Incidence and survival trends for gastric neuroendocrine neoplasms: An analysis of 3523 patients in the SEER database. Issue 10 (October 2018)

• Record Type: Journal Article
• Authors: Cao, Long-Long; Lu, Jun; Lin, Jian-Xian; Zheng, Chao-Hui; Li, Ping; Xie, Jian-Wei; Wang, Jia-Bin; Chen, Qi-Yue; Lin, Mi; Tu, Ru-Hong; Huang, Chang-Ming
• Is Part Of: European journal of surgical oncology. Volume 44:Issue 10(2018)
• Page Start: 1628
• Page End: 1633
• Publication Date: 2018-10
• Subjects: Gastric neuroendocrine neoplasms -- Incidence -- Survival -- Prognosis; Oncology -- Periodicals; Cancer -- Surgery -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- surgery -- Periodicals; Cancer -- Chirurgie -- Périodiques; Cancérologie -- Périodiques; Oncologie; Chirurgie (geneeskunde); Electronic journals; Electronic journals -- Sciences; Electronic journals -- Medicine; Electronic journals; 616.994059005
• DOI: 10.1016/j.ejso.2018.01.082
• Languages: English
• ISSNs: 0748-7983

Abstract

Abstract: Background: The aim of this study is to investigate trends in the incidence and survival of patients with gastric neuroendocrine neoplasms (g-NENs). Methods: and methods: Patients diagnosed with g-NENs (n = 3523) were identified from the Surveillance, Epidemiology and End Results (SEER) database. Patients diagnosed with g-NENs (n = 199) in our department were designated as a validation dataset. Nomograms were adopted to predict disease-specific survival (DSS) and overall survival (OS). Results: The incidence of g-NENs is steadily increasing over time at a rate higher than any other cancer [annual percentage change (APC) = 6.3%, 95% confidence interval (CI) 5.6–7.0]. The 1-, 3-, and 5-year DSS rates were 87%, 78.6% and 70.6%, respectively, and the corresponding OS rates were 84.3%, 71.9%, and 53.7%, respectively. The multivariate analysis identified age, sex, T stage, M stage, and histological type as independent prognostic factors for both DSS and OS (all P < .05). The concordance indexes of the nomograms for DSS and OS in the training dataset were superior to those of the traditional tumor-node-metastasis (TNM) staging system [0.899 and 0.849 versus 0.864 and 0.783]. Calibration plots of the nomograms showed that the probability of DSS and OS closely corresponded to the actual observations in both the SEER-based training dataset and our inpatient validation dataset. Conclusion: The incidence of g-NENs has been steadily increasing at a rapid rate over the past four decades. The nomograms based on the analysis of the SEER database were superior to the TNM staging system in predicting the clinical outcomes for g-NEN patients.