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New prognostic system specific for epidermal growth factor receptor-mutated lung cancer brain metastasis
INTRODUCTION: Brain metastases (BM) from lung cancer are heterogeneous, and accurate prognosis is required for effective treatment strategies. This study aimed to identify prognostic factors and develop a prognostic system exclusively for epidermal growth factor receptor (EGFR)-mutated lung cancer B...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10067922/ https://www.ncbi.nlm.nih.gov/pubmed/37020869 http://dx.doi.org/10.3389/fonc.2023.1093084 |
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author | Zhu, Li-Hua Fan, Xing-Wen Sun, Lu Ni, Ting-ting Li, Ya-qi Wu, Chao-Yang Wu, Kai-Liang |
author_facet | Zhu, Li-Hua Fan, Xing-Wen Sun, Lu Ni, Ting-ting Li, Ya-qi Wu, Chao-Yang Wu, Kai-Liang |
author_sort | Zhu, Li-Hua |
collection | PubMed |
description | INTRODUCTION: Brain metastases (BM) from lung cancer are heterogeneous, and accurate prognosis is required for effective treatment strategies. This study aimed to identify prognostic factors and develop a prognostic system exclusively for epidermal growth factor receptor (EGFR)-mutated lung cancer BM. METHODS: In total, 173 patients with EGFR-mutated lung cancer from two hospitals who developed BM and received tyrosine kinase inhibitor (TKI) and brain radiation therapy (RT) were included. Univariate and multivariate analyses were performed to identify significant EGFR-mutated BM prognostic factors to construct a new EGFR recursive partitioning analysis (RPA) prognostic index. The predictive discrimination of five prognostic scoring systems including RPA, diagnosis-specific prognostic factors indexes (DS-GPA), basic score for brain metastases (BS-BM), lung cancer using molecular markers (lung-mol GPA) and EGFR-RPA were analyzed using log-rank test, concordance index (C-index), and receiver operating characteristic curve (ROC). The potential predictive factors in the multivariable analysis to construct a prognostic index included Karnofsky performance status, BM at initial lung cancer diagnosis, BM progression after TKI, EGFR mutation type, uncontrolled primary tumors, and number of BM. RESULTS AND DISCUSSION: In the log-rank test, indices of RPA, DS-GPA, lung-mol GPA, BS-BM, and EGFR-RPA were all significant predictors of overall survival (OS) (p ≤ 0.05). The C-indices of each prognostic score were 0.603, 0.569, 0.613, 0.595, and 0.671, respectively; The area under the curve (AUC) values predicting 1-year OS were 0.565 (p=0.215), 0.572 (p=0.174), 0.641 (p=0.007), 0.585 (p=0.106), and 0.781 (p=0.000), respectively. Furthermore, EGFR-RPA performed better in terms of calibration than other prognostic indices.BM progression after TKI and EGFR mutation type were specific prognostic factors for EGFR-mutated lung cancer BM. EGFR-RPA was more precise than other models, and useful for personal treatment. |
format | Online Article Text |
id | pubmed-10067922 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100679222023-04-04 New prognostic system specific for epidermal growth factor receptor-mutated lung cancer brain metastasis Zhu, Li-Hua Fan, Xing-Wen Sun, Lu Ni, Ting-ting Li, Ya-qi Wu, Chao-Yang Wu, Kai-Liang Front Oncol Oncology INTRODUCTION: Brain metastases (BM) from lung cancer are heterogeneous, and accurate prognosis is required for effective treatment strategies. This study aimed to identify prognostic factors and develop a prognostic system exclusively for epidermal growth factor receptor (EGFR)-mutated lung cancer BM. METHODS: In total, 173 patients with EGFR-mutated lung cancer from two hospitals who developed BM and received tyrosine kinase inhibitor (TKI) and brain radiation therapy (RT) were included. Univariate and multivariate analyses were performed to identify significant EGFR-mutated BM prognostic factors to construct a new EGFR recursive partitioning analysis (RPA) prognostic index. The predictive discrimination of five prognostic scoring systems including RPA, diagnosis-specific prognostic factors indexes (DS-GPA), basic score for brain metastases (BS-BM), lung cancer using molecular markers (lung-mol GPA) and EGFR-RPA were analyzed using log-rank test, concordance index (C-index), and receiver operating characteristic curve (ROC). The potential predictive factors in the multivariable analysis to construct a prognostic index included Karnofsky performance status, BM at initial lung cancer diagnosis, BM progression after TKI, EGFR mutation type, uncontrolled primary tumors, and number of BM. RESULTS AND DISCUSSION: In the log-rank test, indices of RPA, DS-GPA, lung-mol GPA, BS-BM, and EGFR-RPA were all significant predictors of overall survival (OS) (p ≤ 0.05). The C-indices of each prognostic score were 0.603, 0.569, 0.613, 0.595, and 0.671, respectively; The area under the curve (AUC) values predicting 1-year OS were 0.565 (p=0.215), 0.572 (p=0.174), 0.641 (p=0.007), 0.585 (p=0.106), and 0.781 (p=0.000), respectively. Furthermore, EGFR-RPA performed better in terms of calibration than other prognostic indices.BM progression after TKI and EGFR mutation type were specific prognostic factors for EGFR-mutated lung cancer BM. EGFR-RPA was more precise than other models, and useful for personal treatment. Frontiers Media S.A. 2023-03-20 /pmc/articles/PMC10067922/ /pubmed/37020869 http://dx.doi.org/10.3389/fonc.2023.1093084 Text en Copyright © 2023 Zhu, Fan, Sun, Ni, Li, Wu and Wu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Zhu, Li-Hua Fan, Xing-Wen Sun, Lu Ni, Ting-ting Li, Ya-qi Wu, Chao-Yang Wu, Kai-Liang New prognostic system specific for epidermal growth factor receptor-mutated lung cancer brain metastasis |
title | New prognostic system specific for epidermal growth factor receptor-mutated lung cancer brain metastasis |
title_full | New prognostic system specific for epidermal growth factor receptor-mutated lung cancer brain metastasis |
title_fullStr | New prognostic system specific for epidermal growth factor receptor-mutated lung cancer brain metastasis |
title_full_unstemmed | New prognostic system specific for epidermal growth factor receptor-mutated lung cancer brain metastasis |
title_short | New prognostic system specific for epidermal growth factor receptor-mutated lung cancer brain metastasis |
title_sort | new prognostic system specific for epidermal growth factor receptor-mutated lung cancer brain metastasis |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10067922/ https://www.ncbi.nlm.nih.gov/pubmed/37020869 http://dx.doi.org/10.3389/fonc.2023.1093084 |
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