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Updated: Jun 7, 2025
Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development and validation of a prognostic nomogram for elderly-onset pancreatic neuroendocrine carcinoma: a
Haoxi Liu1, Qian Zhang1, Yitian Chen2
1Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, State Key Laboratory of Digestive Health, National Clinical Research Center for Digestive Diseases, Beijing, China.
Background:
The incidence of elderly-onset pancreatic neuroendocrine carcinoma (PanNEC) is increasing. This study investigated independent risk factors affecting cancer-specific survival (CSS) and constructed a nomogram to predict CSS in patients with elderly-onset PanNEC.
Methods:
PanNEC patients older than 50 years from the Surveillance, Epidemiology, and End Results database were retrospectively selected from 2010 to 2021 and were randomly divided into a training set and a validation set. Independent factors affecting CSS were selected by univariate and multivariate analyses. The nomogram was built using significant variables. The discrimination and calibration of the nomogram were evaluated by the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis.
Results:
A total of 407 patients were selected and randomly assigned to a training set or a validation set at a 6:4 ratio. In the selected population, 227 individuals (55.8%) were male, 313 (76.9%) were white, with a mean age of 69.4 years. Among them, 318 individuals (78.1%) died due to the tumor, with a CSS time of 6 months. Multivariate Cox analysis showed that age [hazard ratio (HR): 1.56, 95% confidence interval (CI): 1.10-2.22, P=0.01], surgery (HR: 2.32, 95% CI: 1.27-4.23, P=0.006), chemotherapy (HR: 2.39, 95% CI: 1.68-3.38, P<0.001), tumor, nodes, and metastasis (TNM) stage (HR: 3.96, 95% CI: 1.19-13.19, P=0.03), and liver metastasis (HR: 1.75, 95% CI: 1.16-2.65, P=0.008) were independent risk factors that shortened CSS. The AUCs of the nomogram for the 6-month, 1-year, and 2-year CSS were 0.826, 0.791, and 0.8 in the training set and 0.848, 0.775, and 0.781 in the validation set, respectively. Calibration curves showed that the nomogram could accurately predict the 6-month, 1-year, and 2-year CSS in both datasets. Furthermore, decision curve analysis indicated that the nomogram had clinical benefits.
Conclusions:
The nomogram for CSS in patients with elderly-onset PanNEC showed good predictive power, enabling clinicians to understand patient's prognosis and make appropriate decisions.
