Multimethod quantitative benefit-risk assessment of treatments for moderate-to-severe osteoarthritis.


Journal

British journal of clinical pharmacology
ISSN: 1365-2125
Titre abrégé: Br J Clin Pharmacol
Pays: England
ID NLM: 7503323

Informations de publication

Date de publication:
08 2022
Historique:
revised: 23 02 2022
received: 29 06 2021
accepted: 03 03 2022
pubmed: 13 3 2022
medline: 20 7 2022
entrez: 12 3 2022
Statut: ppublish

Résumé

Demonstrate how benefit-risk profiles of systemic treatments for moderate-to-severe osteoarthritis (OA) can be compared using a quantitative approach accounting for patient preference. This study used a multimethod benefit-risk modelling approach to quantifiably compare treatments of moderate-to-severe OA. In total four treatments and placebo were compared. Comparisons were based on four attributes identified as most important to patients. Patient Global Assessment of Osteoarthritis was included as a favourable effect. Unfavourable effects, or risks, included opioid dependence, nonfatal myocardial infarction and rapidly progressive OA leading to total joint replacement. Clinical data from randomized clinical trials, a meta-analysis of opioid dependence and a long-term study of celecoxib were mapped into value functions and weighted with patient preferences from a discrete choice experiment. Lower-dose NGFi had the highest weighted net benefit-risk score (0.901), followed by higher-dose NGFi (0.889) and NSAIDs (0.852), and the lowest score was for opioids (0.762). Lower-dose NGFi was the highest-ranked treatment option even when assuming a low incidence (0.34% instead of 4.7%) of opioid dependence (ie, opioid benefit-risk score 808) and accounting for both the uncertainty in clinical effect estimates (first rank probability 46% vs 20% for NSAIDs) and imprecision in patient preference estimates (predicted choice probability 0.26, 95% confidence interval [CI] 0.25-0.28 vs 0.21, 95% CI 0.19-0.23 for NSAIDs). The multimethod approach to quantitative benefit-risk modelling allowed the interpretation of clinical data from the patient perspective while accounting for uncertainties in the clinical effect estimates and imprecision in patient preferences.

Identifiants

pubmed: 35277997
doi: 10.1111/bcp.15309
pmc: PMC9543715
doi:

Substances chimiques

Anti-Inflammatory Agents, Non-Steroidal 0
Celecoxib JCX84Q7J1L

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

3837-3846

Informations de copyright

© 2022 Pfizer Inc. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.

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Auteurs

Kristin Bullok (K)

Eli Lilly & Co., Global Patient Safety, Indianapolis, IN, USA.

Ed Whalen (E)

Pfizer, New York, NY, USA.

Leo Russo (L)

Pfizer, New York, NY, USA.

Rod Junor (R)

Pfizer, New York, NY, USA.

John Markman (J)

Translational Pain Research Program, Department of Neurosurgery, University of Rochester, Rochester, NY, USA.

Brett Hauber (B)

Pfizer, New York, NY, USA.
CHOICE Institute, University of Washington School of Pharmacy, Seattle, WA, USA.

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Classifications MeSH