Predicting response to topical non-steroidal anti-inflammatory drugs in osteoarthritis: an individual patient data meta-analysis of randomized controlled trials.


Journal

Rheumatology (Oxford, England)
ISSN: 1462-0332
Titre abrégé: Rheumatology (Oxford)
Pays: England
ID NLM: 100883501

Informations de publication

Date de publication:
01 09 2020
Historique:
received: 27 08 2019
accepted: 31 01 2020
pubmed: 11 4 2020
medline: 20 1 2021
entrez: 11 4 2020
Statut: ppublish

Résumé

To identify predictors of the specific (difference between treatment and placebo) and overall (change from baseline in treatment arm) treatment effects of topical NSAIDs in OA. Randomized controlled trials (RCTs) of topical NSAIDs in OA were identified through systematic literature searching and inquiry to pharmaceutical companies. The raw, de-identified data were analysed in one-stage individual patient data meta-analysis (IPD-MA). Negative values for treatment effects (0-100 scale) indicate pain reduction. Of 63 eligible RCTs, 15 provided IPD (n = 1951 on topical NSAID), including 11 placebo-controlled RCTs (n = 1587 on topical NSAIDs, 1553 on placebo). Seven potential predictors of response were examined. Topical NSAIDs were superior to placebo [-6 (95% CI -9, -4)], with a small, but statistically significant greater effect in women than men [difference -4 (95% CI -8, -1)]. The overall treatment effect was 4-fold larger than the specific effect [-25 (95% CI -31, -19)] and increased with greater baseline pain severity (P < 0.001). No differences in efficacy were observed for age, BMI, features of inflammation, duration of complaints or radiographic OA severity. Topical NSAIDs are effective for OA pain relief. Greater overall pain relief in individuals with more baseline pain might be due to contextual and non-specific effects, including regression to the mean. Additional factors that have been linked either mechanistically or through empirical evidence to outcomes should be selected for inclusion across future RCTs in order to facilitate the identification of response predictors through IPD-MA.

Identifiants

pubmed: 32276272
pii: 5818943
doi: 10.1093/rheumatology/keaa113
pmc: PMC7449808
doi:

Substances chimiques

Anti-Inflammatory Agents, Non-Steroidal 0

Types de publication

Journal Article Meta-Analysis Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2207-2216

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press on behalf of the British Society for Rheumatology.

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Auteurs

Monica S M Persson (MSM)

Academic Rheumatology, School of Medicine, University of Nottingham, Nottingham, UK.

Joanne Stocks (J)

Academic Rheumatology, School of Medicine, University of Nottingham, Nottingham, UK.

Gyula Varadi (G)

BioPhysics Pharma, Beverly, MA, USA.

Mohammad Hashem Hashempur (MH)

Department of Traditional Persian Medicine, Fasa University of Medical Sciences, Fasa, Iran.

Marienke van Middelkoop (M)

Department of General Practice, University Medical Center, Erasmus Medical Center, Rotterdam, The Netherlands.

Sita Bierma-Zeinstra (S)

Department of General Practice, University Medical Center, Erasmus Medical Center, Rotterdam, The Netherlands.

David A Walsh (DA)

Academic Rheumatology, School of Medicine, University of Nottingham, Nottingham, UK.

Michael Doherty (M)

Academic Rheumatology, School of Medicine, University of Nottingham, Nottingham, UK.

Weiya Zhang (W)

Academic Rheumatology, School of Medicine, University of Nottingham, Nottingham, UK.

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Classifications MeSH