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Predicting Outcomes From Radical Radiotherapy for Non-small Cell Lung Cancer: A Systematic Review of the Existing Literature

Radical radiotherapy (RT) is a potentially curative treatment in non-small cell lung cancer (NSCLC) and is delivered in conventional 2-Gy fractions, hypofractionated and ablative stereotactic courses. No reliable, predictive biomarkers for the clinical events of local control, appearance of distant...

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Autores principales: Walls, Gerard M., Hanna, Gerard G., Qi, Fang, Zhao, Sai, Xia, Jun, Ansari, Mohammed T., Landau, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6191477/
https://www.ncbi.nlm.nih.gov/pubmed/30364202
http://dx.doi.org/10.3389/fonc.2018.00433
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author Walls, Gerard M.
Hanna, Gerard G.
Qi, Fang
Zhao, Sai
Xia, Jun
Ansari, Mohammed T.
Landau, David
author_facet Walls, Gerard M.
Hanna, Gerard G.
Qi, Fang
Zhao, Sai
Xia, Jun
Ansari, Mohammed T.
Landau, David
author_sort Walls, Gerard M.
collection PubMed
description Radical radiotherapy (RT) is a potentially curative treatment in non-small cell lung cancer (NSCLC) and is delivered in conventional 2-Gy fractions, hypofractionated and ablative stereotactic courses. No reliable, predictive biomarkers for the clinical events of local control, appearance of distant metastases and development of toxicity have been introduced in routine clinical practice. Such a test would enable the Radiotherapist to tailor the clinical management of individual patients, considering their pre-treatment characteristics, in order reduce the risk of recurrence or toxicity e.g., dose modification, accelerated fractionation, hypofractionation, or concurrent systemic therapy. The aim of this review was to map the published literature relating to investigations of the potential predictive value of patient or treatment characteristics in radical RT for NSCLC. These investigations should remain a research focus for disease control given the upward trends in lung cancer incidence, and for the avoidance of toxicity, given the survivorship afforded to the cohort of patients that do well with radical RT, or with the increasing range of systemic agents following metastatic relapse. The conclusion of the presented analysis is that there are no published, effective and validated predictive tools for estimation of risk of local/distant recurrence or toxicity after radical RT for NSCLC. The authors have identified an important space for future research in the field of lung cancer radiotherapy.
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spelling pubmed-61914772018-10-24 Predicting Outcomes From Radical Radiotherapy for Non-small Cell Lung Cancer: A Systematic Review of the Existing Literature Walls, Gerard M. Hanna, Gerard G. Qi, Fang Zhao, Sai Xia, Jun Ansari, Mohammed T. Landau, David Front Oncol Oncology Radical radiotherapy (RT) is a potentially curative treatment in non-small cell lung cancer (NSCLC) and is delivered in conventional 2-Gy fractions, hypofractionated and ablative stereotactic courses. No reliable, predictive biomarkers for the clinical events of local control, appearance of distant metastases and development of toxicity have been introduced in routine clinical practice. Such a test would enable the Radiotherapist to tailor the clinical management of individual patients, considering their pre-treatment characteristics, in order reduce the risk of recurrence or toxicity e.g., dose modification, accelerated fractionation, hypofractionation, or concurrent systemic therapy. The aim of this review was to map the published literature relating to investigations of the potential predictive value of patient or treatment characteristics in radical RT for NSCLC. These investigations should remain a research focus for disease control given the upward trends in lung cancer incidence, and for the avoidance of toxicity, given the survivorship afforded to the cohort of patients that do well with radical RT, or with the increasing range of systemic agents following metastatic relapse. The conclusion of the presented analysis is that there are no published, effective and validated predictive tools for estimation of risk of local/distant recurrence or toxicity after radical RT for NSCLC. The authors have identified an important space for future research in the field of lung cancer radiotherapy. Frontiers Media S.A. 2018-10-10 /pmc/articles/PMC6191477/ /pubmed/30364202 http://dx.doi.org/10.3389/fonc.2018.00433 Text en Copyright © 2018 Walls, Hanna, Qi, Zhao, Xia, Ansari and Landau. http://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
Walls, Gerard M.
Hanna, Gerard G.
Qi, Fang
Zhao, Sai
Xia, Jun
Ansari, Mohammed T.
Landau, David
Predicting Outcomes From Radical Radiotherapy for Non-small Cell Lung Cancer: A Systematic Review of the Existing Literature
title Predicting Outcomes From Radical Radiotherapy for Non-small Cell Lung Cancer: A Systematic Review of the Existing Literature
title_full Predicting Outcomes From Radical Radiotherapy for Non-small Cell Lung Cancer: A Systematic Review of the Existing Literature
title_fullStr Predicting Outcomes From Radical Radiotherapy for Non-small Cell Lung Cancer: A Systematic Review of the Existing Literature
title_full_unstemmed Predicting Outcomes From Radical Radiotherapy for Non-small Cell Lung Cancer: A Systematic Review of the Existing Literature
title_short Predicting Outcomes From Radical Radiotherapy for Non-small Cell Lung Cancer: A Systematic Review of the Existing Literature
title_sort predicting outcomes from radical radiotherapy for non-small cell lung cancer: a systematic review of the existing literature
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6191477/
https://www.ncbi.nlm.nih.gov/pubmed/30364202
http://dx.doi.org/10.3389/fonc.2018.00433
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