Development and Validation of Prognostic Nomograms for Periampullary Neuroendocrine Neoplasms: A SEER Database Analysis

Abstract

(1) Background: Periampullary neuroendocrine neoplasms (NENs) are rare tumors that lack a prognostic prediction model. We aimed to design comprehensive and effective nomograms to predict prognosis; (2) Methods: Univariate and multivariate Cox analyses were used to screen out significant variables for the construction of the nomograms. The discrimination and calibration of the nomograms were carried out using calibration plots, concordance indices (C-indices), and area under time-dependent receiver operating characteristic curves (time-dependent AUCs). Decision curve analysis (DCA) was used to compare the clinical applicability of the nomograms, TNM (Tumor- Node-Metastasis) stage, and SEER stage; (3) Results: The independent risk factors for overall survival (OS) and cancer-specific survival (CSS) of patients with periampullary NENs included age, tumor size, histology, differentiation, N stage, M stage, and surgery, which were used to construct the nomograms. The calibration curves and C-indices showed a high degree of agreement between the predicted and actual observed survival rates. The AUCs displayed good calibration and acceptable discrimination of the nomograms. Additionally, the DCA curves indicated that the nomograms showed better clinical applicability; (4) Conclusions: We developed and validated nomogram prognostic models for patients with periampullary NENs. The nomograms provided insightful and applicable tools to evaluate prognosis.