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Enregistrement W4411410168 · doi:10.1016/j.ard.2025.06.1415

ABS0974 EARLY IMPROVEMENTS IN CLINICAL DISEASE ACTIVITY INDEX FOR PSORIATIC ARTHRITIS AND ITS COMPONENTS WITH GUSELKUMAB PREDICT CLINICAL RESPONSE IN TNFi-EXPERIENCED AND BIOLOGIC-NAÏVE PARTICIPANTS WITH ACTIVE PSORIATIC ARTHRITIS: POST HOC ANALYSES OF THREE PHASE 3, RANDOMIZED, CONTROLLED STUDIES

2025· article· en· W4411410168 sur OpenAlexaff
L. Gossec, M. Sharaf, Philipp Sewerin, J. H. Galloway, Maria Antonietta D’Agostino, J. Ramírez, E. Rampakakis, K. Lozenski, Suad Hannawi, Andreas Kerschbaumer

Notice bibliographique

RevueAnnals of the Rheumatic Diseases · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueRheumatoid Arthritis Research and Therapies
Établissements canadiensMcGill University
Organismes subventionnairesnon disponible
Mots-clésMedicinePsoriatic arthritisPsoriasisDermatologyArthritisClinical trialInternal medicine

Résumé

récupéré en direct d'OpenAlex

Background: Feasibility of an outcome measure is the main criterion for its use in psoriatic arthritis (PsA) disease monitoring and implementation of treat-to-target in routine clinical practice. The Disease Activity Index for PsA (DAPSA), a comprehensive tool for evaluating joint disease activity, includes 66/68 swollen/tender joint counts (SJC/TJC), CRP, and patient-reported outcomes (PROs; global assessment of arthritis [PtGA-Arthritis], and pain [Pt Pain]). Given that routine evaluation of CRP is limited, the clinical DAPSA (cDAPSA) was developed as a simplified tool to assess PsA disease activity, with a performance comparable to DAPSA [1], but omitting CRP. Objectives: To evaluate the utility of cDAPSA in monitoring disease activity in both TNF inhibitor (i)-experienced and biologic-naïve PsA patients, we assessed the predictive value of early improvements in cDAPSA and its components for downstream achieviement of low disease activity (LDA) using a large cohort of participants (pts) pooled from 3 randomized controlled trials (RCTs). Methods: Data were pooled from 3 RCTs (DISCOVER-1 [NCT03162796], DISCOVER-2 [NCT03158285], COSMOS [NCT03796858]) of PsA pts receiving guselkumab (GUS) every 4 weeks (Q4W) or at W0, W4, and Q8W, or placebo (PBO). Only pts with baseline cDAPSA score ≥14 were included in these post hoc analyses. W4 cDAPSA total and item score cutoffs predictive of LDA/remission (REM) achievement at W24 in pooled GUS groups were determined separately in TNF inhibitor (i)-experienced and biologic-naïve cohorts with receiver operator characteristic analyses. Achievement of cDAPSA total and item score cutoffs over 24W was compared between GUS Q8W (regimen common to all 3 studies) and PBO in both cohorts using logistic regression. Nonresponder imputation was used for missing data. Further analyses included logistic regression to determine the association between achievement of early (W4) response (cDAPSA total and item score cutoffs) and achievement of LDA/REM at W24 in GUS Q8W. The proportion of patients achieving LDA/REM at W48 among non-acheivers at W24 was also assessed. Results: Among biologic-naïve (N=995) and TNFi-experienced (N=403) PsA pts pooled across 3 RCTs, baseline patient characteristics were generally comparable across prior treatment cohorts, although more biologic-naïve pts reported NSAID use at baseline. W4 cutoffs for cDAPSA total and PRO item scores predictive of LDA/REM achievement at W24 were similar across prior treatment cohorts, while less stringent W4 joint count cutoffs were observed in biologic-naïve than TNFi-experienced pts (SJC: 5.0 vs 3.0; TJC: 13.0 vs 8.0; Table 1). As early as W4 (after 1 dose), GUS Q8W was associated with higher odds of achieving PRO cutoffs (vs PBO) in the biologic-naïve cohort (odds ratios [OR] for both PtGA-Arthritis and Pt Pain: 1.8), and of achieving PtGA-Arthritis (OR: 2.2) and cDAPSA total score (OR: 2.2) cutoffs in TNFi-experienced pts. Odds of achieving all derived cutoffs were consistently higher with GUS Q8W through W24 in both the biologic-naïve and TNFi-experienced cohorts (OR range at W24: 1.8-2.5 and 1.7-2.6, respectively). GUS Q8W pts achieving the derived cutoffs at W4 were more likely to achieve LDA/REM than non-achievers across the biologic-naïve and TNFi-experienced cohorts (OR range: 2.6-5.3 and 4.1-6.6, respectively; Figure 1). Across these cohorts, 32% of GUS Q8W pts who did not achieve LDA/REM at W24 did so at W48. Conclusion: In a PsA population pooled across 3 RCTs, early improvements in cDAPSA total and constituent item scores with GUS Q8W were associated with higher odds of achieving long-term joint disease activity control, regardless of treatment history. The derived cutoffs suggest that TNFi-experienced pts may need to achieve lower SJCs and TJCs to attain sustained control of joint disease activity. These findings support the utility of cDAPSA, and particularly its PRO components, in assessing early improvements in joint disease activity that predict future achievement of low levels of joint disease. REFERENCES: [1] Schoels MM, et al. Ann Rheum Dis. 2016; 75(5):811-8. Acknowledgements: NIL . Disclosure of Interests: Laure Gossec AbbVie, AlfaSigma, Amgen, Bristol Myers Squibb, Celltrion, Janssen, Eli Lilly, MSD, Novartis, Pfizer, Stada, and UCB, AbbVie, Biogen, Eli Lilly, Novartis, UCB, Mohamed Sharaf Johnson & Johnson, EMEA Medical Affairs, Johnson & Johnson Middle East FZ LLC, Dubai, United Arab Emirates, Philipp Sewerin Amgen, AbbVie, Biogen, Bristol Myers Squibb, Celgene, Eli Lilly, Gilead Sciences, Hexal Pharma, Janssen, Novartis Pharma, Pfizer, Roche Pharma, Rheumazentrum Rhein-Ruhr, Sanofi-Genzyme, Swedish Orphan Biovitrum, and UCB Pharma, AXIOM Health, Amgen, AbbVie, Biogen, Bristol Myers Squibb, Celgene, Chugai Pharma Marketing Ltd/Chugai Europe, Deutscher Psoriasis-Bund, Eli Lilly, Gilead Sciences, Hexal Pharma, Janssen, Mediri GmbH, Novartis Pharma, Onkowissen GmbH, Pfizer, Roche Pharma, Rheumazentrum Rhein-Ruhr, Sanofi-Genzyme, Spirit Medical Communication, Swedish Orphan Biovitrum, and UCB Pharma, James Galloway Abbvie, Alfasigma, Galapagos, Janssen, Eli Lilly, Pfizer, and UCB, Abbvie, Alfasigma, Galapagos, Janssen, Eli Lilly, Pfizer, and UCB, Maria Antonietta D'Agostino AbbVie, Bristol Myers Squibb, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, and UCB, Julio Ramírez AbbVie, Angem, Eli Lilly, Janssen, Novartis, Pfizer, UCB, AbbVie, Janssen, Novartis, and UCB, Emmanouil Rampakakis JSS Medical Research, Janssen, Karissa Lozenski Johnson & Johnson, and Bristol Myers Squibb, Immunology Global Medical Affairs, Janssen Pharmaceutical Companies of Johnson & Johnson, Suad Hannawi AbbVie, Amgen, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Janssen, New Bridge, and Novartis, AbbVie, Amgen, AstraZeneca, Eli Lilly, and Janssen, Andreas Kerschbaumer Eli Lilly, Galapagos, Janssen, MSD, Novartis, and Pfizer, AbbVie, Lilly, Gilead, Janssen, 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)0,018
score de la tête « metaresearch » (Gemma)0,014
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 enseignants0,018
Score d'incertitude au seuil0,096

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0180,014
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0040,011
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,001
Communication savante0,0020,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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 Opus0,119
Tête enseignante GPT0,457
Écart entre enseignants0,338 · 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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