Abstract
BACKGROUND: Development of an accurate model to predict prognosis for patients with pancreatic neuroendocrine tumors (P-NETs) after surgical resection is urgently needed. METHODS: In the present study, we conducted Cox proportional hazards regression to identify critical prognostic factors for P-NETs by analyzing data from 2174 patients in the Surveillance, Epidemiology, and End Results (SEER) database. Based on the results of multivariate analysis, a novel nomogram was established. Finally, the novel nomogram for P-NETs was validated in a cohort of 81 patients from a Chinese institute. RESULTS: In the multivariate analysis, age, tumor location, American Joint Committee on Cancer (AJCC) stage, histologic grade, lymph node ratio (LNR) and tumor size were independent risk factors for overall survival (OS) in P-NET patients who underwent radical resection. A nomogram consisting of age, sex, AJCC stage and histologic grade was found to have a concordance index (C-index) of 0.79 for OS in the SEER database, which was significantly higher than the C-index based on the AJCC stage, European Neuroendocrine Tumor Society (ENETS) stage or histologic grade alone. In the validation cohort, the C-index based on the nomogram reached 0.78 for OS. We also defined high-risk (total points >13.5 based on the nomogram) and low-risk populations (total points <13.5 based on the nomogram) in the validation cohort. We found that the actual 5-year recurrence rate in the high-risk group was significantly higher than that in the low-risk group (80.8% vs 23.4%, P<0.001). Kaplan-Meier analysis showed that the 5-year recurrence-free survival (RFS) in the low-risk group was significantly higher than that in the high-risk group (P<0.001). CONCLUSION: An AJCC stage- and histologic grade-based model was found to be extremely efficient in predicting survival for patients with P-NETs after surgical resection and deserves further evaluation for future clinical applications.