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Updated: Oct 18, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development and validation of a novel nomogram for predicting survival rate in pancreatic neuroendocrine neoplasms
Tianbao Liao1,2, Tingting Su3, Lina Huang4
1Department of President's Office, Youjiang Medical University for Nationalities, Baise, China.
Background:
Over the past decades, the incidence and prevalence of pancreatic neuroendocrine neoplasms (pNENs) have steadily increased. However, accurate prediction of the prognosis and treatment of this condition are currently challenging. This study aims to develop and validate a personalized nomogram to predict the survival of patients with pNENs.
Materials And Methods:
A total of 9739 patients with pNENs were downloaded from the Surveillance, Epidemiology, and End Results (SEER) database. Subsequently, the patients were randomly assigned to a derivation cohort (n = 6874) and a validation cohort (n = 2865). The survival of patients was assessed using the Cox proportional hazards (PHs) regression analysis. Then, the nomogram that predicted 3-and 5-year survival rates were developed in the derivation cohort. Further, the predictive performance of the nomogram was evaluated through discrimination and calibration.
Results:
The Cox regression analysis revealed that age, differentiation, the extent of tumor, M staging, and surgery were independent prognostic predictors for pNENs. The nomogram showed superior discrimination capability than AJCC staging in both derived and validation cohorts (C-index: 0.874 versus 0.721 and 0.833 versus 0.721). The calibration curves showed that the practical and predicted survival rates effectively coincided, specifically for the 3-year survival rate.
Conclusion:
Our nomogram is a valuable tool for the prediction of the survival rate for patients with pNENs; this may promote individualized prognostic evaluation and treatment.
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