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Updated: Jun 18, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Developing a nomogram for forecasting the 28-day mortality rate of individuals with bleeding esophageal varices using
Siming Lin1, Jantao Zheng2, Chanjuan Zhou3
1Department of Emergency Medicine, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China; Department of Emergency Medicine, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Background:
This study aimed to create a nomogram using the model for end-stage liver disease (MELD) that can better predict the risk of 28-day mortality in patients with bleeding esophageal varices.
Methods:
Data on patients with bleeding esophageal varices were retrospectively collected from the Medical Information Mart for Intensive Care database. Variables were selected using the least absolute shrinkage and selection operator logistic regression model and were used to construct a prognostic nomogram. The nomogram was evaluated against the MELD model using various methods, including receiver operating characteristic (ROC) curve analysis, calibration plotting, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA).
Results:
A total of 280 patients were included in the study. The patient's use of vasopressin and norepinephrine, respiratory rate, temperature, mean corpuscular volume, and MELD score were included in the nomogram. The area under the ROC curve, NRI, IDI, and DCA of the nomogram indicated that it performs better than the MELD alone.
Conclusion:
A nomogram was created that outperformed the MELD score in forecasting the risk of 28-day mortality in individuals with bleeding esophageal varices.
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