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Enregistrement W4411433673 · doi:10.1016/j.ard.2025.06.191

POS0835 LONG-TERM SAFETY AND EFFICACY OF UPADACITINIB IN PATIENTS WITH PSORIATIC ARTHRITIS: 5-YEAR RESULTS FROM THE PHASE 3 SELECT-PsA 1 STUDY

2025· article· en· W4411433673 sur OpenAlexaff
Iain B. McInnes, Koji Kato, Marina Magrey, Joseph F. Merola, Mitsumasa Kishimoto, Derek Haaland, Laura C. Coates, I. Lagunes, Yi Liu, Erin Mancl, Bijal A. Parikh, Caroline Phillips

Notice bibliographique

RevueAnnals of the Rheumatic Diseases · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueRheumatoid Arthritis Research and Therapies
Établissements canadiensMcMaster UniversityUniversity of Sudbury
Organismes subventionnairesnon disponible
Mots-clésMedicinePsoriatic arthritisTerm (time)Internal medicineOncologyArthritis

Résumé

récupéré en direct d'OpenAlex

Background: Treatment with upadacitinib (UPA), an oral JAK inhibitor, in patients with active PsA and an inadequate response or intolerance to ≥ 1 non-biologic DMARD led to improvements in the signs and symptoms of PsA at week 12 (primary publication) [1] through week 104 (2-year long-term extension) [2] and week 152 (3-year long-term extension) [3] of the phase 3 SELECT-PsA 1 study. Objectives: To evaluate the safety and efficacy of UPA, in the context of the active comparator adalimumab (ADA), at week 260 (5 years) from the long-term extension of SELECT-PsA 1. Methods: Patients with PsA were randomized to receive UPA 15 mg once daily, UPA 30 mg once daily, ADA 40 mg every other week, or placebo for 24 weeks. At week 24, patients treated with placebo were switched to UPA 15 mg or UPA 30 mg. Following the approval of UPA 15 mg, the study protocol was amended whereby patients treated with UPA 30 mg were switched to UPA 15 mg (earliest switch occurred at week 104 of the study). Data for patients who switched from UPA 30 to UPA 15 treatment are not presented. Treatment-emergent adverse events were summarized for patients who received ≥ 1 dose of study drug using all available data from the 5-year study. Safety data are presented as exposure-adjusted event rates (EAERs; defined as events per 100 patient-years), as well as exposure-adjusted incidence rates (EAIRs; defined as number of patients per 100 patient-years) for a subset of adverse events of special interest. Efficacy endpoints were analyzed using nonresponder imputation (NRI) and as observed (AO) for binary endpoints or mixed effect model repeated measures and AO for continuous endpoints, with nominal P values shown, for continuous UPA and ADA treatment groups. Results: In total, 1704 patients received ≥ 1 dose of study drug and 983 (57.7%) patients completed 260 weeks of treatment. Across all patients, the most common primary reasons for discontinuation of study drug in the LTE were adverse events (8.4%), withdrawal of consent (6.2%), and lack of efficacy (4.7%). The safety profile of UPA through week 260 (5 years) was generally comparable to ADA (Figure 1) and consistent with data from weeks 104 and 152 [2, 3]. Rates of malignancy excluding nonmelanoma skin cancer (NMSC), MACE, and VTE were low compared to historical comparators and generally similar across treatment groups. Rates of serious infection, herpes zoster, anemia, lymphopenia, creatine phosphokinase (CPK) elevation, and NMSC remained higher with UPA versus ADA; serious infection, herpes zoster, anemia, neutropenia, and CPK elevation were higher with UPA 30 mg versus UPA 15 mg. Rates (EAERs) of death were the same for both UPA treatment groups and similar (< 1.0 difference in EAERs) with ADA; the most common cause of death was COVID-19/COVID-19 pneumonia. Across efficacy endpoints, improvements observed with UPA treatment at weeks 104 and 152 were generally maintained through week 260 (Table 1) [2, 3]. Based on AO analysis, the proportions of patients who achieved ≥ 20%/50%/70% improvement in ACR response criteria (ACR20/50/70) or minimal disease activity (MDA) with UPA 15 mg treatment were comparable (< 10.0% difference) to ADA at week 260. The proportions of patients achieving ≥ 75%/90%/100% improvement in PASI (PASI75/90/100) were also comparable between UPA 15 mg and ADA at week 260 (AO). Similar trends were observed across binary endpoints using the more conservative NRI analysis, with efficacy responses generally comparable with UPA 15 mg versus ADA at week 260. Across all treatments, mean change from baseline in HAQ-DI and the patient's assessment of pain were maintained from weeks 104 and 152 to week 260 and were comparable with UPA 15 mg versus ADA at week 260 (AO). Mean change from baseline in the modified total Sharp/van der Heijde Score (mTSS) at week 260 was similar across treatment groups (AO). Conclusion: In patients with PsA and an inadequate response or intolerance to ≥ 1 non-biologic DMARD, no new safety risks were identified with long-term treatment with UPA up to 5 years compared to previous reports [1–4] and the safety profile of UPA was generally consistent with ADA. Improvements in efficacy responses across various domains of PsA with UPA treatment were generally maintained over time [2, 3] and were comparable to ADA at week 260 (5 years). REFERENCES: [1] McInnes I, et al. N Engl J Med . 2021;384:1227-39. [2] McInnes I, et al. Rheumatol Ther. 2023;10:275-92. [3] McInnes I, et al. Ann Rheum Dis. 2023 [Abstract]. [4] Burmester G, et al. RMD Open. 2023;9:e002735. Figure 1 Table 1 . Acknowledgements: AbbVie and the authors thank the patients, study sites, and investigators who participated in this trial (NCT03104400). AbbVie funded this study 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 Monica R.P. Elmore, PhD of AbbVie. Editing support was provided by S. Michael Austin of AbbVie. Disclosure of Interests: Iain B. McInnes received honoraria from AbbVie, AstraZeneca, Bristol Myers Squibb, Celgene, Eli Lilly, Evelo, Causeway Therapeutics, Gilead, Janssen, Novartis, Pfizer, Sanofi Regeneron, and UCB Pharma, research grants from AbbVie, AstraZeneca, Bristol Myers Squibb, Celgene, Eli Lilly, Evelo, Causeway Therapeutics, Gilead, Janssen, Novartis, Pfizer, Sanofi Regeneron, and UCB Pharma, Koji Kato is an employee of AbbVie and may hold stock or stock options, Marina Magrey received consulting fees from BMS, Eli Lilly, Janssen, Novartis, Pfizer, and UCB Pharma, research grants from AbbVie, Amgen, BMS, and UCB Pharma, Joseph F. Merola served as consultant for AbbVie, Arena, Avotres, Biogen, Bristol Myers Squibb, Celgene, Dermavant, Eli Lilly, EMD Sorono, Janssen, Leo Pharma, Merck, Novartis, Pfizer, Regeneron, Sanofi, Sun Pharma, and UCB Pharma, an investigator for AbbVie, Arena, Avotres, Biogen, Bristol Myers Squibb, Celgene, Dermavant, Eli Lilly, EMD Sorono, Janssen, Leo Pharma, Merck, Novartis, Pfizer, Regeneron, Sanofi, Sun Pharma, and UCB Pharma, Mitsumasa Kishimoto received honoraria from AbbVie, Amgen, Asahi-Kasei Pharma, Astellas, Ayumi Pharma, BMS, Celgene, Chugai, Daiichi-Sankyo, Eisai, Eli Lilly, Gilead, Janssen, Kyowa Kirin, Novartis, Ono Pharma, Takeda, Tanabe-Mitsubishi, and UCB Pharma, received consulting fees from AbbVie, Amgen, Asahi-Kasei Pharma, Astellas, Ayumi Pharma, BMS, Celgene, Chugai, Daiichi-Sankyo, Eisai, Eli Lilly, Gilead, Janssen, Kyowa Kirin, Novartis, Ono Pharma, Takeda, Tanabe-Mitsubishi, and UCB Pharma, Derek Haaland received honoraria or other fees from AbbVie, Amgen, AstraZeneca, Bristol Myers Squibb, Eli Lilly, GlaxoSmithKline, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi Genzyme, Takeda, and UCB Pharma, served on the advisory board/speaker bureau or similar committee for AbbVie, Amgen, AstraZeneca, Bristol Myers Squibb, GlaxoSmithKline, Janssen, Novartis, Pfizer, Roche, Sanofi Genzyme, Takeda, received funding for grants or clinical trials from AbbVie, Adiga Life Sciences, Amgen, Bristol Myers Squibb, Can-Fite Biopharma, Celgene, Eli Lilly, Gilead, GlaxoSmithKline, Janssen, Novartis, Pfizer, Regeneron, Sanofi-Genzyme, UCB, Laura C. Coates has been paid as a speaker for AbbVie, Amgen, Biogen, Celgene, Galapagos, Gilead, GSK, Janssen, Lilly, Medac, Novartis, Pfizer, and UCB, worked as a paid consultant for AbbVie, Amgen, BI, BMS, Celgene, Gilead, Galapagos, Janssen, Lilly, Moonlake, Novartis, Pfizer, and UCB, received grants/research support from AbbVie, Amgen, Celgene, Janssen, Lilly, Novartis, Pfizer, and UCB, Ivan Lagunes is an employee of AbbVie and may hold stock or stock options, Yanxi Liu is an employee of AbbVie and may hold stock or stock options, Erin Mancl is an employee of AbbVie and may hold stock or stock options, Bhumik Parikh is an employee of AbbVie and may hold stock or stock options, Charles Phillips is an employee of AbbVie and may hold stock or stock options. © 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)0,004
score de la tête « metaresearch » (Gemma)0,003
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 enseignants0,004
Score d'incertitude au seuil0,023

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,003
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,001
Communication savante0,0010,001
Science ouverte0,0000,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0020,001

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.

Tête enseignante Opus0,016
Tête enseignante GPT0,309
Écart entre enseignants0,293 · 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

Citations1
Publié2025
Routes d'admission1
Résumé présentoui

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