亚厘米非小细胞肺癌气腔播散的nomogram风险预测模型构建  

Construction of a nomogram model for predicting risk of spread through air space in sub-centimeter non-small cell lung cancer

作　　者：王萧 张耀 朱康乐 赵怡 史经伟 徐倩倩 刘政呈 WANG Xiao;ZHANG Yao;ZHU Kangle;ZHAO Yi;SHI Jingwei;XU Qianqian;LIU Zhengcheng(Department of Thoracic Surgery,Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University,Nanjing,211166,P.R.China;Department of Thoracic Surgery,Nanjing Drum Tower Hospital,The Affiliated Hospital of Nanjing University Medical School,Nanjing,210008,P.R.China;Department of Anesthesia Surgery,Nanjing Drum Tower Hospital,The Affiliated Hospital of Nanjing University Medical School,Nanjing,210008,P.R.China)

机构地区：[1]南京医科大学鼓楼临床医学院胸外科,南京211166 [2]南京大学医学院附属鼓楼医院胸外科,南京210008 [3]南京大学医学院附属鼓楼医院麻醉手术科,南京210008

出　　处：《中国胸心血管外科临床杂志》2025年第3期345-352,共8页Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

基　　金：江苏省医学重点学科(ZDXK202229);南京市医学科技计划重点项目(ZKX21015)。

摘　　要：目的探讨亚厘米非小细胞肺癌气腔播散(spread through air space,STAS)与临床特征及影像学特征的相关性,构建nomogram风险预测模型,为亚厘米非小细胞肺癌患者术前规划提供参考。方法回顾性分析2022年1月—2023年10月于南京大学医学院附属鼓楼医院接受手术治疗且术后病理确诊为亚厘米非小细胞肺癌患者的临床资料。根据病理诊断肿瘤是否伴随STAS,将其分为STAS阳性组以及STAS阴性组。收集两组患者的临床和影像资料,进行单因素logistic回归分析,将差异具有统计学意义的变量纳入多因素分析,最终筛选出肿瘤发生STAS的独立危险因素,并构建nomogram模型。根据约登指数计算出灵敏度和特异度,并通过曲线下面积(area under the curve,AUC)、校准曲线和决策曲线分析(decision curve analysis,DCA)评估模型的效能。结果共纳入112例患者。STAS阳性组17例,其中男11例、女6例,平均年龄(59.0±10.3)岁;STAS阴性组95例,其中男30例、女65例,平均年龄(56.8±10.3)岁。单因素logistic回归分析显示,男性、抗GAGE7抗体阳性、平均CT值、毛刺征与STAS的发生相关(P<0.05)。多因素logistic回归分析表明,STAS与男性[OR=5.974,95%CI(1.495,23.872)]、抗GAGE7抗体阳性[OR=11.760,95%CI(1.619,85.408)]和平均CT值[OR=1.008,95%CI(1.004,1.013)]相关性仍然显著(P<0.05),而与毛刺征的关联不再显著(P=0.438)。基于上述3项独立预测因素构建亚厘米非小细胞肺癌STAS的nomogram模型。模型AUC值为0.890,灵敏度为76.5%,特异度为91.6%,校准曲线拟合良好,提示对于STAS有较好的预测效能;DCA图显示模型具有临床实用性。结论男性、抗GAGE7抗体阳性和平均CT值是亚厘米非小细胞肺癌STAS的独立预测因素,本研究构建的nomogram模型具有良好的预测价值,对患者的术前规划具有参考意义。Objective To investigate the correlation between spread through air space(STAS)of sub-centimeter non-small cell lung cancer and clinical characteristics and radiological features,constructing a nomogram risk prediction model for STAS to provide a reference for the preoperative planning of sub-centimeter non-small cell lung cancer patients.Methods The data of patients with sub-centimeter non-small cell lung cancer who underwent surgical treatment in Nanjing Drum Tower Hospital from January 2022 to October 2023 were retrospectively collected.According to the pathological diagnosis of whether the tumor was accompanied with STAS,they were divided into a STAS positive group and a STAS negative group.The clinical and radiological data of the two groups were collected for univariate logistic regression analysis,and the variables with statistical differences were included in the multivariate analysis.Finally,independent risk factors for STAS were screened out and a nomogram model was constructed.The sensitivity and specificity were calculated based on the Youden index,and area under the curve(AUC),calibration plots and decision curve analysis(DCA)were used to evaluate the performance of the model.Results A total of 112 patients were collected,which included 17 patients in the STAS positive group,consisting of 11 males and 6 females,with a mean age of(59.0±10.3)years.The STAS negative group included 95 patients,with 30 males and 65 females,and a mean age of(56.8±10.3)years.Univariate logistic regression analysis showed that male,anti-GAGE7 antibody positive,mean CT value and spiculation were associated with the occurrence of STAS(P<0.05).Multivariate regression analysis showed that associations between STAS and male(OR=5.974,95%CI 1.495 to 23.872),anti-GAGE7 antibody positive(OR=11.760,95%CI 1.619 to 85.408)and mean CT value(OR=1.008,95%CI 1.004 to 1.013)were still significant(P<0.05),while the association between STAS and spiculation was not significant anymore(P=0.438).Based on the above three independent predictors,a

关 键 词：亚厘米非小细胞肺癌 气腔播散 列线图 预测模型 

分 类 号：R734.2[医药卫生—肿瘤]