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Updated: May 12, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development and validation of an easy-to-use nomogram for predicting pancreatic malignancy in patients with
Xin Yang1, Shengjie Ding1, Jinlu Guo1
1Department of Gastroenterology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Abstract:
This study aimed to develop and validate a practical nomogram for differentiating between benign and malignant pancreatic masses. A total of 494 patients with pancreatic mass lesions, confirmed by histopathology, were enrolled from Wuhan Union Medical College Hospital between January 2020 and May 2022. The participants were randomly divided into development and validation groups in a 7:3 ratio. Using multivariate logistic regression, the nomogram was constructed based on five independent predictors: blood type, CA19-9, IgG4, anorexia, and weight loss. The model's performance was assessed using receiver operating characteristic (ROC) curve analysis and calibration curves. In the development and validation sets, the areas under the ROC curve were 0.932 and 0.957, respectively. The nomogram demonstrated a high net benefit in the clinical decision curve analysis. Based on the model, pancreatic malignancy risk was classified as low (< 4%), moderate (4%-71%), and high (> 71%). This nomogram provides an easy-to-use, efficient tool for the early differentiation of pancreatic malignancies and could be implemented in primary, secondary, and emergency care settings to facilitate the timely referral of patients to higher-level hospitals.
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