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Enregistrement W4411426123 · doi:10.1016/j.ard.2025.06.1387

ABS0537 EARLY IMPROVEMENT OF PAIN, LONG-TERM DISEASE CONTROL, AND QUALITY OF LIFE OUTCOMES IN PATIENTS WITH PSORIATIC ARTHRITIS TREATED WITH UPADACITINIB

2025· article· en· W4411426123 sur OpenAlexaff
Peter C. Taylor, Lihi Eder, Yael Klionsky, Fabian Proft, T. Iyile, Erin Mancl, Priscila Nakasato, Xiangyang Ye, Lin Zhou, P.J. Mease

Notice bibliographique

RevueAnnals of the Rheumatic Diseases · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueSpondyloarthritis Studies and Treatments
Établissements canadiensWomen's College Hospital
Organismes subventionnairesnon disponible
Mots-clésMedicinePsoriatic arthritisQuality of life (healthcare)Term (time)Pain controlArthritisPhysical therapyInternal medicineSurgery

Résumé

récupéré en direct d'OpenAlex

Background: Severe musculoskeletal manifestations of PsA, particularly joint pain, can result in reduced physical function, decreased quality of life, and progressive and irreversible joint damage [1, 2]. Upadacitinib (15mg; UPA15), an oral JAK inhibitor, has shown to rapidly and meaningfully reduce pain in patients with active PsA and inadequate response (IR) to non-biologic DMARDs (non-bDMARD-IR, including csDMARDs or apremilast) or biologic DMARDs (bDMARD-IR) [3]. However, there is limited evidence of how rapid pain improvement impacts long-term disease control and quality of life. Objectives: This analysis reports the improvement in pain by baseline pain severity and the impact of early pain improvement on long-term, stringent disease control targets and patient-reported outcomes in patients with PsA treated with UPA15 through 152 wks. Methods: In this post hoc analysis, patients randomized to UPA15 in the phase 3 trials SELECT-PsA 1 (N=429; non-bDMARD-IR patients) and SELECT-PsA 2 (N=211; bDMARD-IR patients) were analyzed separately [4, 5]. Mean pain scores (as observed, AO) over 152 wks were calculated in patients with mild/moderate (0-3/4-6) and severe (7-10) baseline pain severity (numeric rating scale, NRS: 0-10). Patients were also stratified by achievement/nonachievement of early pain improvement (≥30% at wk 2 and ≥30/50/70% at wk 12); for each group, achievement of MDA, DAPSA low disease activity (LDA; ≤14), or pain ≤1.5 (NRS) (all reported as nonresponder imputation) and mean change from baseline in SF-36 mental component summary (SF-36 MCS; reported AO) was calculated at wk 152. Results: For patients with severe pain at baseline, mean pain scores rapidly decreased to moderate levels in the first 2 wks of treatment with UPA15, with additional reductions and achievement of mild/moderate levels by wk 152 in both non-bDMARD-IR (wk 152 mean: 3.3) and bDMARD-IR patients (3.8) (Figure 1). For patients with mild/moderate pain at baseline, mean pain scores decreased and were maintained to mild levels through wk 152 in non-bDMARD-IR (2.0) and bDMARD-IR (2.8) patients. In both studies, a larger proportion of patients with early pain improvements achieved MDA, DAPSA LDA, and pain ≤1.5 at wk 152, compared to patients without early pain improvements (Figure 2). Additionally, bDMARD-IR patients with early pain improvements reported greater improvements in SF-36 MCS score at wk 152 compared to those without early improvements, with smaller differences observed in non-bDMARD-IR patients. Conclusion: In non-bDMARD-IR and bDMARD-IR PsA patients, reductions in pain score occurred rapidly and were maintained through 152 wks of treatment with UPA15, regardless of pain severity at baseline. More patients with early pain improvements achieved long-term, stringent disease control targets and quality of life outcomes compared to patients without early pain improvements, suggesting that rapid pain improvement may be a positive indicator of long-term disease control. REFERENCES: [1] Coates LC, et al. Health Qual Life Outcomes. 2020;18:173. [2] Ogdie A, et al. Rheum & Therapy. 2021;9:735-51. [3] McInnes IB, et al. RMD Open . 2022;8:e002049. [4] McInnes, IB et al. N Engl J Med. 2021;384:1227-39. [5] Mease PJ, et al. Ann Rheum Dis. 2021;80:312-20. Acknowledgements: AbbVie funded these trials (NCT03104400; NCT03104374) and participated in the study design, research, analysis, data collection, interpretation of data, reviewing, and approval of the publication. All authors had access to relevant data and participated in the drafting, review, and approval of this publication. No honoraria or payments were made for authorship. Medical writing support was provided by Kathleen E. Gordon, PhD of AbbVie. Editorial support was provided by Angela T. Hadsell of AbbVie. Disclosure of Interests: Peter C. Taylor AbbVie, AbbVie, Biogen, Eli Lilly, Fresenius, Galapagos, Gilead Sciences, GlaxoSmithKline, Janssen, Nordic Pharma, Pfizer Inc, Roche, UCB, Sanofi, Immunovant, Moonlake, Galapagos, Lihi Eder AbbVie, UCB, Eli Lilly, Novartis, Fresenius Kabi, Janssen, BMS, and Pfizer, Yael Klionsky Janssen and AstraZeneca, Eli Lilly, MediQ, Amgen, Abbvie and Aztrazeneca, Fabian Proft AMGEN, AbbVie, BMS, Celgene, Janssen, MSD, Novartis, Pfizer, Roche, UCB, Medscape, Galapagos, Hexal, Novartis, Eli Lily, UCB, Thomas Iyile AbbVie Inc., Erin Mancl AbbVie Inc., Priscila Nakasato AbbVie Inc., Xiaolan Ye AbbVie Inc., Limei Zhou AbbVie Inc., Philip J. Mease AbbVie, Acelyrin, Amgen, Bristol Myers, Inmagene, Janssen, Lilly, Moonlake, Novartis, Pfizer, and UCB. © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,009

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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.

Tête enseignante Opus0,016
Tête enseignante GPT0,279
Écart entre enseignants0,263 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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