山东医药2019，Vol.59Issue(5)：5-8,4.DOI:10.3969/j.issn.1002-266X.2019.05.002
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
摘要
Abstract
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 onCT, 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.关键词
孤立性肺结节/危险因素/预测模型/计算机断层扫描Key words
solitary pulmonary nodules/risk factors/predictive models/computed tomography分类
医药卫生引用本文复制引用
卢兴时,仲毅,王小雷,马金山..恶性孤立性肺结节的危险因素分析及预测模型建立[J].山东医药,2019,59(5):5-8,4.基金项目
新疆维吾尔自治区自然科学基金资助项目(2015211C193) （2015211C193）
