Development and Validation of Prognostic Nomograms for Patients with Duodenal Neuroendocrine Neoplasms

BACKGROUND: This study was designed to predict prognosis of patients with primary duodenal neuroendocrine neoplasms (D-NENs) by developing nomograms. MATERIAL/METHODS: Patients diagnosed with D-NENs between 1988 and 2015 were queried from the SEER database and a total of 965 appropriate cases were randomly separated into the training and validation sets. Kaplan-Meier analysis was used to generated survival curves, and the difference among the groups was assessed by the log-rank test. Independent prognostic indicators were acquired by Cox regression analysis, and were used to develop predictive overall survival (OS) and cancer-specific survival (CSS) nomograms. Harrell’s concordance index (C-index), area under the curve (AUC), calibration curves, and decision curve analysis (DCA) were used to assess the efficacy of nomograms. Tumor stage was regarded as a benchmark in predicting prognostic compared with the nomograms built in this study. RESULTS: The C-index was 0.739 (0.690–0.788) and 0.859 (0.802–0.916) for OS and CSS nomograms, respectively. Calibration curves exhibited obvious consistency between the nomograms and the actual observations. In addition, C-index, AUC, and DCA were better than tumor stage in the evaluative performance of nomograms. CONCLUSIONS: The nomograms were able to predict the 1-, 5-, and 10-year OS and CSS for D-NENs patients. The good performance of these nomograms suggest that they can be used for evaluating the prognosis of patients with D-NENs and can facilitate individualized treatment in clinical practice.