TY - JOUR
T1 - Data-based radiation oncology
T2 - Design of clinical trials in the toxicity biomarkers era
AU - Azria, David
AU - Lapierre, Ariane
AU - Gourgou, Sophie
AU - De Ruysscher, Dirk
AU - Colinge, Jacques
AU - Lambin, Philippe
AU - Brengues, Muriel
AU - Ward, Tim
AU - Bentzen, Søren M.
AU - Thierens, Hubert
AU - Rancati, Tiziana
AU - Talbot, Christopher J.
AU - Vega, Ana
AU - Kerns, Sarah L.
AU - Andreassen, Christian Nicolaj
AU - Chang-Claude, Jenny
AU - West, Catharine M.L.
AU - Gill, Corey M.
AU - Rosenstein, Barry S.
N1 - Publisher Copyright:
© 2017 Azria, Lapierre, Gourgou, De Ruysscher, Colinge, Lambin, Brengues, Ward, Bentzen, Thierens, Rancati, Talbot, Vega, Kerns, Andreassen, Chang-Claude, West, Gill and Rosenstein.
PY - 2017/4/27
Y1 - 2017/4/27
N2 - 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.
AB - 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.
KW - Biomarkers
KW - Patient selection
KW - Radiotherapy
KW - Toxicity tests
KW - Trial design
UR - http://www.scopus.com/inward/record.url?scp=85019032512&partnerID=8YFLogxK
U2 - 10.3389/fonc.2017.00083
DO - 10.3389/fonc.2017.00083
M3 - Short survey
AN - SCOPUS:85019032512
SN - 2234-943X
VL - 7
JO - Frontiers in Oncology
JF - Frontiers in Oncology
IS - APR
M1 - 83
ER -