原发性胃肠间质瘤术后无复发生存危险因素分析及其预测模型建立:历史性队列研究  

Analysis of risk factors affecting postoperative relapse-free survival in primary gastrointestinal stromal tumor and establishment of Nomogram predictive model:a historical cohort study

作　　者：张海宝[1] 王朝樣 林浩 巨家华 杨熊飞[2] 杨伟林[3] 俞永江 ZHANG Haibao;WANG Chaoyang;LIN Hao;JU Jiahua;YANG Xiongfei;YANG Weilin;YU Yongjiang(The First Clinical Medical College,Lanzhou University,Lanzhou 730000,P.R.China;Department of Anorectal Surgery,Gansu Provincial People’s Hospital,Lanzhou 730000,P.R.China;Department of Gastrointestinal Surgery/Hernia and Abdominal Wall Surgery,The First Hospital of Lanzhou University,Lanzhou 730000,P.R.China)

机构地区：[1]兰州大学第一临床医学院,兰州730000 [2]甘肃省人民医院肛肠科,兰州730000 [3]兰州大学第一医院胃肠及疝与腹壁外科,兰州730000

出　　处：《中国普外基础与临床杂志》2024年第5期585-592,共8页Chinese Journal of Bases and Clinics In General Surgery

基　　金：甘肃省自然科学基金项目(项目编号:21JR1RA089)。

摘　　要：目的 分析影响原发性胃肠间质瘤(gastrointestinal stromal tumor,GIST)患者术后复发的相关危险因素并构建列线图预测模型。方法 回顾性收集2011年1月至2020年12月期间在兰州大学第一医院和甘肃省人民医院经术后病理证实为GIST患者的临床病理资料,使用R软件相关函数按7∶3比例随机分为训练集和验证集。采用单因素和多因素Cox回归分析影响GIST患者术后无复发生存期(relapse-free survival,RFS)的风险因素并以此构建预测GIST患者术后3年和5年无复发生存率概率的列线图预测模型。使用受试者操作特征曲线下面积、一致性指数及校准曲线评估模型的效能,通过决策曲线分析评估列线图预测模型与改良美国国立卫生研究院分级标准的临床效用。结果 本研究最终纳入454例患者,其中训练集317例、验证集137例。多因素Cox回归分析结果显示,肿瘤位置、肿瘤大小、分化程度、美国癌症联合委员会TNM分期、有丝分裂率、CD34表达、手术方式、淋巴结检出数目及靶向药物治疗时间为GIST患者术后RFS的影响因素(P<0.05),基于这些影响因素构建的列线图预测模型区分GIST患者术后无复发生存的一致性指数(95%CI)在训练集和验证集中分别为0.731(0.679,0.783)及0.685(0.647,0.722),它区分GIST患者术后3、5年无复发生存的受试者操作特征曲线下面积(95%CI)在训练集中分别为0.764(0.681,0.846)和0.724(0.661,0.787),在验证集中分别为0.749(0.625,0.872)和0.739(0.647,0.832);通过Bootstrap抽样1 000次对列线图预测模型进行验证并绘制的校准曲线结果显示,在训练集中列线图预测的GIST术后3年及5年无复发生存率与实际的无复发生存率具有良好的一致性,而在验证集中一致性稍差;在训练集中,采用决策曲线分析评估列线图预测模型在阈值概率范围为0.19~0.57时预测GIST术后3年无复发生存率具有较高的净收益,阈值概率范围为0.44~0.83时,�Objective To analyze the relevant risk factors affecting postoperative relapse-free survival(RFS)in the primary gastrointestinal stromal tumors(GIST)and develop a Nomogram predictive model of postoperative RFS for the GIST patients. Methods The patients diagnosed with GIST by postoperative pathology from January 2011 toDecember 2020 at the First Hospital of Lanzhou University and Gansu Provincial People’s Hospital were collected, andthen were randomly divided into a training set and a validation set at a ratio of 7∶3 using R software function. Theunivariate and multivariate Cox regression analysis were used to identify the risk factors affecting the RFS for the GISTpatients after surgery, and then based on this, the Nomogram predictive model was constructed to predict the probabilityof RFS at 3- and 5-year after surgery for the patients with GIST. The effectiveness of the Nomogram was evaluated usingthe area under the receiver operating characteristic curve (AUC), consistency index (C-index), and calibration curve, andthe clinical utility of the Nomogram and the modified National Institutes of Health (M-NIH) classification standard wasevaluated using the decision curve analysis (DCA). Results A total of 454 patients were included, including 317 in thetraining set and 137 in the validation set. The results of multivariate Cox regression analysis showed that the tumorlocation, tumor size, differentiation degree, American Joint Committee onCancer TNM stage, mitotic rate, CD34expression, treatment method, number of lymph node detection, and targeted drug treatment time were the influencingfactors of postoperative RFS for the GIST patients (P<0.05). The Nomogram predictive model was constructed based onthe influencing factors. The C-index of the Nomogram in the training set and validation set were 0.731 [95%CI (0.679,0.783)] and 0.685 [95%CI (0.647, 0.722)], respectively. The AUC (95%CI) of distinguishing the RFS at 3- and 5-year aftersurgery were 0.764 (0.681, 0.846) and 0.724 (0.661, 0.787) in the training set a

关 键 词：胃肠间质瘤 列线图 预测模型 生存分析 

分 类 号：R73[医药卫生—肿瘤]