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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

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 pati...

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Formato: Online Artículo Texto
Lenguaje:English
Publicado: 中国肺癌杂志编辑部 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936085/
https://www.ncbi.nlm.nih.gov/pubmed/33508896
http://dx.doi.org/10.3779/j.issn.1009-3419.2021.102.05
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collection PubMed
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 (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.
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spelling pubmed-79360852021-03-19 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 Zhongguo Fei Ai Za Zhi 临床研究 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. 中国肺癌杂志编辑部 2021-02-20 /pmc/articles/PMC7936085/ /pubmed/33508896 http://dx.doi.org/10.3779/j.issn.1009-3419.2021.102.05 Text en 版权所有©《中国肺癌杂志》编辑部2021 This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 3.0) License. See: https://creativecommons.org/licenses/by/3.0/.
spellingShingle 临床研究
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic 临床研究
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936085/
https://www.ncbi.nlm.nih.gov/pubmed/33508896
http://dx.doi.org/10.3779/j.issn.1009-3419.2021.102.05
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