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Enregistrement W4366831740 · doi:10.1093/rheumatology/kead104.226

P185 Long-term efficacy and safety of upadacitinib in patients with psoriatic arthritis refractory to biologic therapies: 2-year results from the phase 3 SELECT-PsA 2 study

2023· article· en· W4366831740 sur OpenAlexaff
Philip J. Mease, Arathi R. Setty, Kim Papp, Filip Van den Bosch, Shigeyoshi Tsuji, Mauro Waldemar Keiserman, Xianwei Bu, Liang Chen, R. Mccaskill, E. Mcdearmon-Blondell, Peter Wung, William Tillett

Notice bibliographique

RevueLara D. Veeken · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueSpondyloarthritis Studies and Treatments
Établissements canadiensProbity Medical Research
Organismes subventionnairesAstraZenecaEli Lilly and Company
Mots-clésMedicinePsoriatic arthritisAdverse effectDiscontinuationInternal medicinePlaceboPsoriasisTolerabilityPhases of clinical researchRheumatoid arthritisClinical trialGastroenterologySurgeryDermatology

Résumé

récupéré en direct d'OpenAlex

Abstract Background/Aims Upadacitinib (UPA), an oral Janus kinase (JAK) inhibitor, demonstrated efficacy and safety in patients (pts) with psoriatic arthritis (PsA) and prior inadequate response or intolerance to ≥ 1 biologic disease-modifying antirheumatic drug (bDMARD) at week (wk) 56 in the phase 3 SELECT-PsA 2 study. We aimed to evaluate the efficacy and safety of UPA at wk 104 from the ongoing long-term extension of SELECT-PsA 2. Methods Pts were randomized to UPA 15 mg (UPA15), UPA 30 mg (UPA30), or placebo (PBO) for 24 wks; PBO pts were then switched to UPA15 or UPA30. For continuous UPA treatment groups, efficacy endpoints at wk 104 were analyzed using non-responder imputation (NRI) and as observed (AO) (binary endpoints) or mixed-effect model repeated measures (MMRM) and AO (continuous endpoints). Treatment-emergent adverse events (TEAEs) were summarized for pts who received ≥1 dose of study drug using visit-based cut-off at wk 104. Results A total of 641 pts received ≥1 dose of study drug. At wk 104, 38.4% of all patients had discontinued study drug, with the highest discontinuation observed in patients randomized to PBO at baseline (all PBO: 46.7%). The most common reasons for discontinuation were lack of efficacy (UPA15: 12.3%, UPA30: 8.7%, all PBO: 21.7%) and adverse event (UPA15: 10.9%, UPA30: 13.3%, all PBO: 12.7%). The proportion of UPA pts that achieved ACR20/50/70, MDA, PASI75/90/100, and resolution of dactylitis and enthesitis were generally similar, or further improved, with 104 wks of treatment vs 56 wks. Similarly, mean change from baseline in HAQ-DI, patient’s assessment of pain, BASDAI, and ASDAS was improved with UPA treatment. At 104 wks of therapy, clinical responses were largely similar with UPA15 and UPA30. Generally, safety data at wk 104 were consistent with that reported at wk 56. Rates of serious infection, herpes zoster, hepatic disorder, anemia, neutropenia, lymphopenia, and CPK elevation remained numerically higher with UPA30 vs UPA15, while rates of malignancies, MACE, and VTE were similar for both UPA groups. One death was reported with UPA15 (unexplained due to lack of information; however, the patient had recently been diagnosed with ovarian cancer) and two with UPA30 (pancytopenia and COVID-19 pneumonia). Conclusion In PsA pts with prior inadequate response or intolerance to ≥ 1 bDMARD, clinical responses were maintained with UPA15 and UPA30 up to two years of treatment. No new safety signals were identified in this long-term extension. Disclosure P.J. Mease: Consultancies; Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squib, Celgene, Eli Lilly, Galapagos, Genentech, Gilead, GSK, Janssen, Novartis, Pfizer, Sun Pharma, and UCB. Member of speakers’ bureau; Speakers bureau: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squib, Celgene, Eli Lilly, Galapagos, Genentech, Gilead, GSK, Janssen, Novartis, Pfizer, Sun Pharma, and UCB. Grants/research support; Grant/research support from: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squib, Celgene, Eli Lilly, Galapagos, Genentech, Gilead, GSK, Janssen, Novartis, Pfizer, Sun Pharma, and UCB. A. Setty: Shareholder/stock ownership; Financial Disclosures: Employee of AbbVie and may hold stock or options. K. Papp: Consultancies; Consultant of: AbbVie, Akros, Allergan, Almirall, Amgen, Arcutis, Avillion, Bausch Health, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Dermavant, Dermira, Eli Lilly, Galderma, Genentech/Roche. Member of speakers’ bureau; Speakers bureau: AbbVie, Akros, Allergan, Almirall, Amgen, Bausch Health, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Dermavant, Dermira, Eli Lilly, Galderma, Genentech/Roche, Janssen, Kyowa. Grants/research support; Grant/research support from: AbbVie, Akros, Allergan, Almirall, Amgen, Arcutis, Avillion, Bausch Health, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Dermavant, Dermira, Eli Lilly, Galderma, G. F. Van den Bosch: Consultancies; Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Galapagos, Gilead, Janssen, Merck, Novartis, Pfizer, and UCB. Member of speakers’ bureau; Speakers bureau: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Galapagos, Gilead, Janssen, Merck, Novartis, Pfizer, and UCB. S. Tsuji: Consultancies; Consultant of: AbbVie, Eli Lilly, Janssen, Novartis, and UCB. Member of speakers’ bureau; Speakers bureau: AbbVie, Eli Lilly, Janssen, Novartis, and UCB. Grants/research support; Grant/research support from: AbbVie, Eli Lilly, Janssen, Novartis, and UCB. M. Keiserman: Consultancies; Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and UCB. Member of speakers’ bureau; Speakers bureau: AbbVie, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and UCB. Grants/research support; Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and UCB. X. Bu: Shareholder/stock ownership; Financial Disclosures: Employee of AbbVie and may hold stock or options. L. Chen: Shareholder/stock ownership; Financial Disclosures: Employee of AbbVie and may hold stock or options. R. Mccaskill: Shareholder/stock ownership; Financial Disclosures: Employee of AbbVie and may hold stock or options. E. Mcdearmon-Blondell: Shareholder/stock ownership; Financial Disclosures: Employee of AbbVie and may hold stock or options. P. Wung: Shareholder/stock ownership; Financial Disclosures: Employee of AbbVie and may hold stock or options. W. Tillett: Consultancies; Consultant of: AbbVie, Amgen, Celgene, Eli Lilly, MSD, Novartis, Pfizer, and UCB. Member of speakers’ bureau; Speakers bureau: AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, and UCB. Grants/research support; Grant/research support from: AbbVie, Celgene, Eli Lilly, and Janssen.

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)0,003
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: Essai randomisé · Signal consensuel: Essai randomisé
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,014

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,002
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,018
Tête enseignante GPT0,284
Écart entre enseignants0,266 · 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'étudeEssai randomisé
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
Publié2023
Routes d'admission1
Résumé présentoui

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