The University of Southampton
University of Southampton Institutional Repository
Warning ePrints Soton is experiencing an issue with some file downloads not being available. We are working hard to fix this. Please bear with us.

An updated algorithm recommendation for the management of knee osteoarthritis from the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO)

An updated algorithm recommendation for the management of knee osteoarthritis from the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO)
An updated algorithm recommendation for the management of knee osteoarthritis from the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO)

Objectives: The European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO) sought to revisit the 2014 algorithm recommendations for knee osteoarthritis (OA), in light of recent efficacy and safety evidence, in order to develop an updated stepwise algorithm that provides practical guidance for the prescribing physician that is applicable in Europe and internationally. Methods: Using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) process, a summary of evidence document for each intervention in OA was provided to all members of an ESCEO working group, who were required to evaluate and vote on the strength of recommendation for each intervention. Based on the evidence collected, and on the strength of recommendations afforded by consensus of the working group, the final algorithm was constructed. Results: An algorithm for management of knee OA comprising a stepwise approach and incorporating consensus on 15 treatment recommendations was prepared by the ESCEO working group. Both “strong” and “weak” recommendations were afforded to different interventions. The algorithm highlights the continued importance of non-pharmacological interventions throughout the management of OA. Benefits and limitations of different pharmacological treatments are explored in this article, with particular emphasis on safety issues highlighted by recent literature analyses. Conclusions: The updated ESCEO stepwise algorithm, developed by consensus from clinical experts in OA and informed by available evidence for the benefits and harms of various treatments, provides practical, current guidance that will enable clinicians to deliver patient-centric care in OA practice.

Algorithm, GRADE, Knee osteoarthritis, Recommendations, Treatment
0049-0172
Bruyère, Olivier
ba727e54-ca17-4fa8-be3d-4729fb4b8c0d
Honvo, Germain
b028bd1a-b0a7-444f-bde5-32b5b611b9af
Veronese, Nicola
a9a97f63-a828-45a3-bae0-68182c5a44fd
Arden, Nigel K.
23af958d-835c-4d79-be54-4bbe4c68077f
Branco, Jaime
1be74759-fd01-4fee-9178-ef739a5072ed
Curtis, Elizabeth M.
12aba0c3-1e9e-49ef-a7e9-3247e649cdd6
Al-Daghri, Nasser M.
0bf1023c-a104-4f74-8b06-87780dfbd8b4
Herrero-Beaumont, Gabriel
44373e0b-5324-4603-9185-3c18015963d1
Martel-Pelletier, Johanne
fdcae9e5-239c-430f-a971-a287f7a0645e
Pelletier, Jean Pierre
bed7c601-ce19-4804-8781-d27f674ccccb
Rannou, François
2b61556e-9368-4b92-8f27-25e6697230dc
Rizzoli, René
c1190577-8164-471d-b90f-6959f92bc25e
Roth, Roland
5a82424f-5a06-47d8-85ad-d9fe260a9ad0
Uebelhart, Daniel
56d19cf5-f45b-46db-8170-356da80a9e52
Cooper, Cyrus
e05f5612-b493-4273-9b71-9e0ce32bdad6
Reginster, Jean Yves
08b05e27-73dd-4ce9-90e5-d64ec922147a
Bruyère, Olivier
ba727e54-ca17-4fa8-be3d-4729fb4b8c0d
Honvo, Germain
b028bd1a-b0a7-444f-bde5-32b5b611b9af
Veronese, Nicola
a9a97f63-a828-45a3-bae0-68182c5a44fd
Arden, Nigel K.
23af958d-835c-4d79-be54-4bbe4c68077f
Branco, Jaime
1be74759-fd01-4fee-9178-ef739a5072ed
Curtis, Elizabeth M.
12aba0c3-1e9e-49ef-a7e9-3247e649cdd6
Al-Daghri, Nasser M.
0bf1023c-a104-4f74-8b06-87780dfbd8b4
Herrero-Beaumont, Gabriel
44373e0b-5324-4603-9185-3c18015963d1
Martel-Pelletier, Johanne
fdcae9e5-239c-430f-a971-a287f7a0645e
Pelletier, Jean Pierre
bed7c601-ce19-4804-8781-d27f674ccccb
Rannou, François
2b61556e-9368-4b92-8f27-25e6697230dc
Rizzoli, René
c1190577-8164-471d-b90f-6959f92bc25e
Roth, Roland
5a82424f-5a06-47d8-85ad-d9fe260a9ad0
Uebelhart, Daniel
56d19cf5-f45b-46db-8170-356da80a9e52
Cooper, Cyrus
e05f5612-b493-4273-9b71-9e0ce32bdad6
Reginster, Jean Yves
08b05e27-73dd-4ce9-90e5-d64ec922147a

Bruyère, Olivier, Honvo, Germain, Veronese, Nicola, Arden, Nigel K., Branco, Jaime, Curtis, Elizabeth M., Al-Daghri, Nasser M., Herrero-Beaumont, Gabriel, Martel-Pelletier, Johanne, Pelletier, Jean Pierre, Rannou, François, Rizzoli, René, Roth, Roland, Uebelhart, Daniel, Cooper, Cyrus and Reginster, Jean Yves (2019) An updated algorithm recommendation for the management of knee osteoarthritis from the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO). Seminars in Arthritis and Rheumatism. (doi:10.1016/j.semarthrit.2019.04.008).

Record type: Review

Abstract

Objectives: The European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO) sought to revisit the 2014 algorithm recommendations for knee osteoarthritis (OA), in light of recent efficacy and safety evidence, in order to develop an updated stepwise algorithm that provides practical guidance for the prescribing physician that is applicable in Europe and internationally. Methods: Using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) process, a summary of evidence document for each intervention in OA was provided to all members of an ESCEO working group, who were required to evaluate and vote on the strength of recommendation for each intervention. Based on the evidence collected, and on the strength of recommendations afforded by consensus of the working group, the final algorithm was constructed. Results: An algorithm for management of knee OA comprising a stepwise approach and incorporating consensus on 15 treatment recommendations was prepared by the ESCEO working group. Both “strong” and “weak” recommendations were afforded to different interventions. The algorithm highlights the continued importance of non-pharmacological interventions throughout the management of OA. Benefits and limitations of different pharmacological treatments are explored in this article, with particular emphasis on safety issues highlighted by recent literature analyses. Conclusions: The updated ESCEO stepwise algorithm, developed by consensus from clinical experts in OA and informed by available evidence for the benefits and harms of various treatments, provides practical, current guidance that will enable clinicians to deliver patient-centric care in OA practice.

Text
1-s2.0-S0049017219300435-main - Version of Record
Download (1MB)

More information

e-pub ahead of print date: 30 April 2019
Keywords: Algorithm, GRADE, Knee osteoarthritis, Recommendations, Treatment

Identifiers

Local EPrints ID: 431876
URI: http://eprints.soton.ac.uk/id/eprint/431876
ISSN: 0049-0172
PURE UUID: 75fc248d-30b7-4c3c-871c-8597cd08b0d7
ORCID for Elizabeth M. Curtis: ORCID iD orcid.org/0000-0002-5147-0550
ORCID for Cyrus Cooper: ORCID iD orcid.org/0000-0003-3510-0709

Catalogue record

Date deposited: 20 Jun 2019 16:30
Last modified: 26 Nov 2021 03:09

Export record

Altmetrics

Contributors

Author: Olivier Bruyère
Author: Germain Honvo
Author: Nicola Veronese
Author: Nigel K. Arden
Author: Jaime Branco
Author: Nasser M. Al-Daghri
Author: Gabriel Herrero-Beaumont
Author: Johanne Martel-Pelletier
Author: Jean Pierre Pelletier
Author: François Rannou
Author: René Rizzoli
Author: Roland Roth
Author: Daniel Uebelhart
Author: Cyrus Cooper ORCID iD
Author: Jean Yves Reginster

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×