title: Optimal design and patient selection for interventional trials using radiogenomic biomarkers: A REQUITE and Radiogenomics consortium statement.
abstract: The optimal design and patient selection for interventional trials in radiogenomics seem trivial at first sight. However, radiogenomics do not give binary information like in e.g. targetable mutation biomarkers. Here, the risk to develop severe side effects is continuous, with increasing incidences of side effects with higher doses and/or volumes. In addition, a multi-SNP assay will produce a predicted probability of developing side effects and will require one or more cut-off thresholds for classifying risk into discrete categories. A classical biomarker trial design is therefore not optimal, whereas a risk factor stratification approach is more appropriate. Patient selection is crucial and this should be based on the dose-response relations for a specific endpoint. Alternatives to standard treatment should be available and this should take into account the preferences of patients. This will be discussed in detail.
authors.affiliation: Maastricht University Medical Center, Department of Radiation Oncology (MAASTRO Clinic), The Netherlands; KU Leuven, Radiation Oncology, Belgium. Electronic address: dirk.deruysscher@maastro.nl.
authors.forename: Dirk
authors.initials: D
authors.lastname: De Ruysscher
authors.affiliation: KU Leuven, Radiation Oncology, Belgium.
authors.forename: Gilles
authors.initials: G
authors.lastname: Defraene
authors.affiliation: Department of Clinical Epidemiology and Medical Technology Assessment, Maastricht University Medical Centre, The Netherlands.
authors.forename: Bram L T
authors.initials: BLT
authors.lastname: Ramaekers
authors.affiliation: Maastricht University Medical Center, Department of Radiation Oncology (MAASTRO Clinic), The Netherlands.
authors.forename: Philippe
authors.initials: P
authors.lastname: Lambin
authors.affiliation: Patient Advocate, Hasselt, Belgium.
authors.forename: Erik
authors.initials: E
authors.lastname: Briers
authors.affiliation: Patient Advocate, Cambridge, UK.
authors.forename: Hilary
authors.initials: H
authors.lastname: Stobart
authors.affiliation: Patient Advocate, Manchester, UK.
authors.forename: Tim
authors.initials: T
authors.lastname: Ward
authors.affiliation: University of Maryland, School of Medicine, USA.
authors.forename: Søren M
authors.initials: SM
authors.lastname: Bentzen
authors.affiliation: The University of Manchester, Manchester Academic Health Science Centre, UK.
authors.forename: Tjeerd
authors.initials: T
authors.lastname: Van Staa
authors.affiliation: Department of Radiation Oncology and Medical Physics, Institut Regional du Cancer Montpellier, France.
authors.forename: David
authors.initials: D
authors.lastname: Azria
authors.affiliation: Department of Radiation Oncology and Medical Physics, Institut Regional du Cancer Montpellier, France.
authors.forename: Barry
authors.initials: B
authors.lastname: Rosenstein
authors.affiliation: University of Rochester Medical Center, USA.
authors.forename: Sarah
authors.initials: S
authors.lastname: Kerns
authors.affiliation: The University of Manchester, Translational Radiobiology Group I Institute of Cancer Sciences, The Christie NHS Foundation Trust, UK.
authors.forename: Catharine
authors.initials: C
authors.lastname: West
mesh_terms: D035843:Biomedical Research / Q000379:methods; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease; D023281:Genomics / Q000379:methods*; D006801:Humans; D009369:Neoplasms / Q000532:radiotherapy*; D018579:Patient Selection; D011832:Radiation Injuries / Q000209:etiology / Q000235:genetics*; D011878:Radiotherapy / Q000009:adverse effects; D011879:Radiotherapy Dosage; D012107:Research Design; D018570:Risk Assessment / Q000379:methods
chemical_list: D005819:Genetic Markers
keywords: Biomarkers; Patient selection; Radiogenomics; Trial design