Statistical analysis
NRI
REGRESSION
R software (version 4.1.0) and SPSS 20.0 were utilized for all statistical analyses in this study. The baseline characteristics comparison between the training and validation group was performed by using the Chi-square test and Fisher’s exact test. Univariate Cox regression analysis was used to determine the association between clinicopathological variables and prognosis. Then, the multivariate Cox regression analysis was performed to find the independent prognostic factors for elderly patients with EOC (The concordance index (C-index), the receiver operating characteristic (ROC), the calibration curve, the decision curve (DCA), the net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were all calculated by R software. Among them, C-index, ROC, and the calibration curve were used to appraise the discriminative ability and the prediction efficiency of the nomogram. In addition, DCA, NRI as well as IDI were adopted to assess the predictive ability and effectiveness of the nomogram in comparison with the traditional AJCC stage system. New risk stratification was developed by X-tile software according to the total points of the nomogram, and patients were then separated into low, medium, and high-risk groups. The survival differences in different risk stratification groups were compared by log-rank test and Kaplan–Meier plots.