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Mennan, C.* ; Hopkins, T.* ; Channon, A.* ; Elliott, A.* ; Johnstone, B.* ; Kadir, T.* ; Loughlin, J.* ; Peffers, M.* ; Pitsillides, A.* ; Sofat, N.* ; Stewart, C.* ; Watt, F.E.* ; Zeggini, E. ; Holt, C.* ; Roberts, S.*

The use of technology in the subcategorisation of osteoarthritis: A delphi study approach.

Osteoarthr. Cartil. 2:100081 (2020)
Postprint Forschungsdaten DOI
Open Access Hybrid
Creative Commons Lizenzvertrag
ObjectiveThis UK-wide OATech+ Network consensus study utilised a Delphi approach to discern levels. of awareness across an expert panel regarding the role of existing and novel technologies in osteoarthritis research. To direct future cross-disciplinary research it aimed to identify which could be adopted to subcategorise patients with osteoarthritis (OA).DesignAn online questionnaire was formulated based on technologies which might aid OA research and subcategorisation. During a two-day face-to-face meeting concordance of expert opinion was established with surveys (23 questions) before, during and at the end of the meeting (Rounds 1,2 and 3, respectively). Experts spoke on current evidence for imaging, genomics, epigenomics, proteomics, metabolomics, biomarkers, activity monitoring, clinical engineering and machine learning relating to subcategorisation. For each round of voting, ≥80% votes led to consensus and ≤20% to exclusion of a statement.ResultsPanel members were unanimous that a combination of novel technological advances have potential to improve OA diagnostics and treatment through subcategorisation,. agreeing in Rounds 1 and 2 that epigenetics, genetics, MRI, proteomics, wet biomarkers and machine learning could aid subcategorisation. Expert presentations changed participants’ opinions on the value of metabolomics, activity monitoring and clinical engineering, all reaching consensus in Round 2. X-rays lost consensus between Rounds 1 and 2; clinical X-rays reached consensus in Round 3.ConclusionConsensus identified that 9 of the 11 technologies should be targeted towards OA subcategorisation to address existing OA research technology and knowledge gaps. These novel, rapidly evolving technologies are recommended as a focus for emergent, cross-disciplinary osteoarthritis research programmes.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Stratification; Osteoarthritis; Technology; Phenotype; Omics; Biomarkers
Sprache englisch
Veröffentlichungsjahr 2020
HGF-Berichtsjahr 2020
ISSN (print) / ISBN 1063-4584
e-ISSN 1063-4584
Zeitschrift Osteoarthritis and Cartilage
Quellenangaben Band: 2, Heft: 3, Seiten: , Artikelnummer: 100081 Supplement: ,
Verlag Elsevier
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Translational Genomics (ITG)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Genetics and Epidemiology
PSP-Element(e) G-506700-001
DOI 10.1016/j.ocarto.2020.100081
Scopus ID 85162434259
Erfassungsdatum 2020-06-29
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