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Nomogram based on preoperative CT imaging predicts the EGFR mutation status in lung adenocarcinoma

Authors :
Guojin Zhang
Jing Zhang
Yuntai Cao
Zhiyong Zhao
Shenglin Li
Liangna Deng
Junlin Zhou
Source :
Translational Oncology, Vol 14, Iss 1, Pp 100954- (2021)
Publication Year :
2021
Publisher :
Elsevier, 2021.

Abstract

Tyrosine kinase inhibitors (TKIs) provide clinical benefits to the lung cancer patients with epidermal growth factor receptor (EGFR) mutations. However, non-invasively determine EGFR mutation status in patients before targeted therapy remains a challenge. This study aimed to develop and validate a nomogram for preoperative prediction of EGFR mutation status in patients with lung adenocarcinoma. The medical records of 403 patients with lung adenocarcinoma confirmed by histology from January 2016 to June 2020 were retrospectively collected. We combined CT features and clinical risk factors and used them to build a prediction nomogram. The performance of the nomogram was evaluated in terms of calibration, discrimination, and clinical usefulness. The nomogram was further validated in an independent external cohort. Finally, a nomogram that contained CT features and clinical risk factors, which could conveniently and non-invasively predict EGFR mutation status in patients with lung adenocarcinoma before surgery.

Details

Language :
English
ISSN :
19365233
Volume :
14
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Translational Oncology
Publication Type :
Academic Journal
Accession number :
edsdoj.0d05bbde34604f5d8edf35fa3e90d771
Document Type :
article
Full Text :
https://doi.org/10.1016/j.tranon.2020.100954