小于1 cm的肺实性结节区分肺癌与肺内淋巴结的多因素分析

Multivariate Analysis of Solid Pulmonary Nodules Smaller than 1 cm in Distinguishing Lung Cancer from Intrapulmonary Lymph Nodes

背景与目的肺实性小结节的术前诊断及鉴别诊断十分困难。计算机断层扫描(computed tomography,CT)作为肺癌筛查的常用手段,被广泛应用于临床。本研究旨在对<1 cm的肺实性结节临床诊疗中肺恶性结节与肺内淋巴结患者的临床资料进行分析,为两者的鉴别提供参考。方法回顾性分析2017年6月-2020年6月行手术治疗的肺实性结节患者。共收集了145个结节(肺腺癌60个,肺类癌2个,恶性间皮瘤1个,肉瘤样癌1个,淋巴结81个)的患者临床资料,最终分为肺腺癌和肺内淋巴结两组,并对其临床资料进行了统计分析。根据单因素分析(χ^(2)检验、t检验)结果筛选有统计学差异的变量,纳入Logistic回归多因素分析,确定预测变量并绘制受试者工作曲线(receiver operatingcharacteristic,ROC)曲线,得到曲线下面积(areaunderthecurve,AUC)值。结果Logistic回归分析显示结节最长径、Max CT值、分叶征和毛刺征是肺腺癌与肺内淋巴结鉴别的重要指标,风险比分别为106.645(95%CI:3.828-2,971.220,P<0.01)、0.980(95%CI:0.969-0.991,P<0.01)、3.550(95%CI:1.299-9.701,P=0.01)、3.618(95%CI:1.288-10.163,P=0.02)。根据Logistic回归分析结果确定预测模型,绘制ROC曲线,计算曲线下面积AUC值=0.877(95%CI:0.821-0.933,P<0.01)。结论对于<1 cm的肺实性结节,在众多因素中,肺结节最长径、Max CT值、分叶征和毛刺征对鉴别肺恶性结节和肺内淋巴结更为重要。

Background and objective Preoperative diagnosis and differential diagnosis of small solid pulmonary nodules are very difficult.Computed tomography(CT),as a common method for lung cancer screening,is widely used in clinical practice.The aim of this study was to analyze the clinical data of patients with malignant pulmonary nodules and intrapulmonary lymph nodes in the clinical diagnosis and treatment of<1 cm solid pulmonary nodules,so as to provide reference for the differentiation of the two.Methods Patients with solid pulmonary nodules who underwent surgery from June 2017 to June 2020 were analyzed retrospectively.The clinical data of 145 nodules(lung adenocarcinoma 60,lung carcinoid 2,malignant mesothelioma 1,sarcomatoid carcinoma 1,lymph node 81)were collected and finally divided into two groups:lung adenocarcinoma and intrapulmonary lymph nodes,and their clinical data were statistically analyzed.According to the results of univariate analysis(χ^(2)test,t test),the variables with statistical differences were selected and included in Logistic regression multivariate analysis.The predictive variables were determined and the receiver operating characteristic(ROC)curve was drawn to get the area under the curve(AUC)value of the area under the curve.Results Logistic regression analysis showed that the longest diameter,Max CT value,lobulation sign and spiculation sign were important indicators for distinguishing lung adenocarcinoma from intrapulmonary lymph nodes,and the risk ratios were 106.645(95%CI:3.828-2,971.220,P<0.01),0.980(95%CI:0.969-0.991,P<0.01),3.550(95%CI:1.299-9.701,P=0.01),3.618(95%CI:1.288-10.163,P=0.02).According to the results of Logistic regression analysis,the prediction model is determined,the ROC curve is drawn,and the AUC value under the curve is calculated to be 0.877(95%CI:0.821-0.933,P<0.01).Conclusion For<1 cm solid pulmonary nodules,among many factors,the longest diameter,Max CT value,lobulation sign and spiculation sign are more important in distinguishing malignant pulmonary nodules from intrapulmonary lymph nodes.