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EGFR plasma mutation in prediction models for resistance with EGFR TKI and survival of non-small cell lung cancer

BACKGROUND: This study aims to clarify the prognostic role of epidermal growth factor receptor (EGFR) mutations in plasma of non-small cell lung cancer (NSCLC) for resistance to tyrosine kinase inhibitor (TKI), in correlation with clinical characteristics. A total of 94 Adenocarcinoma, clinical stag...

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Autores principales: Phan, Thang Thanh, Tran, Bich-Thu, Nguyen, Son Truong, Ho, Toan Trong, Nguyen, Hang Thuy, Le, Vu Thuong, Le, Anh Tuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339636/
https://www.ncbi.nlm.nih.gov/pubmed/30661185
http://dx.doi.org/10.1186/s40169-019-0219-8
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author Phan, Thang Thanh
Tran, Bich-Thu
Nguyen, Son Truong
Ho, Toan Trong
Nguyen, Hang Thuy
Le, Vu Thuong
Le, Anh Tuan
author_facet Phan, Thang Thanh
Tran, Bich-Thu
Nguyen, Son Truong
Ho, Toan Trong
Nguyen, Hang Thuy
Le, Vu Thuong
Le, Anh Tuan
author_sort Phan, Thang Thanh
collection PubMed
description BACKGROUND: This study aims to clarify the prognostic role of epidermal growth factor receptor (EGFR) mutations in plasma of non-small cell lung cancer (NSCLC) for resistance to tyrosine kinase inhibitor (TKI), in correlation with clinical characteristics. A total of 94 Adenocarcinoma, clinical stage IV NSCLC patients with either E19del or L858R mutation were admitted to the prospective study from Jan-2016 to Jul-2018. EGFR mutations in plasma were detected by scorpions ARMS method. The Kaplan–Meier and Cox regression methods were used to estimate and test the difference of progression-free survival (PFS) and overall survival (OS) between groups. The prognostic power of each factor was appraised by the Bayesian Model Averaging (BMA) method. RESULTS: Among 94 patients, 28 cases still are good responses according to the RECIST criteria and negative for EGFR mutations in plasma. Of 66 resistant patients, EGFR mutations were positive in plasma of 57 cases (86.4%) which was higher than the value of pre-treatment (48.5%). Of which, 17 patients (25.8%) have the occurrence of EGFR mutations in plasma earlier than progression 2.1 (0.6–7.9) months. The secondary T790M mutation was found in the plasma of 32 cases (48.5%). Median PFS and OS for the study subjects were 12.9 (11.0–14.2) and 29.5 (25.2–41.3) months, respectively. The post-treatment EGFR plasma test with brain and new metastasis were detected as independent prognostic factors for worse PFS (P = 0.008, 0.016 and 0.028, respectively). While EGFR plasma (P = 0.044) with bone metastasis at baseline (P = 0.012), new metastasis (P = 0.003), and high cfDNA concentration (P = 0.004) serve as the worse survival factors, surgery treatment helps to prolong OS in NSCLC treated with EGFR TKI (P = 0.012). BMA analysis identified EGFR plasma test as the strongest prognostic factor for both PFS and OS (possibility of 100% and 99.7%, respectively). CONCLUSIONS: EGFR plasma test is the powerfully prognostic factor for early resistance with EGFR TKI and worse survival in NSCLC regardless of clinical characteristics.
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spelling pubmed-63396362019-02-02 EGFR plasma mutation in prediction models for resistance with EGFR TKI and survival of non-small cell lung cancer Phan, Thang Thanh Tran, Bich-Thu Nguyen, Son Truong Ho, Toan Trong Nguyen, Hang Thuy Le, Vu Thuong Le, Anh Tuan Clin Transl Med Research BACKGROUND: This study aims to clarify the prognostic role of epidermal growth factor receptor (EGFR) mutations in plasma of non-small cell lung cancer (NSCLC) for resistance to tyrosine kinase inhibitor (TKI), in correlation with clinical characteristics. A total of 94 Adenocarcinoma, clinical stage IV NSCLC patients with either E19del or L858R mutation were admitted to the prospective study from Jan-2016 to Jul-2018. EGFR mutations in plasma were detected by scorpions ARMS method. The Kaplan–Meier and Cox regression methods were used to estimate and test the difference of progression-free survival (PFS) and overall survival (OS) between groups. The prognostic power of each factor was appraised by the Bayesian Model Averaging (BMA) method. RESULTS: Among 94 patients, 28 cases still are good responses according to the RECIST criteria and negative for EGFR mutations in plasma. Of 66 resistant patients, EGFR mutations were positive in plasma of 57 cases (86.4%) which was higher than the value of pre-treatment (48.5%). Of which, 17 patients (25.8%) have the occurrence of EGFR mutations in plasma earlier than progression 2.1 (0.6–7.9) months. The secondary T790M mutation was found in the plasma of 32 cases (48.5%). Median PFS and OS for the study subjects were 12.9 (11.0–14.2) and 29.5 (25.2–41.3) months, respectively. The post-treatment EGFR plasma test with brain and new metastasis were detected as independent prognostic factors for worse PFS (P = 0.008, 0.016 and 0.028, respectively). While EGFR plasma (P = 0.044) with bone metastasis at baseline (P = 0.012), new metastasis (P = 0.003), and high cfDNA concentration (P = 0.004) serve as the worse survival factors, surgery treatment helps to prolong OS in NSCLC treated with EGFR TKI (P = 0.012). BMA analysis identified EGFR plasma test as the strongest prognostic factor for both PFS and OS (possibility of 100% and 99.7%, respectively). CONCLUSIONS: EGFR plasma test is the powerfully prognostic factor for early resistance with EGFR TKI and worse survival in NSCLC regardless of clinical characteristics. Springer Berlin Heidelberg 2019-01-19 /pmc/articles/PMC6339636/ /pubmed/30661185 http://dx.doi.org/10.1186/s40169-019-0219-8 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Phan, Thang Thanh
Tran, Bich-Thu
Nguyen, Son Truong
Ho, Toan Trong
Nguyen, Hang Thuy
Le, Vu Thuong
Le, Anh Tuan
EGFR plasma mutation in prediction models for resistance with EGFR TKI and survival of non-small cell lung cancer
title EGFR plasma mutation in prediction models for resistance with EGFR TKI and survival of non-small cell lung cancer
title_full EGFR plasma mutation in prediction models for resistance with EGFR TKI and survival of non-small cell lung cancer
title_fullStr EGFR plasma mutation in prediction models for resistance with EGFR TKI and survival of non-small cell lung cancer
title_full_unstemmed EGFR plasma mutation in prediction models for resistance with EGFR TKI and survival of non-small cell lung cancer
title_short EGFR plasma mutation in prediction models for resistance with EGFR TKI and survival of non-small cell lung cancer
title_sort egfr plasma mutation in prediction models for resistance with egfr tki and survival of non-small cell lung cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339636/
https://www.ncbi.nlm.nih.gov/pubmed/30661185
http://dx.doi.org/10.1186/s40169-019-0219-8
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