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Nomogram based on preoperative CT imaging predicts the EGFR mutation status in lung adenocarcinoma
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 n...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Neoplasia Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7691609/ https://www.ncbi.nlm.nih.gov/pubmed/33232920 http://dx.doi.org/10.1016/j.tranon.2020.100954 |
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author | Zhang, Guojin Zhang, Jing Cao, Yuntai Zhao, Zhiyong Li, Shenglin Deng, Liangna Zhou, Junlin |
author_facet | Zhang, Guojin Zhang, Jing Cao, Yuntai Zhao, Zhiyong Li, Shenglin Deng, Liangna Zhou, Junlin |
author_sort | Zhang, Guojin |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7691609 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Neoplasia Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-76916092020-12-09 Nomogram based on preoperative CT imaging predicts the EGFR mutation status in lung adenocarcinoma Zhang, Guojin Zhang, Jing Cao, Yuntai Zhao, Zhiyong Li, Shenglin Deng, Liangna Zhou, Junlin Transl Oncol Original article 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. Neoplasia Press 2020-11-21 /pmc/articles/PMC7691609/ /pubmed/33232920 http://dx.doi.org/10.1016/j.tranon.2020.100954 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Original article Zhang, Guojin Zhang, Jing Cao, Yuntai Zhao, Zhiyong Li, Shenglin Deng, Liangna Zhou, Junlin Nomogram based on preoperative CT imaging predicts the EGFR mutation status in lung adenocarcinoma |
title | Nomogram based on preoperative CT imaging predicts the EGFR mutation status in lung adenocarcinoma |
title_full | Nomogram based on preoperative CT imaging predicts the EGFR mutation status in lung adenocarcinoma |
title_fullStr | Nomogram based on preoperative CT imaging predicts the EGFR mutation status in lung adenocarcinoma |
title_full_unstemmed | Nomogram based on preoperative CT imaging predicts the EGFR mutation status in lung adenocarcinoma |
title_short | Nomogram based on preoperative CT imaging predicts the EGFR mutation status in lung adenocarcinoma |
title_sort | nomogram based on preoperative ct imaging predicts the egfr mutation status in lung adenocarcinoma |
topic | Original article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7691609/ https://www.ncbi.nlm.nih.gov/pubmed/33232920 http://dx.doi.org/10.1016/j.tranon.2020.100954 |
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