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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...

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Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
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.
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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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