POS1356 ASSESSMENT OF THE EFFICACY OF COMBINATION OF ORAL ACETAMINOPHEN AND TOPICAL DICLOFENAC IN OSTEOARTHRITIS PAIN: INSIGHTS FROM A MODEL-BASED META-ANALYSIS
Notice bibliographique
Résumé
Background Osteoarthritis (OA) is a major cause of chronic pain and disability in older adults and currently affects approximately 300 million people worldwide [1]. In the absence of curative therapy, symptomatic drugs comprise the backbone of pain management in OA. However, acetaminophen provides inadequate relief and oral non-steroidal anti-inflammatory drugs (NSAIDs) exhibit significant gastrointestinal and cardiovascular toxicity which prohibit their long-term use in the elderly [2,3]. Although opioids can be an effective alternative in patients experiencing insufficient pain relief with other analgesics, concerns have been raised about the risk of side effects, addiction, and overdose deaths [4]. Therefore, there is a significant unmet need for effective and well-tolerated treatments. Acetaminophen and topical diclofenac exhibit complementary mechanisms of action targeting pain and inflammation, respectively, and are therefore attractive candidates for use in combination analgesia in OA pain [5,6,7]. Although ample clinical evidence exists on the monotherapy of acetaminophen or topical diclofenac in OA, there is a data gap for evidence on their combination. Objectives The present study aims to assess the effect of the combination of acetaminophen and topical diclofenac in OA and compare its performance to acetaminophen and diclofenac monotherapy using a model-based meta-analysis (MBMA) leveraging published summary-level data on the combination from OA as well as other acute pain indications [8]. Methods Randomized controlled trials (RCTs) investigating the combination of acetaminophen and diclofenac in OA and acute pain settings were identified through systematic literature searches. MBMA was implemented to infer the efficacy of the combination in the population of interest. Pain score reduction on numerical rating scale (NRS), visual analogue scale (VAS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain subscale along with opioid sparing effect (defined as reduced opioid dose without loss of analgesic efficacy) were selected as the clinical endpoints. Results In the absence of RCTs on the combination in OA, MBMA was implemented in conjunction with extrapolation principles on trials in acute pain setting (11 RCTs, n=1396 patients). The combination demonstrated greater reduction in pain scores versus acetaminophen monotherapy in 8 of the 11 RCTs. Moreover, a parsimonious MBMA was developed on 5 RCTs allowing PCA, which revealed a statistically significant 32% lesser opioid use with the combination than with acetaminophen monotherapy (Figure 1). However, the combination effect was less conclusive versus diclofenac monotherapy. Conclusion The current analysis demonstrates greater pain reduction and opioid sparing efficacy for the combination versus acetaminophen monotherapy in the treatment of acute pain. Considering the overlap in pain transmission pathways between acute and chronic OA pain, the combination may be anticipated to exhibit similar performance on extrapolation to chronic OA pain. Overall, our research tries to bridge the gap in pharmacological and clinical evidence supporting the use of combination of acetaminophen and topical diclofenac in mild-to-moderate OA pain. References [1]GBD 2017 Disease and Injury Incidence and Prevalence Collaborators. Lancet. 2018;392(10159):1789-1858. [2]Bannuru, R. Osteoarthritis and Cartilage. 2010;(18), S250 [3]Cooper, C. Drugs Aging. 2019;36(Suppl 1), 15-24 [4]Deveza, LA. Osteoarthritis Cartilage. 2018;26(3):293-295. [5]Altman, RD. J Rheumatol. 2004;31(1):5-7. [6]Anderson, BJ. Paediatr Anaesth. 2008;18(10), 915-921 [7]Shah, S. Postgrad Med J. 2012; 88(1036), 73-78. [8]Mandema, JW. Clin Pharmacol Ther. 2011;90(6):766-769. Acknowledgements This study was funded by Haleon. Disclosure of Interests Vidhu Sood Employee of: Haleon, Li Qin: None declared, Eugène Cox: None declared, Iñaki Trocóniz: None declared, Oscar Della Pasqua Employee of: GlaxoSmithKline.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,022 | 0,031 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,012 | 0,051 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».