. In internal validation, the C index, calibration curve, and decision curve analysis (DCA) were employed to assess the discrimination, calibration, and clinical utility of the models, respectively. Results. In the training cohort, age, histological type, Federation of Gynecology and Obstetrics (FIGO) stage, number of examined lymph nodes, and number of positive lymph nodes were found to be independent prognostic factors of postoperative CSS. A practical nomogram model of EOC patients with PE treatment was constructed based on these selected risk factors. Time-dependent ROC curves and KM curves showed the superior predictive capability and excellent clinical stratification of the nomogram in both training and validation cohorts. In the internal validation, the C index, calibration plots, and DCA in the training and validation cohorts confirmed that the nomogram presents a high level of prediction accuracy and clinical applicability. Conclusion. Our nomogram exhibited satisfactory survival prediction and prognostic discrimination. It is a user-friendly tool with high clinical pragmatism for estimating prognosis and guiding the long-term management of EOC patients with PE treatment.

Funding
Nanjing Medical University Grant PY2022032Nanjing Medical University Grant SYH-3201160-0056Nanjing Medical University Grant 82273199Nanjing Medical University Grant BK20221417Nanjing Medical University Grant ZDXK202239Laboratory Medicine Research of Jiangsu Medical Association Grant PY2022032Laboratory Medicine Research of Jiangsu Medical Association Grant SYH-3201160-0056Laboratory Medicine Research of Jiangsu Medical Association Grant 82273199Laboratory Medicine Research of Jiangsu Medical Association Grant BK20221417Laboratory Medicine Research of Jiangsu Medical Association Grant ZDXK202239National Natural Science Foundation of China Grant PY2022032National Natural Science Foundation of China Grant SYH-3201160-0056National Natural Science Foundation of China Grant 82273199National Natural Science Foundation of China Grant BK20221417National Natural Science Foundation of China Grant ZDXK202239Natural Science Foundation of Jiangsu Province Grant PY2022032Natural Science Foundation of Jiangsu Province Grant SYH-3201160-0056Natural Science Foundation of Jiangsu Province Grant 82273199Natural Science Foundation of Jiangsu Province Grant BK20221417Natural Science Foundation of Jiangsu Province Grant ZDXK202239Key Medical Subjects of Jiangsu Province Grant PY2022032Key Medical Subjects of Jiangsu Province Grant SYH-3201160-0056Key Medical Subjects of Jiangsu Province Grant 82273199Key Medical Subjects of Jiangsu Province Grant BK20221417Key Medical Subjects of Jiangsu Province Grant ZDXK202239