恶性孤立性肺结节的危险因素分析及预测模型建立

Risk factors and establishment of predictive models for malignant solitary pulmonary nodules

目的分析恶性孤立性肺结节(SPN)的危险因素,并建立预测模型。方法选择196例SPN患者,其中良性病变91例、恶性病变105例。收集患者的临床资料,包括性别、民族、年龄、病程、症状(咳嗽、咯血、胸痛、发热、体质量减轻)、吸烟指数、肿瘤既往史、家族肿瘤史。对患者进行计算机断层扫描(CT),观察结节的直径、位置、分叶征、毛刺征、血管集束征、胸膜凹陷征、空泡征、空洞、钙化、卫星灶、边界情况及标准摄取值(SUV)。采集患者外周静脉血,检测血清肿瘤标记物癌胚抗原(CEA)、神经元特异性烯醇化酶(NSE)、细胞角蛋白19(CYFRA21-1)、鳞状上皮细胞癌抗原(SCC)和CA125水平。采用Logistic回归分析筛选恶性SPN的危险因素,并建立临床预测模型。绘制该模型的ROC曲线,计算曲线下面积(AUC),评价该模型对恶性SPN的诊断价值。结果多因素Logistic回归分析筛选出高龄、直径增大、分叶、CYFRA21-1阳性为恶性SPN患者的独立预测因子(P均<0. 05)。建立的恶性SPN预测模型为:P=ex/(1+ex),X=-8. 15+[0. 105×年龄(岁)+[0. 092×直径(mm)]+(1. 303×分叶)+(1. 965×CYFRA21-1)。该模型的AUC为85. 8%(95%CI为0. 800～0. 915),高于国内模型、Mayo模型和VA模型。结论高龄、CT上SPN直径较大、分叶征及CYFRA21-1阳性是恶性SPN的独立危险因素;成功建立了恶性SPN的预测模型,该模型有助于指导临床诊断恶性SPN。

Objective To analyze the independent risk factors for malignant solitary pulmonary nodules(SPN)and to establish predictive models.Methods We selected 196 patients with SPN,including 91 benign lesions and 105 malignant lesions,and collected clinical data,including gender,ethnicity,age,duration of symptoms(cough,hemoptysis,chest pain,fever,and weight loss),smoking index,past history of cancer,and family history of cancer.All patients received computed tomography(CT),and we observed the imaging features,including diameter,location,lobulation,spiculation,vascular convergence,pleural indentation,vacuole sign,cavity,calcification,satellite focus,boundary,and standard uptake value(SUV).Peripheral venous blood was collected from patients for detection of serum tumor markers carcino-embryonic antigen(CEA),neuron-specific enolase(NSE),cytokeratin 19(CYFRA21-1),squamous cell carcinoma antigen(SCC),and CA125.Logistic regression analysis was used to screen the risk factors for malignant SPN and we established the clinical prediction model.The ROC curve of the model was drawn,and the area under the curve(AUC)was calculated to evaluate the diagnostic value of the model for malignant SPN.Results Multivariate logistic regression analysis screened out the independent risk factors for malignant SPN patients,including age,diameter increase,lobulation,and CYFRA21-1.The established malignant SPN prediction model was:P=ex/(1+ex),X=-8.15+[0.105×age(years)+[0.092×diameter(mm)]+(1.303×lobulation)+(1.965×CYFRA21-1).The model had an AUC of 85.8%(95%CI 0.800-0.915),which was higher than that of the domestic model,Mayo model and VA model.Conclusions Advanced age,larger diameter of SPN on CT,burr sign,and positive CYFRA21-1 are independent risk factors for malignant SPN.The predictive model of malignant SPN is successfully established,which is helpful to guide the clinical diagnosis of malignant SPN.