Mennan, C;
Hopkins, T;
Channon, A;
Elliott, M;
Johnstone, B;
Kadir, T;
Loughlin, J;
Peffers, M;
Pitsillides, A;
Sofat, N;
et al.
Mennan, C; Hopkins, T; Channon, A; Elliott, M; Johnstone, B; Kadir, T; Loughlin, J; Peffers, M; Pitsillides, A; Sofat, N; Stewart, C; Watt, FE; Zeggini, E; Holt, C; Roberts, S
(2020)
The Use of Technology in the Subcategorisation of Osteoarthritis: a Delphi Study Approach.
Osteoarthritis and Cartilage Open, 2 (3).
p. 100081.
ISSN 2665-9131
https://doi.org/10.1016/j.ocarto.2020.100081
SGUL Authors: Sofat, Nidhi
Abstract
Objective
This 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).
Design
An 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.
Results
Panel 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.
Conclusion
Consensus 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.
Item Type: |
Article
|
Additional Information: |
© 2020 Osteoarthritis Research Society International (OARSI). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
SGUL Research Institute / Research Centre: |
Academic Structure > Infection and Immunity Research Institute (INII) |
Journal or Publication Title: |
Osteoarthritis and Cartilage Open |
ISSN: |
2665-9131 |
Language: |
en |
Dates: |
Date | Event |
---|
September 2020 | Published | 9 June 2020 | Published Online | 28 May 2020 | Accepted |
|
Projects: |
Project ID | Funder | Funder ID |
---|
EP/N027264/1 | Engineering and Physical Sciences Research Council | http://dx.doi.org/10.13039/501100000266 | 21156 | Versus Arthritis | UNSPECIFIED | 18450 | Versus Arthritis | UNSPECIFIED | MR/L0104531/1 | Medical Research Council | http://dx.doi.org/10.13039/501100000265 | 20771 | Versus Arthritis | UNSPECIFIED | JXR 10641 | Centre for Integrated Research into Musculoskeletal Ageing | UNSPECIFIED | MR/P020941/1 | Centre for Integrated Research into Musculoskeletal Ageing | UNSPECIFIED | MR/R502182/1 | Centre for Integrated Research into Musculoskeletal Ageing | UNSPECIFIED | 20205 | Versus Arthritis | UNSPECIFIED | 21621 | Versus Arthritis | UNSPECIFIED |
|
URI: |
https://openaccess.sgul.ac.uk/id/eprint/112039 |
Publisher's version: |
https://doi.org/10.1016/j.ocarto.2020.100081 |
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