基于临床和超声特征的术前诊断肝内胆管癌列线图的构建与评估  

Development and evaluation of a clinical and ultrasound features-based nomogram for the preoperative diagnosis of intrahepatic cholangiocarcinoma

作　　者：刘春蕊 薛海燕 刘晗 万鹏[2] 姚静 孔文韬[1] 周正扬[3] Liu Chunrui;Xue Haiyan;Liu Han;Wan Peng;Yao Jing;Kong Wentao;Zhou Zhengyang(Department of Ultrasound,Nanjing Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University,Nanjing 210008,China;College of Computer Science and Technology,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China;Department of Radiology,Nanjing Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University,Nanjing 210008,China)

机构地区：[1]南京大学医学院附属鼓楼医院超声医学科,南京210008 [2]南京航空航天大学计算机科学与技术学院,南京210016 [3]南京大学医学院附属鼓楼医院医学影像科,南京210008

出　　处：《中华肝胆外科杂志》2024年第5期354-359,共6页Chinese Journal of Hepatobiliary Surgery

基　　金：国家科技部基金(SQ2020YFA0713800);国家自然科学基金(81771844、82371981)。

摘　　要：目的建立和评估基于临床和超声特征的诊断肝内胆管癌的列线图。方法回顾性分析2016年1月至2022年8月南京大学医学院附属鼓楼医院因肝占位性病变拟行肝切除术的723例肝癌患者资料。最终入组399例患者,其中男性284例,女性115例,年龄(60.5±10.5)岁。399例患者中肝细胞癌198例、肝内胆管癌201例。399例患者通过计算机产生随机数的方法以7∶3随机分为训练集(n=279)和测试集(n=120)。单因素和多因素logistic回归分析肝内胆管癌的影响因素,根据多因素logistic回归分析结果,使用R软件建立术前诊断肝内胆管癌的列线图。采用受试者工作特征(ROC)曲线、校准曲线评估列线图诊断肝内胆管癌的能力。决策曲线分析模型给患者带来的净收益。结果多因素logistic回归分析示病灶形状不规则、胆管扩张、女性、肝硬化、糖类抗原242>10 U/ml、糖类抗原125>30 U/ml和甲胎蛋白>10μg/L是肝内胆管癌的影响因素(均P<0.05)。基于上述因素构建列线图。列线图在训练集和测试集诊断肝内胆管癌的ROC曲线下面积分别是0.966、0.956,校准曲线显示该模型的预测效果与实际情况的一致性良好。决策曲线分析显示在多数合理阈值概率,列线图比所有患者都诊断为肝细胞癌或肝内胆管癌更有效,即可以获得净获益。结论基于临床和超声特征构建的术前诊断肝内胆管癌列线图诊断效果良好。Objective To establish and evaluate a clinical and ultrasound parameters-based nomogram for the preoperative differentiating diagnosis of intrahepatic cholangiocarcinoma(ICC).Methods A total of 723 patients undergoing hepatectomy in Nanjing Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University from January 2016 to August 2022 were retrospectively screened.A total of 399 patients with hepatocellular carcinoma(HCC,198 cases)or ICC(201 cases)were enrolled in this study,including 284 males and 115 females,aged(60.5±10.5)years.Through random sampling using computer-generated random numbers,patients were divided into training(n=279)and validation groups(n=120)in a ratio of 7∶3.Univariate and multivariate logistic regression were performed to identify factors differentiating ICC,and a nomogram was established using R software based on independent risk factors for ICC.The accuracy of the nomogram was evaluated by receiver operating characteristic curve and calibration curves.Decision curve analysis was performed to assess the net benefit of the model.Results Multivariate logistic regression analysis showed that irregular shape,cholangiectasis,female,cirrhosis,carbohydrate antigen 242>10 U/ml,carbohydrate antigen 125>30 U/ml and alpha-fetoprotein>10μg/L were independent differentiating factors for ICC(all P<0.05).A nomogram was constructed based on those factors.The nomogram showed a better discrimination between ICC and HCC.The area under the curve of the training group and the validation group were 0.966 and 0.956,respectively.The calibration curve showed that the prediction effect of the model is in good agreement with the actual situation.Decision curve analysis showed that the nomogram was more effective than diagnosing all patients as either HCC or ICC,which yielded a net benefit at the most reasonable threshold probabilities.Conclusion The nomogram for the preoperative diagnosis of ICC based on clinical and ultrasound features showed a good diagnostic performance.

关 键 词：胆管上皮癌 癌 肝细胞 列线图 超声 

分 类 号：R735.7[医药卫生—肿瘤]