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Enregistrement W4379522682 · doi:10.1136/annrheumdis-2023-eular.2761

POS0023 PERFORMANCE OF BASDAI VS. ASDAS IN EVALUATING AXIAL INVOLVEMENT IN PATIENTS WITH PSA TREATED WITH GUSELKUMAB: POOLED ANALYSIS OF TWO PHASE 3 STUDIES

2023· article· en· W4379522682 sur OpenAlexaff
Xenofon Baraliakos, Dafna D. Gladman, Soumya D. Chakravarty, Cinty Gong, M. Shawi, Emmanouil Rampakakis, Mitsumasa Kishimoto, Enrique R. Soriano, P. J. Mease

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomainePharmacology, Toxicology and Pharmaceutics
ThématiqueDrug-Induced Hepatotoxicity and Protection
Établissements canadiensMcGill UniversityToronto Western Hospital
Organismes subventionnairesnon disponible
Mots-clésMedicineBASDAIInternal medicineArthritisPsoriatic arthritis

Résumé

récupéré en direct d'OpenAlex

<h3>Background</h3> Although the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) is used to assess the activity of axial disease in patients (pts) with psoriatic arthritis (PsA), only one of its questions is specific to axial symptoms. Alternatively, the Ankylosing Spondylitis Disease Activity Score (ASDAS) excludes assessment of enthesitis, gives less weight to peripheral activity and is considered more objective than the BASDAI. <h3>Objectives</h3> The current post hoc analysis aimed to compare the performance of BASDAI and ASDAS in evaluating symptoms of axial involvement in pts with axial PsA (axPsA). <h3>Methods</h3> Pts enrolled in the DISCOVER-1 (D1) and DISCOVER-2 (D2) studies were adults with active PsA despite standard therapies. D1 pts had ≥3 swollen and ≥3 tender joints (SJC; TJC) and C-reactive protein (CRP) ≥0.3 mg/dL; D2 pts had SJC ≥5, TJC ≥5 and CRP ≥0.6 mg/dL. 31% of D1 pts received 1-2 prior tumor necrosis factor inhibitors; D2 pts were biologic-naïve. Pts were randomized 1:1:1 to GUS 100 mg every 4 weeks (Q4W); GUS 100 mg at W0, W4, then Q8W; or placebo with crossover to GUS Q4W at W24. axPsA was defined by presence of sacroiliitis based on previous radiograph or magnetic resonance (MR) imaging confirmation. Data were pooled across all treatment groups. In addition to BASDAI and ASDAS, modified versions excluding the peripheral arthritis and enthesitis questions (mBASDAI) and the peripheral arthritis question (mASDAS) were calculated. Normalized (scale of 0-10) versions of ASDAS and mASDAS were calculated based on maximum scores of ≈7 and ≈6.3, respectively. The correlation of BASDAI/mBASDAI and ASDAS/mASDAS with SJC, TJC, enthesitis, Functional Assessment of Chronic Illness Therapy (FACIT)-fatigue, pt pain, pt global, and physician global was assessed with Pearson’s correlation coefficient. The cross-sectional and longitudinal (W52) effects of Leeds enthesitis index (LEI), SJC, and axPsA on BASDAI/mBASDAI and ASDAS/mASDAS were assessed with mixed models. <h3>Results</h3> 436 pts with available baseline (BL) BASDAI information were included in the analysis. In pts with axPsA, BASDAI showed weak correlation with SJC, TJC, LEI, and physician global; moderate correlation with fatigue; and strong correlation with pt global and pt pain. Similar results were observed for ASDAS and modified versions. Among pts without axPsA, correlations of BASDAI and ASDAS with SJC, TJC, and LEI remained weak; correlations with pt global and pt pain remained strong. Longitudinally, among pts with and without BL enthesitis, respectively, LEI and SJC showed significant but not clinically important associations with either outcome. Presence of axial disease was associated with significantly greater BASDAI and ASDAS scores, at BL and longitudinally, without differences in the incremental effect on BASDAI, normalized ASDAS, or their modified versions. <h3>Conclusion</h3> In pts with axPsA, the BASDAI and ASDAS performed similarly, with both demonstrating weak correlations with peripheral arthritis and moderate/strong correlations with pt fatigue and pain. The BASDAI and ASDAS also showed similar ability to discern changes in axial disease activity. These results suggest that both BASDAI and ASDAS are valid, and perform comparably, in assessing activity of axial disease in PsA pts. <h3>REFERENCES:</h3> NIL. <h3>Acknowledgements:</h3> NIL. <h3>Disclosure of Interests</h3> Xenofon Baraliakos Consultant of: AbbVie, Chugai, Eli Lilly, Galapagos, Janssen, MSD, Novartis, Pfizer, Roche, and UCB, Grant/research support from: AbbVie, MSD, and Novartis, Dafna D Gladman Consultant of: BMS, Galapagos, Gilead, and Novartis, Grant/research support from: AbbVie, Amgen, Eli Lilly, Janssen, Pfizer, UCB, Soumya D Chakravarty Employee of: Janssen Scientific Affairs, LLC and shareholder in Johnson &amp; Johnson, of which Janssen Scientific Affairs, LLC is a wholly-owned subsidiary, Cinty Gong Employee of: Janssen Scientific Affairs, LLC and shareholder in Johnson &amp; Johnson, of which Janssen Scientific Affairs, LLC is a wholly-owned subsidiary, May Shawi Shareholder of: Johnson &amp; Johnson, Employee of: Janssen Pharmaceutical Companies, a wholly-owned subsidiary of Johnson &amp; Johnson, Emmanouil Rampakakis Consultant of: Janssen, Employee of: JSS Medical Research, Mitsumasa Kishimoto Speakers bureau: AbbVie, Amgen, Asahi-Kasei Pharma, Astellas, Ayumi Pharma, BMS, Chugai, Daiichi-Sankyo, Eisai, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, Tanabe-Mitsubishi, and UCB Pharma, Consultant of: AbbVie, Amgen, Asahi-Kasei Pharma, Astellas, Ayumi Pharma, BMS, Chugai, Daiichi-Sankyo, Eisai, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, Tanabe-Mitsubishi, and UCB Pharma, Enrique Soriano Speakers bureau: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and UCB, Consultant of: AbbVie, Janssen, Novartis, and Roche, Grant/research support from: AbbVie, Janssen, Novartis, Pfizer, Roche, and UCB, Philip J Mease Speakers bureau: AbbVie, Amgen, Eli Lilly, Janssen, Novartis, Pfizer, Sun Pharma, and UCB, Consultant of: AbbVie, Aclaris, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Inmagene, Janssen, Novartis, Pfizer, Sun Pharma, and UCB, Grant/research support from: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer, Sun Pharma, and UCB.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut 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 enseignants0,338
Score d'incertitude au seuil0,757

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,004
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,169
Tête enseignante GPT0,466
Écart entre enseignants0,297 · 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 tête enseignante, 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

Citations1
Publié2023
Routes d'admission1
Résumé présentoui

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