基于术前血清肿瘤标记物的胃癌预后预测模型:一项多中心回顾性研究  

The novel prognosis prediction model based on preoperative serum tumor markers in gastric cancer:A multicenter,retrospective study

作　　者：王林俊 沈义凯 杨昆[2] 张子臻[3] 林建贤[4] 严超[5] 陈豪[6] 林杰 黄洪鑫 朱晟君 夏义文 蒋天璐 沈旭昇 李清雅 刘宏达 张殿彩 徐皓 杨力 李国新[6] 朱正纲[5] 黄昌明[4] 曹晖[3] 胡建昆[2] 徐泽宽 WANG Lin-jun;SHEN Yi-kai;YANG Kun;ZHANG Zi-zhen;LIN Jian-xian;YAN Chao;CHEN Hao;LIN Jie;HUANG Hong-xin;ZHU Cheng-jun;XIA Yi-wen;JIANG Tian-lu;SHEN Xu sheng;LI Qing-ya;LIU Hong-da;ZHANG Dian-cai;XU Hao;YANG Li;LI Guo-xin;ZHU Zheng-gang;HUANG Chang-ming;CAO Hui;HU Jian-kun;XU Ze-kuan(Gastric Cancer Center,the First Affiliated Hospital of Nanjing Medical University,Nanjing 210029,China;Gastric Cancer Center,West China Hospital,Sichuan University,Chengdu 610041,China;Department of Gastrointestinal Surgery,Renji Hospital,Shanghai Jiao Tong University School of Medicine,Shanghai 200120,China;Department of Gastric Surgery,Fujian Medical University Union Hospital,Fuzhou 350001,China;Department of Gastrointestinal Surgery,Ruijin Hospital,Shanghai Jiao Tong University School of Medicine,Shanghai 200025,China;Department of General Surgery,Nanfang Hospital,Southern Medical University,Guangzhou 510515,China)

机构地区：[1]南京医科大学第一附属医院胃肿瘤中心,江苏南京210029 [2]四川大学华西医院胃肠外科中心,四川成都610041 [3]上海交通大学医学院附属仁济医院胃肠外科,上海200127 [4]福建医科大学附属协和医院胃外科,福建福州350001 [5]上海交通大学医学院附属瑞金医院胃肠外科,上海200025 [6]南方医科大学南方医院普通外科,广东广州510515

出　　处：《中国实用外科杂志》2025年第1期95-108,共14页Chinese Journal of Practical Surgery

基　　金：国家自然科学基金项目(No.82472936);中国国家科学技术基础研究专项基金项目(No.2019FY101104);南京医科大学第一附属医院创新研究项目(PAPD);江苏省高等教育机构重点学科建设项目(No.JX10231801);江苏省重点学科(普通外科学)项目(No.ZDXKA2016005);南京医科大学部省共建肿瘤个体化医学协同创新中心项目。

摘　　要：目的探索基于联合使用多种常用的肿瘤标记物的预测模型,提高对胃癌预后预测的准确性。方法采用多中心、回顾性研究,收集2015年1月至2022年12月6家医院接受根治性胃切除术治疗的5119例胃癌病人。根据纳入及排除标准,最终纳入2947例病人。评估病人的基本信息,包括性别、年龄、肿瘤位置、肿瘤大小、分化程度、血管侵犯、神经侵犯、浸润深度(T)、淋巴结转移(N)、病理分期和术前血清肿瘤标记物进行分析。采用校准曲线、一致性指数(C-index)和决策曲线分析(DCA)对列线图的可信度进行评估。结果R语言随机选择4/5(2357/2947)的病人纳入训练队列,剩余1/5(590/2947)为验证队列。CEA、CA72-4、CA19-9和CA125被纳入风险评分。根据最佳临界值将病人分为高、低风险评分组。模型中纳入年龄、肿瘤位置、T、N和风险评分分组。在训练队列中,列线图的C指数为0.782(95%CI:0.744-0.820),在验证队列中为0.802(95%CI:0.733-0.871)。DCA曲线表明,该预测模型具有良好的临床适用性。校准曲线显示列线图预测的OS值基本与实际相符。结论基于术前血清肿瘤标记物的新型预后预测模型在预测胃癌根治术后病人的总生存期方面具有较好的临床应用价值,可指导胃癌病人的术后治疗。Objective To explore a novel prediction model based on the combined use of multiple common tumor markers to improve the accuracy of prognostic prediction for gastric cancer(GC).Methods This multi-center retrospective analysis collected 5119 GC patients treated with radical resection from January 2015 to December 2022 in 6 hospitals.Based on the inclusion and exclusion criteria,2947 patients were finally enrolled.Basic information about patients,including sex,age,tumor location,tumor size,differentiation,vascular invasion,neural invasion,depth of invasion(T),lymph node metastasis(N),pathological stage and preoperative serum tumor markers were assessed for analysis.The calibration curves,consistency index(C-index)and decision curve analysis(DCA)were employed to evaluate the precision and credibility of nomogram.Results R software randomly selected 4/5 patients(2357/2947)to be included in the training cohort and the remaining 1/5(590/2947)for the validation cohort.CEA,CA72-4,CA19-9 and CA125 were incorporated into risk-score.Patients were divided into high or low risk-score group based on the optimal cut-off value.Age,tumor location,T,N,and risk-score group were enrolled in the nomogram.The C-index of nomogram was 0.782(95%CI:0.744-0.820)in training cohort and 0.802(95%CI:0.733-0.871)in the validation cohort.The DCA curves showed the proposed predictive model had good clinical applicability.Calibration curves indicated the OS values predicted by nomogram fit well with the actual OS observed in the patients.Conclusions The novel prognostic prediction model based on preoperative serum tumor markers has potential clinical application value in predicting OS probability of gastric cancer patients undergoing radical surgery.Thus,it can guide the follow-up treatment of GC patients after surgical intervention.

关 键 词：胃癌 血清肿瘤标记物 LASSO-Cox回归 预后模型 列线图 

分 类 号：R6[医药卫生—外科学]