P164 Do real-world treatment patterns reflect PsA recommendations? Results from the PRO-SPIRIT study
Notice bibliographique
Résumé
Abstract Background/Aims The Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) and the European Alliance of Associations for Rheumatology (EULAR) developed recommendation sets for psoriatic arthritis (PsA) treatment based on current evidence. All biologic disease-modifying anti-rheumatic drugs (bDMARDs) are equally recommended for peripheral arthritis. Different treatments exist for relevant skin and axial involvement. Interleukin 17 (IL-17) inhibitors (i) and IL-12/23i are recommended over tumour necrosis factor inhibitors (TNFi) for PsA with significant skin involvement. IL-12/23i are not recommended with axial manifestations. PRO-SPIRIT is the first large sample prospective multi-national observational PsA study. The objective of this study was to report the real-world treatment patterns reflecting PsA recommendations using results from the PRO-SPIRIT study. Methods PRO-SPIRIT enrolled adults with PsA from 2019 to 2022 who initiated or switched to approved biologic or targeted synthetic disease-modifying anti-rheumatic drugs (b/tsDMARD). Treatment groups included TNFi, IL-17Ai, IL-12/23i, IL-23i, Janus kinase (JAKi), and phosphodiesterase-4 (PDE4i). Mode of action (MoA) was at the discretion of the treating physician. Patient demographic, disease activity, treatment characteristics, and clinical and patient-reported outcomes were collected at baseline (BL). Descriptive results are presented. Missing BL values were imputed. Results Analysis includes 1,192 patients with PsA treated by different MoA. Patients with arthritis (defined by swollen joint count (SJC) and tender joint count (TJC) ≥5) were equally distributed across treatment classes except for a lower percentage in PDE4i. Patients receiving IL-17Ai commonly presented with joint, skin, and nail involvement. Patients with higher skin (body surface area (BSA) ≥3%) and nail involvement were more commonly treated by IL-17Ai and IL-23i, less so with JAKi. Patients receiving JAKi presented with more joint and axial, and less skin involvement. After IL-23i, PDE4i had the second highest proportion of patients with nail involvement. PDE4i patients were low and reported less active domain affectation in general. Line of therapy results showed more patients treated with IL-12/23i, JAKi, and IL-17Ai after prior b/tsDMARDs treatment. Conclusion In general, patients had polyarticular disease at BL. Pts with skin and nail involvement were more commonly treated with IL-17Ai and IL-23i over TNFi and JAKi. Patients with axial manifestations were more commonly treated with IL-17Ai and JAKi over IL-12/23i and IL-23i. Findings add to the evidence on real-world PsA treatment patterns and recommendations sets for guiding individualised PsA treatment. Disclosure W. Tillett: Honoraria; AbbVie, Amgen, Celgene, Eli Lilly and Company, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, and UCB Pharma. M. Nisar: Honoraria; AbbVie, Bristol Myers Squibb, Celgene, Chugai, Eli Lilly and Company, Merck Sharp and Dohme, Novartis, Pfizer, Roche, and UCB Pharma. V. Chandran: Grants/research support; AbbVie, and is a consultant for: AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly and Company, Janssen, Novartis, Pfizer, and UCB Pharma. K. Ng: Shareholder/stock ownership; Employee and shareholder of Eli Lilly and Company. M. Ngantcha: Shareholder/stock ownership; Employee and shareholder of Eli Lilly and Company. C. Laedermann: Shareholder/stock ownership; Employee and shareholder of Eli Lilly and Company. S. Moyano: Shareholder/stock ownership; Employee and shareholder of Eli Lilly and Company. R. Alten: Grants/research support; AbbVie, Bristol Myers Squibb, Eli Lilly and Company, Galapagos NV, Gilead Sciences, Janssen, Novartis, Pfizer, and UCB Pharma. L. Kristensen: Consultancies; AbbVie, Amgen, Biogen, Bristol Myers Squibb, Eli Lilly and Company, Gilead Sciences, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, and UCB Pharma. Grants/research support; AbbVie, Biogen, Eli Lilly and Company, Gilead Sciences, Janssen, Novartis, Pfizer, and UCB Pharma.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,046 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».