Multivariate Analysis of Solid Pulmonary Nodules Smaller than 1 cm in Distinguishing Lung Cancer from Intrapulmonary Lymph Nodes
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 patie...
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| Format: | Article |
| Language: | zho |
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Chinese Anti-Cancer Association; Chinese Antituberculosis Association
2021-02-01
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| Series: | Chinese Journal of Lung Cancer |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.3779/j.issn.1009-3419.2021.102.05 |
| _version_ | 1828888899094577152 |
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| author | Jizheng TANG Chunquan LIU Peihao WANG Yong CUI |
| author_facet | Jizheng TANG Chunquan LIU Peihao WANG Yong CUI |
| author_sort | Jizheng TANG |
| collection | DOAJ |
| description | 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 (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). 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. |
| first_indexed | 2024-12-13T12:31:51Z |
| format | Article |
| id | doaj.art-dc18fd3743ad40718253657e7e7996ad |
| institution | Directory Open Access Journal |
| issn | 1009-3419 1999-6187 |
| language | zho |
| last_indexed | 2024-12-13T12:31:51Z |
| publishDate | 2021-02-01 |
| publisher | Chinese Anti-Cancer Association; Chinese Antituberculosis Association |
| record_format | Article |
| series | Chinese Journal of Lung Cancer |
| spelling | doaj.art-dc18fd3743ad40718253657e7e7996ad2022-12-21T23:46:01ZzhoChinese Anti-Cancer Association; Chinese Antituberculosis AssociationChinese Journal of Lung Cancer1009-34191999-61872021-02-01242949810.3779/j.issn.1009-3419.2021.102.05Multivariate Analysis of Solid Pulmonary Nodules Smaller than 1 cm in
Distinguishing Lung Cancer from Intrapulmonary Lymph NodesJizheng TANG0Chunquan LIU1Peihao WANG2Yong CUI3Department of Thoracic Surgery, Beijing Friendship Hospital of Capital Medical University, Beijing 100050, ChinaDepartment of Thoracic Surgery, Beijing Friendship Hospital of Capital Medical University, Beijing 100050, ChinaDepartment of Thoracic Surgery, Beijing Friendship Hospital of Capital Medical University, Beijing 100050, ChinaDepartment of Thoracic Surgery, Beijing Friendship Hospital of Capital Medical University, Beijing 100050, ChinaBackground 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 (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). 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.http://dx.doi.org/10.3779/j.issn.1009-3419.2021.102.05solid pulmonary nodulesintrapulmonary lymph nodesmalignant pulmonary nodulesreceiver operating characteristic (roc) curve |
| spellingShingle | Jizheng TANG Chunquan LIU Peihao WANG Yong CUI Multivariate Analysis of Solid Pulmonary Nodules Smaller than 1 cm in Distinguishing Lung Cancer from Intrapulmonary Lymph Nodes Chinese Journal of Lung Cancer solid pulmonary nodules intrapulmonary lymph nodes malignant pulmonary nodules receiver operating characteristic (roc) curve |
| title | Multivariate Analysis of Solid Pulmonary Nodules Smaller than 1 cm in
Distinguishing Lung Cancer from Intrapulmonary Lymph Nodes |
| title_full | Multivariate Analysis of Solid Pulmonary Nodules Smaller than 1 cm in
Distinguishing Lung Cancer from Intrapulmonary Lymph Nodes |
| title_fullStr | Multivariate Analysis of Solid Pulmonary Nodules Smaller than 1 cm in
Distinguishing Lung Cancer from Intrapulmonary Lymph Nodes |
| title_full_unstemmed | Multivariate Analysis of Solid Pulmonary Nodules Smaller than 1 cm in
Distinguishing Lung Cancer from Intrapulmonary Lymph Nodes |
| title_short | Multivariate Analysis of Solid Pulmonary Nodules Smaller than 1 cm in
Distinguishing Lung Cancer from Intrapulmonary Lymph Nodes |
| title_sort | multivariate analysis of solid pulmonary nodules smaller than 1 cm in
distinguishing lung cancer from intrapulmonary lymph nodes |
| topic | solid pulmonary nodules intrapulmonary lymph nodes malignant pulmonary nodules receiver operating characteristic (roc) curve |
| url | http://dx.doi.org/10.3779/j.issn.1009-3419.2021.102.05 |
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