Objective: The aim of this study was to construct a competent model that can effectively predict the prognosis of patients with gastric carcinoid (GC) or neuroendocrine carcinoma (NEC).
Patients and methods: Data of patients with GC or NEC were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database from 1975 to 2017. Univariable and multivariable Cox analysis was used to determine the independent factors for patients with GC or NEC. Nomograms were established based on the independent factors and the results were evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).
Results: A total of 214 patients with GC and 65 patients with gastric NEC were extracted from the SEER database. Independent prognostic factors for patients with GC were M stage, gender, age, and chemotherapy. Independent prognostic factors for patients with gastric NEC included age, M stage, and chemotherapy. ROC curves, calibration curves, and DCA confirmed that the nomograms can precisely predict the prognosis of patients with GC and NEC.
Conclusions: The nomograms can effectively predict survival in patients with GC or NEC, which may assist the clinician in their decision-making and quantitatively judge the prognosis of individual patients.