A Practical and Easy-to-use Tool for Estimating the Overall Survival of Elderly Patients with Non-Functional Pancreatic Neuroendocrine Tumors

Abstract

Abstract Background The objective of this study was to develop a nomogram for the prediction of overall survival (OS) in elderly patients diagnosed with non-functional pancreatic neuroendocrine tumors (NF-pNETs). Methods 1. Patients aged 65 years and older, who were diagnosed with NF-pNETs between 2004 and 2016, were selected for this study from the Surveillance, Epidemiology, and End Results (SEER) database. The enrolled patients were randomly divided into two cohorts - training and validation - in a ratio of 7:3. Multivariate Cox regression analysis was utilized to identify predictors associated with overall survival (OS) for constructing nomograms. The performance of the nomogram was evaluated using various metrics including concordance index (C-index), area under the receiver operating characteristic curve (AUC), calibration plots, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision-curve analysis (DCA). Results The multivariate Cox regression analysis revealed that age at diagnosis, primary site, histology grade, tumor size, N stage, M stage, and surgery status were independent covariates significantly associated with overall survival (OS). These factors were utilized to develop a nomogram. The constructed nomogram demonstrated a C-index greater than 0.75. Furthermore, the area under the curve (AUC) values indicated the superior discriminatory performance of the established nomogram compared to the American Joint Committee on Cancer (AJCC) TNM staging system for predicting OS. Calibration plots exhibited close alignment between predicted and actual survival rates. Additionally, both net reclassification improvement (NRI) and integrated discrimination improvement (IDI) showed positive improvements in the prediction accuracy of the nomogram over the TNM staging system in both training and validation cohorts. Finally, decision curve analysis (DCA) substantiated the substantial clinical utility of the developed nomogram. Conclusion We constructed a nomogram for predicting OS in elderly patients with NF-pNETs to help clinicians assess patient prognosis.