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Updated: Jul 16, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Construction and validation of a prognostic nomogram for ductal adenocarcinoma of the prostate: A population-based
Cheng Li1, Zhengqiang Wan1, Yinglei Wang2
1The Second Clinical Medical College of Binzhou Medical University, Yantai, Shandong, China.
Abstract:
This study aimed to establish and validate a nomogram for ductal adenocarcinoma of the prostate (DAC) to accurately predict the prognosis of DAC patients. The data of 834 patients with confirmed DAC were obtained from the Surveillance, Epidemiology, and End Results database. The cases were randomly assigned to the training and internal validation cohorts. Data from patients attending our institution as an external validation cohort (n = 35). Nomogram and web-based dynamic nomogram were constructed based on Cox regression analysis, and their prediction accuracy was evaluated by concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis. Multivariate analyses identified age, T-stage, N-stage, M-stage, surgery, lymph node dissection, Gleason score, and PSA as independent prognostic factors for overall survival. The C-index and calibration curves demonstrate the good discriminative performance of the prediction model. The area under the curve further confirmed the accuracy of the nomogram in predicting survival. In addition, the area under the curve and decision curve analysis were better than the 7th tumor-node-metastasis staging system. The Kaplan-Meier curves of the nomogram-based risk groups showed significant differences (P < .001). We constructed and validated the first nomogram to predict patients with DAC.
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