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Mathematical prediction model of computed tomography signs is superior to intraoperative frozen section in the diagnosis of ground‐glass nodular invasive adenocarcinoma of the lung
BACKGROUND: At present, lobectomy is still the standard treatment for lung cancer. Judging whether a lesion is invasive adenocarcinoma (IA) has important guiding significance for determining the scope of surgical resection. The commonly used methods are intraoperative frozen sections and computed to...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons Australia, Ltd
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8410573/ https://www.ncbi.nlm.nih.gov/pubmed/34310857 http://dx.doi.org/10.1111/1759-7714.14082 |
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author | Tang, Jizheng Cui, Yong Li, Bowen Xue, Xingxing Tian, Feng |
author_facet | Tang, Jizheng Cui, Yong Li, Bowen Xue, Xingxing Tian, Feng |
author_sort | Tang, Jizheng |
collection | PubMed |
description | BACKGROUND: At present, lobectomy is still the standard treatment for lung cancer. Judging whether a lesion is invasive adenocarcinoma (IA) has important guiding significance for determining the scope of surgical resection. The commonly used methods are intraoperative frozen sections and computed tomography (CT) signs. There is still controversy about the accuracy of both in judging the invasiveness of ground‐glass nodules (GGNs). METHODS: The clinical data of patients with GGNs who underwent surgery were collected. According to the results of univariate analysis, 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 in order to achieve the area under the curve (AUC) value. RESULTS: According to the results of logistic regression analysis, the longest diameter and maximum CT value of nodules were independent risk factors for IA. The mathematical prediction model of CT signs was determined, and the ROC curves of CT signs and intraoperative frozen sections (FS) were drawn, respectively. The AUC values under the curves were calculated to be 0.873 and 0.807, respectively. The mathematical prediction model of intraoperative frozen section combined with CT signs was established. A ROC curve was drawn and the AUC was calculated to be 0.925. CONCLUSIONS: The diagnostic accuracy of CT signs in judging whether nonbenign GGNs were IA was higher than that of intraoperative FS. Combined with CT signs and intraoperative FS to establish a mathematical prediction model, the diagnostic accuracy of judging whether nonbenign GGNs are IA is significantly improved. |
format | Online Article Text |
id | pubmed-8410573 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley & Sons Australia, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-84105732021-09-03 Mathematical prediction model of computed tomography signs is superior to intraoperative frozen section in the diagnosis of ground‐glass nodular invasive adenocarcinoma of the lung Tang, Jizheng Cui, Yong Li, Bowen Xue, Xingxing Tian, Feng Thorac Cancer Original Articles BACKGROUND: At present, lobectomy is still the standard treatment for lung cancer. Judging whether a lesion is invasive adenocarcinoma (IA) has important guiding significance for determining the scope of surgical resection. The commonly used methods are intraoperative frozen sections and computed tomography (CT) signs. There is still controversy about the accuracy of both in judging the invasiveness of ground‐glass nodules (GGNs). METHODS: The clinical data of patients with GGNs who underwent surgery were collected. According to the results of univariate analysis, 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 in order to achieve the area under the curve (AUC) value. RESULTS: According to the results of logistic regression analysis, the longest diameter and maximum CT value of nodules were independent risk factors for IA. The mathematical prediction model of CT signs was determined, and the ROC curves of CT signs and intraoperative frozen sections (FS) were drawn, respectively. The AUC values under the curves were calculated to be 0.873 and 0.807, respectively. The mathematical prediction model of intraoperative frozen section combined with CT signs was established. A ROC curve was drawn and the AUC was calculated to be 0.925. CONCLUSIONS: The diagnostic accuracy of CT signs in judging whether nonbenign GGNs were IA was higher than that of intraoperative FS. Combined with CT signs and intraoperative FS to establish a mathematical prediction model, the diagnostic accuracy of judging whether nonbenign GGNs are IA is significantly improved. John Wiley & Sons Australia, Ltd 2021-07-26 2021-09 /pmc/articles/PMC8410573/ /pubmed/34310857 http://dx.doi.org/10.1111/1759-7714.14082 Text en © 2021 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Original Articles Tang, Jizheng Cui, Yong Li, Bowen Xue, Xingxing Tian, Feng Mathematical prediction model of computed tomography signs is superior to intraoperative frozen section in the diagnosis of ground‐glass nodular invasive adenocarcinoma of the lung |
title | Mathematical prediction model of computed tomography signs is superior to intraoperative frozen section in the diagnosis of ground‐glass nodular invasive adenocarcinoma of the lung |
title_full | Mathematical prediction model of computed tomography signs is superior to intraoperative frozen section in the diagnosis of ground‐glass nodular invasive adenocarcinoma of the lung |
title_fullStr | Mathematical prediction model of computed tomography signs is superior to intraoperative frozen section in the diagnosis of ground‐glass nodular invasive adenocarcinoma of the lung |
title_full_unstemmed | Mathematical prediction model of computed tomography signs is superior to intraoperative frozen section in the diagnosis of ground‐glass nodular invasive adenocarcinoma of the lung |
title_short | Mathematical prediction model of computed tomography signs is superior to intraoperative frozen section in the diagnosis of ground‐glass nodular invasive adenocarcinoma of the lung |
title_sort | mathematical prediction model of computed tomography signs is superior to intraoperative frozen section in the diagnosis of ground‐glass nodular invasive adenocarcinoma of the lung |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8410573/ https://www.ncbi.nlm.nih.gov/pubmed/34310857 http://dx.doi.org/10.1111/1759-7714.14082 |
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