Related Experiment Video
Updated: Aug 24, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Survival nomogram for endometrial cancer with lung metastasis: A SEER database analysis
Guangwei Yan1, Yingbin Li1, Yanmin Du1
1Department of Pathology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Purpose:
The lung is the most common distant metastatic organ in patients with endometrial cancer (EC) but is rarely reported. This study examines the association between clinical characteristics and overall survival (OS) in EC with lung metastasis.
Methods:
Patients with EC who had accompanying lung metastasis were selected from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2017. Univariate and multivariate Cox regression were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) and assess OS outcomes related to EC with lung metastasis. A Cox proportional hazards nomogram model for OS was constructed and validated. The calibration plot, receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to evaluate the discriminative ability and clinical benefit of the novel nomogram. Kaplan-Meier curves and scatter diagram analysis were used to investigate the risk stratifications of the nomogram.
Results:
Overall, 1542 EC patients with lung metastasis between 2010 and 2017 were included and randomly divided into training and validation cohorts. A nomogram model was constructed using the clinical characteristics of tumor grade, histological type, surgery, adjuvant chemotherapy, adjuvant radiation, brain metastasis and liver metastasis. The concordance indexes (C-indexes) were 0.750 (95% CI, 0.732-0.767) and 0.743 (95% CI, 0.719-0.767) for the training cohort and validation cohort, respectively. Calibration plots and DCA showed good clinical applicability of the nomogram. The areas under the curves (AUCs) were 0.803 and 0.766 for 1-year and 3-year OS, respectively, indicating that the nomogram model had a stable discriminative ability. An online calculator of our nomogram is available on the internet at https://endometrialcancer.shinyapps.io/DynNomapp/. Additionally, patients in the high-risk group had a significantly worse OS than those in the low-risk group.
Conclusion:
An easy-to-use, highly accurate nomogram was developed for predicting the prognosis of EC patients with lung metastasis.
More Related Videos
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
Related Concept Videos
Cancer Survival Analysis
Kaplan-Meier Approach