Related Experiment Video
Updated: Jan 31, 2026
Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Competing risks and cause-specific mortality in patients with pancreatic neuroendocrine tumors
Zhuyin Li1, Shuai Du, Wei Feng
1First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China.
Background And Objective:
Currently, there are no competing risk analyses of cause-specific mortality in patients with pancreatic neuroendocrine tumors.
Materials And Methods:
We estimated a cumulative incidence function for cause-specific mortality. The first nomogram for predicting cause-specific mortality was constructed using a proportional subdistribution hazard model, validated using bootstrap cross-validation, and evaluated with decision curve analysis.
Results:
Sex, age, positive lymph node status, metastasis, surveillance, epidemiology, and end results historic stage, grade, and surgery strongly predicted cause-specific mortality. The discrimination performance of Fine-Gray models was evaluated using the c-index, which was 0.864. In addition, the calibration plot of the developed nomogram demonstrated good concordance between the predicted and actual outcomes. Decision curve analysis yielded a range of threshold probabilities (0.014-0.779) at which the clinical net benefit of the risk model was greater than that in hypothetical all-screening or no-screening scenarios.
Conclusion:
Our nomogram allows selection of a patient population at high risk for cancer-specific mortality and thus facilitates the design of prevention trials for the affected population.
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