Objective: To establish a novel nomogram to predict overall survival of patients with gastric neuroendocrine neoplasms (g-NEN). Methods: A case control study was conducted. Clinicopathological and follow-up data of patients with g-NEN who were treated in two academic medical centers in Southern China between July 2008 and June 2018 were retrospectively collected, including 174 patients from Sun Yat-sen University Cancer Center and 102 patients from the First Affiliated Hospital of Sun Yat-sen University. Univariate survival analysis using Kaplan-Meier method and multivariate analysis using Cox regression were performed to identify prognostic factors. A nomogram was subsequently established based on prognostic factors. Harrell's concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA) were used to verify the performance of the model according to differentiation, calibration and clinical utility. Results: A total of 276 patients were enrolled in the study, of whom 189 patients were male and 87 were female. The age at diagnosis was below 60 years old in 150 patients and 60 years or older in 126 patients. There were patients diagnosed with gastric neuroendocrine carcinoma (g-NEC) and 101 patients with gastric neuroendocrine tumor (g-NET). The number of patients with primary tumor locating at upper, middle and lower parts of stomach was 131, 98 and 47, respectively. As for TNM stage, 72 patients were categorized as stage I, 26 patients stage II, 93 patients stage III, and 85 patients stage IV. Univariate analysis indicated that age, pathological type, primary site, Ki-67 index, T stage, N stage, and M stage were associated with overall survival of g-NEN patients (all P<0.05). Multivariate regression analysis testified that high Ki-67 index, advanced T stage and advanced M stage were independent prognostic factors (all P<0.05). The C-index of the nomogram was 0.806 (95%CI: 0.769-0.863). The calibration curve of the nomogram showed that the predicted survival rate was consistent with the actual survival rate in g-NEN patients. The ROC curves and DCA showed that the nomogram had better differentiation and clinical utility than the American Joint Committee on Cancer (AJCC) 8th TNM staging system (the area under the ROC curve was 0.862 vs. 0.792). Conclusion: The first nomogram to predict overall survival of patients with g-NEN is established and verified in this study, which provides individual prediction of 3-year overall survival rate and is applicable to both g-NET and g-NEC patients.
目的： 利用列线图建立胃神经内分泌肿瘤（g-NEN）患者的生存预测模型。 方法： 采用病例对照研究方法，收集中山大学肿瘤防治中心（174例）和中山大学附属第一医院（102例）两中心2008年7月至2018年6月收治的g-NEN患者的临床病理信息和生存随访资料，根据Kaplan-Meier单因素生存分析和Cox多因素分析筛选出的独立预后因素建立列线图模型。采用一致性指数（C-index）、受试者工作特征曲线（ROC）、校准曲线以及临床决策曲线（DCA）从区分度、校准度和临床效用3个方面验证该模型的性能。 结果： 全组患者中男性189例，女性87例；<60岁和60岁以上者分别为150例和126例；胃神经内分泌癌（g-NEC）175例，胃神经内分泌瘤（g-NET）101例；肿瘤胃内原发部位：胃上部、胃中部和胃下部分别为131例、98例和47例；肿瘤TNM分期：Ⅰ期72例、Ⅱ期26例、Ⅲ期93例和Ⅳ期85例。单因素分析结果显示，年龄、病理类型、胃内原发部位、Ki-67指数、T分期、N分期和M分期与本组g-NEN患者预后有关（均P<0.05）。多因素回归分析结果显示，Ki-67指数高、T分期晚和M分期晚是影响g-NEN患者生存的独立预后因素（均P<0.05）。列线图模型的C-index为0.806（95% CI：0.769~0.863）。校准曲线证实模型与实际观测结果有较好的一致性，ROC曲线与DCA决策曲线显示，模型相比美国癌症联合委员会（AJCC）第8版TNM分期系统具有更好的区分度和临床效用（其中ROC曲线下面积为0.862比0.792）。 结论： 本研究建立并验证了针对g-NEN、且同时适用于g-NET和g-NEC的预后预测系统，以可视化的列线图模型预测g-NEN患者的3年总生存率，具有良好的预测性能和临床应用价值。.
Keywords: Neuroendocrine neoplasms, gastric; Nomogram; Overall survival.