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Data-Based Radiation Oncology: Design of Clinical Trials in the Toxicity Biomarkers Era
The ability to stratify patients using a set of biomarkers, which predict that toxicity risk would allow for radiotherapy (RT) modulation and serve as a valuable tool for precision medicine and personalized RT. For patients presenting with tumors with a low risk of recurrence, modifying RT schedules...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5406456/ https://www.ncbi.nlm.nih.gov/pubmed/28497027 http://dx.doi.org/10.3389/fonc.2017.00083 |
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author | Azria, David Lapierre, Ariane Gourgou, Sophie De Ruysscher, Dirk Colinge, Jacques Lambin, Philippe Brengues, Muriel Ward, Tim Bentzen, Søren M. Thierens, Hubert Rancati, Tiziana Talbot, Christopher J. Vega, Ana Kerns, Sarah L. Andreassen, Christian Nicolaj Chang-Claude, Jenny West, Catharine M. L. Gill, Corey M. Rosenstein, Barry S. |
author_facet | Azria, David Lapierre, Ariane Gourgou, Sophie De Ruysscher, Dirk Colinge, Jacques Lambin, Philippe Brengues, Muriel Ward, Tim Bentzen, Søren M. Thierens, Hubert Rancati, Tiziana Talbot, Christopher J. Vega, Ana Kerns, Sarah L. Andreassen, Christian Nicolaj Chang-Claude, Jenny West, Catharine M. L. Gill, Corey M. Rosenstein, Barry S. |
author_sort | Azria, David |
collection | PubMed |
description | The ability to stratify patients using a set of biomarkers, which predict that toxicity risk would allow for radiotherapy (RT) modulation and serve as a valuable tool for precision medicine and personalized RT. For patients presenting with tumors with a low risk of recurrence, modifying RT schedules to avoid toxicity would be clinically advantageous. Indeed, for the patient at low risk of developing radiation-associated toxicity, use of a hypofractionated protocol could be proposed leading to treatment time reduction and a cost–utility advantage. Conversely, for patients predicted to be at high risk for toxicity, either a more conformal form or a new technique of RT, or a multidisciplinary approach employing surgery could be included in the trial design to avoid or mitigate RT when the potential toxicity risk may be higher than the risk of disease recurrence. In addition, for patients at high risk of recurrence and low risk of toxicity, dose escalation, such as a greater boost dose, or irradiation field extensions could be considered to improve local control without severe toxicities, providing enhanced clinical benefit. In cases of high risk of toxicity, tumor control should be prioritized. In this review, toxicity biomarkers with sufficient evidence for clinical testing are presented. In addition, clinical trial designs and predictive models are described for different clinical situations. |
format | Online Article Text |
id | pubmed-5406456 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-54064562017-05-11 Data-Based Radiation Oncology: Design of Clinical Trials in the Toxicity Biomarkers Era Azria, David Lapierre, Ariane Gourgou, Sophie De Ruysscher, Dirk Colinge, Jacques Lambin, Philippe Brengues, Muriel Ward, Tim Bentzen, Søren M. Thierens, Hubert Rancati, Tiziana Talbot, Christopher J. Vega, Ana Kerns, Sarah L. Andreassen, Christian Nicolaj Chang-Claude, Jenny West, Catharine M. L. Gill, Corey M. Rosenstein, Barry S. Front Oncol Oncology The ability to stratify patients using a set of biomarkers, which predict that toxicity risk would allow for radiotherapy (RT) modulation and serve as a valuable tool for precision medicine and personalized RT. For patients presenting with tumors with a low risk of recurrence, modifying RT schedules to avoid toxicity would be clinically advantageous. Indeed, for the patient at low risk of developing radiation-associated toxicity, use of a hypofractionated protocol could be proposed leading to treatment time reduction and a cost–utility advantage. Conversely, for patients predicted to be at high risk for toxicity, either a more conformal form or a new technique of RT, or a multidisciplinary approach employing surgery could be included in the trial design to avoid or mitigate RT when the potential toxicity risk may be higher than the risk of disease recurrence. In addition, for patients at high risk of recurrence and low risk of toxicity, dose escalation, such as a greater boost dose, or irradiation field extensions could be considered to improve local control without severe toxicities, providing enhanced clinical benefit. In cases of high risk of toxicity, tumor control should be prioritized. In this review, toxicity biomarkers with sufficient evidence for clinical testing are presented. In addition, clinical trial designs and predictive models are described for different clinical situations. Frontiers Media S.A. 2017-04-27 /pmc/articles/PMC5406456/ /pubmed/28497027 http://dx.doi.org/10.3389/fonc.2017.00083 Text en Copyright © 2017 Azria, Lapierre, Gourgou, De Ruysscher, Colinge, Lambin, Brengues, Ward, Bentzen, Thierens, Rancati, Talbot, Vega, Kerns, Andreassen, Chang-Claude, West, Gill and Rosenstein. 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) or licensor 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 Azria, David Lapierre, Ariane Gourgou, Sophie De Ruysscher, Dirk Colinge, Jacques Lambin, Philippe Brengues, Muriel Ward, Tim Bentzen, Søren M. Thierens, Hubert Rancati, Tiziana Talbot, Christopher J. Vega, Ana Kerns, Sarah L. Andreassen, Christian Nicolaj Chang-Claude, Jenny West, Catharine M. L. Gill, Corey M. Rosenstein, Barry S. Data-Based Radiation Oncology: Design of Clinical Trials in the Toxicity Biomarkers Era |
title | Data-Based Radiation Oncology: Design of Clinical Trials in the Toxicity Biomarkers Era |
title_full | Data-Based Radiation Oncology: Design of Clinical Trials in the Toxicity Biomarkers Era |
title_fullStr | Data-Based Radiation Oncology: Design of Clinical Trials in the Toxicity Biomarkers Era |
title_full_unstemmed | Data-Based Radiation Oncology: Design of Clinical Trials in the Toxicity Biomarkers Era |
title_short | Data-Based Radiation Oncology: Design of Clinical Trials in the Toxicity Biomarkers Era |
title_sort | data-based radiation oncology: design of clinical trials in the toxicity biomarkers era |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5406456/ https://www.ncbi.nlm.nih.gov/pubmed/28497027 http://dx.doi.org/10.3389/fonc.2017.00083 |
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