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Updated: Aug 14, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
A nomogram for predicting overall survival in patients with type II endometrial carcinoma: a retrospective analysis
1Clinical Medical Colleges, Weifang Medical University, Weifang, China. scgdoctor@126.com.
Objective:
Type II endometrial cancer (EC) is associated with high risk of metastasis and poor prognosis. We aimed to develop a nomogram for predicting survival probability in patients with type II EC.
Patients And Methods:
Data from a total of 4,117 patients with confirmed type II EC were pulled from the Surveillance, Epidemiology, and End Results (SEER) database, and were randomly divided into a training set and an internal verification set. A nomogram was constructed based on the training set. The concordance index (C-index), area under the ROC curve, and calibration plots were used to evaluate the identification and calibration of the nomogram. The SEER internal validation set and the Chinese multicenter data set (74 patients) were used to verify discriminations and corrections of the model.
Results:
Multivariate analysis indicated that age, marital status, tumor size, T stage, N stage, M stage, surgery, radiotherapy, and chemotherapy were independent factors affecting the prognosis of type II EC patients (p<0.001). The corresponding nomogram has showed excellent calibration and discrimination (C-index [95% CI], 0.752 [0.738-0.766]). The model was verified in the internal verification set (0.760 [0.739-0.781]) and the Chinese multicenter set (0.784 [0.607-0.961]). In addition, the AUC further confirmed the accuracy of the nomogram in predicting survival. The calibration curve of OS within 5 years confirmed good calibration of the nomogram.
Conclusions:
This model and the corresponding risk classification system may provide useful tools for clinicians to evaluate the long-term prognosis of patients and carry out personalized clinical evaluation.
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