南方医科大学学报

南方医科大学学报 ›› 2023, Vol. 43 ›› Issue (2): 183-190.doi: 10.12122/j.issn.1673-4254.2023.02.04

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基于单中心490例胃神经内分泌肿瘤建立的列线图具有良好的预后预测性能

张奔龙，鲁意迅，李 力，高云鹤，梁文全，郗洪庆，王鑫鑫，张珂诚，陈 凛   

  1. 中国人民解放军总医院第一医学中心普通外科医学部，北京 100853
  • 出版日期:2023-02-20 发布日期:2023-03-16

Establishment and validation of a nomogram for predicting prognosis of gastric neuroendocrine neoplasms based on data from 490 cases in a single center

ZHANG Benlong, LU Yixun, LI Li, GAO Yunhe, LIANG Wenquan, XI Hongqing, WANG Xinxin, ZHANG Kecheng, CHEN Lin   

  1. Department of General Surgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
  • Online:2023-02-20 Published:2023-03-16

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摘要： 目的 开发和验证一种有效的列线图，用以评估胃神经内分泌肿瘤（G-NEN)患者的个体预后。方法 采用回顾性病例对照的研究方法，收集2000年1月~2021年12月在解放军总医院第一医学中心确诊为G-NEN患者的临床病理资料，依据严格的纳排标准筛选，共纳入490例患者为研究对象。采用SPSS 26.0与R 4.2.0软件进行数据整理及分析统计：log-rank检验分析生存率的组间差异，Cox回归模型分析得出影响G-NEN患者预后的独立危险因素并纳入列线图，采用一致性指数（C?index）、受试者工作特征曲线（ROC）及其曲线下面积（AUC）、校准曲线、临床决策曲线（DCA）及其曲线下面积（AUDC）验证该模型的效能，并与第8版美国癌症联合委员会（AJCC）的TNM分期系统进行比较。结果 490例G-NEN患者年龄58.6±10.92岁；男性346例（70.6%），女性144例（29.4%）；病理分级为NET G1的患者130例（26.5%），NET G2患者 54例（11.0%），NEC患者206例（42.0%)，MiNEN患者100例（20.5%），未发现NET G3的患者；Ⅰ~Ⅳ期患者个数分别为：222例（45.3%），75例（15.3%），130例（26.5%），63例（12.9%）。单因素分析结果显示，年龄、性别、吸烟史、饮酒史、病理分级、Ki-67指数、肿瘤形态、肿瘤位置、肿瘤大小、浸润深度、淋巴结转移、远处转移、F-NLR是影响患者预后的危险因素（P<0.05），多因素分析结果显示，年龄、病理分级、肿瘤位置、浸润深度、淋巴结转移、远处转移、F-NLR 是影响 G-NEN 患者生存的独立危险因素（P<0.05）。列线图模型C?index为0.829（95% CI：0.800~0.858），1年、3年、5年总体生存率的ROC曲线下面积分别0.883、0.895、0.944。校准曲线证实模型与实际观测结果具有较好的一致。TNM 分期系统与列线图模型的 1年、3年、5年总体生存率DCA曲线下面积分别为：0.033和0.0218、0.191和0.148、0.248和0.197，表明列线图模型与TNM分期系统都具有明显的正向净收益，但列线图预测模型表现了更高的净收益，显示出更好的临床效用。结论 本研究基于490例G-NEN患者数据建立的列线图预后预测模型具有良好的预测性能和临床应用价值，对于临床医生更加简便快捷的评估G-NEN个体化预后具有显著意义。

关键词: 胃神经内分泌肿瘤；列线图模型；预后；总体生存率

Abstract: Objective To develop and validate a nomogram for predicting outcomes of patients with gastric neuroendocrine neoplasms (G-NENs). Methods We retrospectively collected the clinical data from 490 patients with the diagnosis of G-NEN at our medical center from 2000 to 2021. Log-rank test was used to analyze the overall survival (OS) of the patients. The independent risk factors affecting the prognosis of G-NEN were identified by Cox regression analysis to construct the prognostic nomogram, whose performance was evaluated using the C-index, receiver-operating characteristic (ROC) curve, area under the ROC curve (AUC), calibration curve, DCA, and AUDC. Results Among the 490 G-NEN patients (mean age of 58.6±10.92 years, including 346 male and 144 female patients), 130 (26.5%) had NET G1, 54 (11.0%) had NET G2, 206 (42.0%) had NEC, and 100 (20.5% ) had MiNEN. None of the patients had NET G3. The numbers of patients in stage I-IV were 222 (45.3%), 75 (15.3%), 130 (26.5%), and 63 (12.9%), respectively. Univariate and multivariate analyses identified age, pathological grade, tumor location, depth of invasion, lymph node metastasis, distant metastasis, and F-NLR as independent risk factors affecting the survival of the patients (P<0.05). The C-index of the prognostic nomogram was 0.829 (95% CI: 0.800-0.858), and its AUC for predicting 1- , 3- and 5- year OS were 0.883, 0.895 and 0.944, respectively. The calibration curve confirmed a good consistency between the model prediction results and the actual observations. For predicting 1- year, 3-year and 5-year OS, the TNM staging system and the nomogram had AUC of 0.033 vs 0.0218, 0.191 vs 0.148, and 0.248 vs 0.197, respectively, suggesting higher net benefit and better clinical utility of the nomogram. Conclusion The prognostic nomogram established in this study has good predictive performance and clinical value to facilitate prognostic evaluation of individual patients with G-NEN.

Key words: gastric neuroendocrine neoplasm; nomogram; prognosis; overall survival