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The use of technology in the subcategorisation of osteoarthritis: a Delphi study approach

Lookup NU author(s): Professor John LoughlinORCiD



This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Objective This study utilised a Delphi consensus process within the OATech Network+ to identify whether existing technology could aid subcategorisation of patients with osteoarthritis (OA) and determine the level of awareness of these technologies across the expert panel. Design An online questionnaire was formulated based on technologies which may aid subcategorisation of OA. A two-day face-to-face meeting was held to monitor concordance of expert opinion with online surveys (23 questions) completed before (Round 1), during (Round 2) and at the end of (Round 3) the meeting. Experts spoke at the start of the meeting on imaging, genomics, epigenomics, proteomics, metabolomics, biomarkers, activity monitoring, clinical engineering and machine learning. For each round of voting, ≥80% votes led to consensus and ≤20% votes led to exclusion of a statement. Results Panel members were unanimous that technological advances can improve OA subcategorisation. It was agreed at Rounds 1 and 2 that epigenetics, genetics, MRI, proteomics, wet biomarkers and machine learning could all aid subcategorisation. Talks from experts changed participants’ opinions on the usefulness of metabolomics, activity monitoring and clinical engineering, reaching consensus in Round 2. X-rays lost consensus between Rounds 1 and 2 but their use in the clinic (but not for research) reached consensus in Round 3. Ultrasound failed to reach consensus for either ConclusionConsensus was reached that 9 of the 11 technologies identified could aid OA subcategorisation. Interestingly, these 9 are the more recent and rapidly evolving technologies (unlike non-consensus-reaching X-rays and ultrasound), suggesting further improvements are likely.

Publication metadata

Author(s): Mennan C, Hopkins T, Channon A, Elliot M, Johnstone B, Kadir T, Loughlin J, Peffers M, Pitsillides A, Sofat N, Stewart C, Watt FE, Zeggini E, Holt C, Roberts S

Publication type: Article

Publication status: Published

Journal: Osteoarthritis and Cartilage Open

Year: 2020

Volume: 2

Issue: 3

Print publication date: 01/09/2020

Online publication date: 09/06/2020

Acceptance date: 04/06/2020

Date deposited: 09/06/2020

ISSN (electronic): 2665-9131

Publisher: Elsevier


DOI: 10.1016/j.ocarto.2020.100081


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