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Enregistrement W4411410596 · doi:10.1016/j.ard.2025.06.1258

ABS0448 ZASOCITINIB (TAK-279), AN ORAL, ALLOSTERIC, SELECTIVE TYK2 INHIBITOR, IN MODERATE-TO-SEVERE PLAQUE PSORIASIS: EFFICACY ANALYSIS BY BASELINE CHARACTERISTICS FROM A RANDOMISED PHASE 2B TRIAL

2025· article· en· W4411410596 sur OpenAlexaff
Nada Elbuluk, M. Gooderham, John Blau, Weidong Zhang, J. Uy, Warren Winkelman, M. Lebwohl

Notice bibliographique

RevueAnnals of the Rheumatic Diseases · 2025
Typearticle
Langueen
DomaineImmunology and Microbiology
ThématiquePsoriasis: Treatment and Pathogenesis
Établissements canadiensSKiN Health
Organismes subventionnairesnon disponible
Mots-clésMedicinePlaque psoriasisPsoriasisInternal medicineRandomized controlled trialClinical trialPharmacologyDermatology

Résumé

récupéré en direct d'OpenAlex

Background: Zasocitinib (TAK-279) is a highly selective and potent, oral, allosteric tyrosine kinase 2 (TYK2) inhibitor. In a phase 2b trial of moderate-to-severe plaque psoriasis, the primary endpoint (psoriasis area and severity index [PASI] 75 response at Week 12) was met with zasocitinib 5, 15 and 30 mg once daily; 33% of patients receiving zasocitinib 30 mg achieved PASI 100 [1]. Objectives: To evaluate the influence of baseline characteristics on zasocitinib efficacy in patients with plaque psoriasis in the phase 2b trial. Methods: This was a phase 2b, randomised, multicentre, double-blind, placebo-controlled, multiple-dose study (NCT04999839). Post hoc analyses were performed on Week 12 PASI 75/90/100 responses, Physician Global Assessment (PGA) scores of clear (0) or almost clear (1), and Dermatology Life Quality Index (DLQI) scores stratified by weight, sex, age, race, disease duration, prior biologics use and baseline PASI. The treatment difference between zasocitinib groups and placebo was calculated using the Mantel–Haenszel method, and p values were calculated using a Cochran–Mantel–Haenszel test with prior biologic treatment included as a stratification factor; treatment difference estimates stratified by prior biologic treatment, in which treatment difference estimates were unadjusted and chi-square test was used to calculate p values. For DLQI, a mixed model for repeated measures was used to calculate the least square mean, with treatment, visit, treatment-by-visit interaction and prior biologic treatment (not included for the subgroup analysis by prior biologic treatment) as fixed effects and baseline score as the covariate. Results: Overall, 259 patients were included in this study. PASI 75 response rates with zasocitinib were greater than placebo regardless of weight (≤ 90 kg: placebo, 8.8%; 15 mg, 70.4%; 30 mg, 69.7%; > 90 kg: placebo, 0%; 15 mg, 65.4%; 30 mg, 63.2%, each p < 0.001), sex (male: placebo, 0%; 15 mg, 61.8%; 30 mg, 72.7%, each p < 0.001; female: placebo, 14.3%; 15 mg, 78.9% [ p < 0.001]; 30 mg, 57.9% [ p < 0.01]), age (≤ 40 years: placebo, 0%; 15 mg, 55.6% [ p < 0.01]; 30 mg, 62.5% [ p < 0.001]; > 40 years: placebo, 7.3%; 15 mg, 74.3%; 30 mg, 69.4%, each p < 0.001), race (White: placebo, 6.8%; 15 mg, 67.4%; 30 mg, 64.3%, each p < 0.001; non-White: placebo, 0%; 15 mg, 71.4% [ p < 0.05]; 30 mg, 80.0% [ p < 0.005], disease duration (≤ 10 years: placebo, 3.6%; 15 mg, 47.4%; 30 mg, 58.8%; >10 years: placebo, 8.3%; 15 mg, 79.4%; 30 mg, 71.4%, each p < 0.001), prior biologics (yes: placebo, 0%; 15 mg, 100% [ p < 0.001]; 30 mg, 37.5% [ p = 0.055, not significant]; no: placebo, 6.8%; 15 mg, 61.4%; 30 mg, 72.7%, each p < 0.001) and baseline PASI (≤ 16: placebo, 10.7%; 15 mg, 57.9%; 30 mg, 60.7%; > 16: placebo, 0%; 15 mg, 93.3%; 30 mg, 75.0%, each p < 0.001; Figure 1). PASI 90, PASI 100, PGA 0/1 and DLQI were also significantly improved with zasocitinib treatment versus placebo in almost all subgroups. Conclusion: Treatment with zasocitinib 15 mg or 30 mg demonstrated consistent improvements in PASI 75, PASI 90, PASI 100, PGA 0/1 and DLQI at Week 12 versus placebo in patients with moderate-to-severe plaque psoriasis, regardless of baseline weight, sex, age, disease duration, prior biologic use and PASI. Phase 3 trials (NCT06088043 and NCT06108544) are ongoing to investigate the efficacy and safety of zasocitinib in larger patient groups. REFERENCES: [1] Armstrong A, et al. JAMA Dermatol 2024;160:1066–74. Acknowledgements: This study was funded by Nimbus Discovery, Inc. and Takeda Development Center Americas, Inc. Writing assistance was provided by Tina Borg, PhD, of Oxford PharmaGenesis and funded by Takeda Development Center Americas, Inc. Nimbus refers to the group of entities including Nimbus Therapeutics LLC, Nimbus Discovery Inc., and Nimbus Lakshmi Inc. Disclosure of Interests: Nada Elbuluk has received royalties from McGraw Hill, has stock options in VisualDx, is a consultant, advisory board member, and/or speaker for AbbVie, Allergan, Avita, Beiersdorf, Dior, Eli Lilly, Galderma, Incyte, Janssen, La Roche Posay, L'Oreal, McGraw Hill, Medscape, Pfizer, Sanofi, Takeda, Unilever, VisualDx, and has received grant funding from Pfizer, Melinda Gooderham is an investigator, speaker and/or advisor for AbbVie, Akros, Amgen, AnaptysBio, Apogee, Arcutis Biotherapeutics, Aristea, Bausch Health, Boehringer Ingelheim, Bristol Myers Squibb, Dermavant, Dermira, Eli Lilly, Galderma, GSK, Incyte, Inmagene, JAMP, Janssen, Kyowa Kirin, LEO Pharma, MedImmune, Meiji, MoonLake Immunotherapeutics, Nimbus, Novartis, Pfizer, Regeneron, Sanofi Genzyme, Sun Pharma, Takeda, Tarsus Pharmaceuticals, UCB, Union Therapeutics, Ventyx Biosciences and Vyne Therapeutics, Jessamyn Blau is an equity holder and an employee of Takeda, Wenwen Zhang is an equity holder and an employee of Takeda, Jonathan Uy is an equity holder and an employee of Takeda, Warren Winkelman is an equity holder and an employee of Takeda, Mark Lebwohl is a consultant for Almirall, AltruBio, Apogee Therapeutics, Arcutis Biotherapeutics, AstraZeneca, Atomwise, Avotres, Boehringer Ingelheim, Bristol Myers Squibb, Castle Biosciences, Celltrion, CorEvitas, Dermavant, Dermsquared, Evommune, Facilitation of International Dermatology Education, Forte Biosciences, Galderma, Genentech, Incyte, LEO Pharma, Meiji Seika Pharma, Mindera, Pfizer, Sanofi-Regeneron, Seanergy, Strata, Takeda, Trevi Therapeutics and Verrica Pharmaceuticals, is an employee of Mount Sinai, and receives research funds from AbbVie, Arcutis Biotherapeutics, Avotres, Boehringer Ingelheim, Cara Therapeutics, Clexio Biosciences, Dermavant, Eli Lilly, Incyte, Inozyme, Janssen, Pfizer, Sanofi-Regeneron 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)0,004
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 enseignants0,007
Score d'incertitude au seuil0,022

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,002
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0030,003
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,001
Communication savante0,0010,001
Science ouverte0,0010,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0070,001

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 Opus0,029
Tête enseignante GPT0,314
Écart entre enseignants0,286 · 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
Publié2025
Routes d'admission1
Résumé présentoui

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