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

Abstract 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 findin...

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Autores principales:	Xiaoyu Han, Jun Fan, Yumin Li, Yukun Cao, Jin Gu, Xi Jia, Yuhui Wang, Heshui Shi
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/bfbca12fd1d94d028d0094be93f511ee
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spelling	oai:doaj.org-article:bfbca12fd1d94d028d0094be93f511ee2021-12-02T11:37:26ZValue of CT features for predicting EGFR mutations and ALK positivity in patients with lung adenocarcinoma10.1038/s41598-021-83646-72045-2322https://doaj.org/article/bfbca12fd1d94d028d0094be93f511ee2021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-83646-7https://doaj.org/toc/2045-2322Abstract 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.Xiaoyu HanJun FanYumin LiYukun CaoJin GuXi JiaYuhui WangHeshui ShiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Xiaoyu Han Jun Fan Yumin Li Yukun Cao Jin Gu Xi Jia Yuhui Wang Heshui Shi Value of CT features for predicting EGFR mutations and ALK positivity in patients with lung adenocarcinoma
description	Abstract 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.
format	article
author	Xiaoyu Han Jun Fan Yumin Li Yukun Cao Jin Gu Xi Jia Yuhui Wang Heshui Shi
author_facet	Xiaoyu Han Jun Fan Yumin Li Yukun Cao Jin Gu Xi Jia Yuhui Wang Heshui Shi
author_sort	Xiaoyu Han
title	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_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_sort	value of ct features for predicting egfr mutations and alk positivity in patients with lung adenocarcinoma
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/bfbca12fd1d94d028d0094be93f511ee
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Value of CT features for predicting EGFR mutations and ALK positivity in patients with lung adenocarcinoma

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