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DOI 10.3779/j.issn.1009-3419.2021.102.05

Медицинская библиотека · Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2021

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

Tang Jizheng, Liu Chunquan, Wang Peihao, Cui Yong

СтатьяПеревод пока не подготовлен

Аннотация

BACKGROUND

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 (χ² 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).

CONCLUSIONS

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.

Для цитирования: Tang Jizheng, Liu Chunquan, Wang Peihao, Cui Yong. [Multivariate Analysis of Solid Pulmonary Nodules Smaller than 1 cm in 
Distinguishing Lung Cancer from Intrapulmonary Lymph Nodes].. Zhongguo fei ai za zhi = Chinese journal of lung cancer. 2021. DOI: 10.3779/j.issn.1009-3419.2021.102.05.

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