TY - JOUR
T1 - Clinical Trial Strategies to Compare Protons With Photons
AU - Langendijk, Johannes A.
AU - Boersma, Liesbeth J.
AU - Rasch, Coen R. N.
AU - van Vulpen, Marco
AU - Reitsma, Johannes B.
AU - van der Schaaf, Arjen
AU - Schuit, Ewoud
N1 - Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
PY - 2018/4
Y1 - 2018/4
N2 - The favorable beam properties of protons can be translated into clinical benefits by target dose escalation to improve local control without enhancing unacceptable radiation toxicity or to spare normal tissues to prevent radiation-induced side effects without jeopardizing local tumor control. For the clinical validation of the added value of protons to improve local control, randomized controlled trials are required. For the clinical validation of the added value of protons to prevent side effects, both model-based validation or randomized controlled trials can be used. Model-based patient selection for proton therapy is crucial, independent of the validation approach. Combining these approaches in rapid learning health care systems is expected to yield the most efficient and scientifically sound way to continuously improve patient selection and the therapeutic window, eventually leading to more cancer survivors with better quality of life. (C) 2018 The Authors. Published by Elsevier Inc.
AB - The favorable beam properties of protons can be translated into clinical benefits by target dose escalation to improve local control without enhancing unacceptable radiation toxicity or to spare normal tissues to prevent radiation-induced side effects without jeopardizing local tumor control. For the clinical validation of the added value of protons to improve local control, randomized controlled trials are required. For the clinical validation of the added value of protons to prevent side effects, both model-based validation or randomized controlled trials can be used. Model-based patient selection for proton therapy is crucial, independent of the validation approach. Combining these approaches in rapid learning health care systems is expected to yield the most efficient and scientifically sound way to continuously improve patient selection and the therapeutic window, eventually leading to more cancer survivors with better quality of life. (C) 2018 The Authors. Published by Elsevier Inc.
KW - INTENSITY-MODULATED RADIOTHERAPY
KW - MODEL-BASED APPROACH
KW - COMPLICATION PROBABILITY-MODELS
KW - TREATMENT PLAN OPTIMIZATION
KW - PATIENT-RATED XEROSTOMIA
KW - TUBE-FEEDING DEPENDENCE
KW - LEARNING HEALTH-CARE
KW - NECK-CANCER
KW - BREAST-CANCER
KW - NTCP MODELS
U2 - 10.1016/j.semradonc.2017.11.008
DO - 10.1016/j.semradonc.2017.11.008
M3 - Article
C2 - 29735194
SN - 1053-4296
VL - 28
SP - 79
EP - 87
JO - Seminars in radiation oncology
JF - Seminars in radiation oncology
IS - 2
ER -