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Value of CT features for predicting EGFR mutations and ALK positivity in patients with lung adenocarcinoma

The aim of this study was to identify the relationships of epidermal growth factor receptor (EGFR) mutations and anaplastic large-cell lymphoma kinase (ALK) status with CT characteristics in adenocarcinoma using the largest patient cohort to date. In this study, preoperative chest CT findings prior...

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Autores principales: Han, Xiaoyu, Fan, Jun, Li, Yumin, Cao, Yukun, Gu, Jin, Jia, Xi, Wang, Yuhui, Shi, Heshui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7952563/
https://www.ncbi.nlm.nih.gov/pubmed/33707479
http://dx.doi.org/10.1038/s41598-021-83646-7
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author Han, Xiaoyu
Fan, Jun
Li, Yumin
Cao, Yukun
Gu, Jin
Jia, Xi
Wang, Yuhui
Shi, Heshui
author_facet Han, Xiaoyu
Fan, Jun
Li, Yumin
Cao, Yukun
Gu, Jin
Jia, Xi
Wang, Yuhui
Shi, Heshui
author_sort Han, Xiaoyu
collection PubMed
description The aim of this study was to identify the relationships of epidermal growth factor receptor (EGFR) mutations and anaplastic large-cell lymphoma kinase (ALK) status with CT characteristics in adenocarcinoma using the largest patient cohort to date. In this study, preoperative chest CT findings prior to treatment were retrospectively evaluated in 827 surgically resected lung adenocarcinomas. All patients were tested for EGFR mutations and ALK status. EGFR mutations were found in 489 (59.1%) patients, and ALK positivity was found in 57 (7.0%). By logistic regression, the most significant independent prognostic factors of EGFR effective mutations were female sex, nonsmoker status, GGO air bronchograms and pleural retraction. For EGFR mutation prediction, receiver operating characteristic (ROC) curves yielded areas under the curve (AUCs) of 0.682 and 0.758 for clinical only or combined CT features, respectively, with a significant difference (p < 0.001). Furthermore, the exon 21 mutation rate in GGO was significantly higher than the exon 19 mutation rate(p = 0.029). The most significant independent prognostic factors of ALK positivity were age, solid-predominant-subtype tumours, mucinous lung adenocarcinoma, solid tumours and no air bronchograms on CT. ROC curve analysis showed that for predicting ALK positivity, the use of clinical variables combined with CT features (AUC = 0.739) was superior to the use of clinical variables alone (AUC = 0.657), with a significant difference (p = 0.0082). The use of CT features for patients may allow analyses of tumours and more accurately predict patient populations who will benefit from therapies targeting treatment.
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spelling pubmed-79525632021-03-12 Value of CT features for predicting EGFR mutations and ALK positivity in patients with lung adenocarcinoma Han, Xiaoyu Fan, Jun Li, Yumin Cao, Yukun Gu, Jin Jia, Xi Wang, Yuhui Shi, Heshui Sci Rep Article The aim of this study was to identify the relationships of epidermal growth factor receptor (EGFR) mutations and anaplastic large-cell lymphoma kinase (ALK) status with CT characteristics in adenocarcinoma using the largest patient cohort to date. In this study, preoperative chest CT findings prior to treatment were retrospectively evaluated in 827 surgically resected lung adenocarcinomas. All patients were tested for EGFR mutations and ALK status. EGFR mutations were found in 489 (59.1%) patients, and ALK positivity was found in 57 (7.0%). By logistic regression, the most significant independent prognostic factors of EGFR effective mutations were female sex, nonsmoker status, GGO air bronchograms and pleural retraction. For EGFR mutation prediction, receiver operating characteristic (ROC) curves yielded areas under the curve (AUCs) of 0.682 and 0.758 for clinical only or combined CT features, respectively, with a significant difference (p < 0.001). Furthermore, the exon 21 mutation rate in GGO was significantly higher than the exon 19 mutation rate(p = 0.029). The most significant independent prognostic factors of ALK positivity were age, solid-predominant-subtype tumours, mucinous lung adenocarcinoma, solid tumours and no air bronchograms on CT. ROC curve analysis showed that for predicting ALK positivity, the use of clinical variables combined with CT features (AUC = 0.739) was superior to the use of clinical variables alone (AUC = 0.657), with a significant difference (p = 0.0082). The use of CT features for patients may allow analyses of tumours and more accurately predict patient populations who will benefit from therapies targeting treatment. Nature Publishing Group UK 2021-03-11 /pmc/articles/PMC7952563/ /pubmed/33707479 http://dx.doi.org/10.1038/s41598-021-83646-7 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Han, Xiaoyu
Fan, Jun
Li, Yumin
Cao, Yukun
Gu, Jin
Jia, Xi
Wang, Yuhui
Shi, Heshui
Value of CT features for predicting EGFR mutations and ALK positivity in patients with lung adenocarcinoma
title Value of CT features for predicting EGFR mutations and ALK positivity in patients with lung adenocarcinoma
title_full Value of CT features for predicting EGFR mutations and ALK positivity in patients with lung adenocarcinoma
title_fullStr Value of CT features for predicting EGFR mutations and ALK positivity in patients with lung adenocarcinoma
title_full_unstemmed Value of CT features for predicting EGFR mutations and ALK positivity in patients with lung adenocarcinoma
title_short Value of CT features for predicting EGFR mutations and ALK positivity in patients with lung adenocarcinoma
title_sort value of ct features for predicting egfr mutations and alk positivity in patients with lung adenocarcinoma
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7952563/
https://www.ncbi.nlm.nih.gov/pubmed/33707479
http://dx.doi.org/10.1038/s41598-021-83646-7
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