Guselkumab and Il-17 Inhibitors Improve Patient-Perceived Impact of Psoriatic Arthritis Similarly: 6 Month Interim Results of the PsABIOnd Observational Cohort Study
Notice bibliographique
Résumé
Objectives Targeted drugs in PsA have demonstrated efficacy in randomized controlled trials, including aspects of patient-reported impact. However, comparison data from observational studies are scarce, particularly for IL-23 and IL-17 inhibitors (i). As part of the 6 month (M) interim analysis of the first ≥600 participants (pts) enrolled in the PsABIOnd observational study, we assessed changes from baseline (BL) in PsA Impact of Disease-12 (PsAID12) following biologic treatment initiation. Methods PsABIOnd ( NCT05049798 ) is an ongoing international, prospective study in 1300 planned PsA pts starting guselkumab (GUS) or IL-17i as first- to fourth-line biologic therapy (monotherapy or in combination with other agents) per standard clinical practice.[1] All enrolled pts with available PsAID-12 data at BL and the 6M visit (± 3M) were analyzed according to their treatment group (regardless of later switches). Impact of PsA was assessed with PsAID-12 comprising 12 items (including pain, fatigue, skin problems, etc.) scored 010, with higher values indicating a worse state. Mean change from BL in PsAID-12 subdomain and total scores, and proportions of pts achieving minimal clinically important improvement (MCII, ≥1.4) at the 6M visit were determined. Propensity score (PS) analysis evaluated treatment effect for the change in PsAID-12 total score and MCII (using nonresponder imputation), adjusting for BL imbalances across cohorts. Subdomain analyses were descriptive. Results At the Jan 2024 cutoff date, 323 and 296 pts receiving GUS or IL-17i, respectively, with PsAID-12 data available at BL and the 6M visit were analyzed. In both cohorts, PsAID-12 subdomains with highest impact at BL were pain, fatigue, and discomfort. At the 6M visit, mean (95% confidence interval [CI]) changes from BL in PsAID-12 total score were similar in the GUS (−1.5 [−1.7; −1.3]) and IL-17i (1.6 [1.8; 1.3]) cohorts. PS-adjusted treatment effect (regression coefficient [95% CI]) for GUS vs IL17i in change from BL in PsAID-12 total score was not significant (0.2 [−0.3; 0.6]). Proportions of pts achieving MCII in PsAID-12 total score at the 6M visit were 53% and 48% in the GUS and IL-17i cohorts, respectively, with a non-significant PS-adjusted treatment effect (odds ratio [95% CI]: 1.2 [0.8; 1.8]). Mean changes from BL in subdomain scores were similar across cohorts (Figure 1). Figure 1: Mean change from baseline in PsAID-12 subdomain scores with guselkumab and IL-17i at the 6M visit Last observation carried forward was imputed for participants with no 6M visit. Propensity score-adjusted treatment effect (regression coefficient [95% CI]) for GUS vs IL-17i for pain; fatigue; skin problems; work/leisure activities; functional capacity; discomfort; sleep disturbance; coping; anxiety, fear and uncertainty; embarrassment/shame; social participation; and depression were: 0.4 (−0.2,0.9); 0.1 (−0.5, 0.6); −0.1 (−0.8, 0.6); 0.1 (−0.6, 0.7); 0.1 (−0.5, 0.7); 0.3 (−0.3,1.0); 0.2 (−0.4, 0.9); 0.4 (−0.3,1.0); 0.1 (−0.5, 0.7); −0.01 (−0.7, 0.6); 0.1 (−0.6, 0.8); and −0.1 (−0.6, 0.5), respectively. For participants who switched/stopped initial treatment, data occurring after the switch or stop was excluded from the analysis. Conclusion By 6M of treatment, clinically meaningful improvements in PsAID-12 total score were seen in around half of pts treated with GUS or IL-17i, with similar magnitudes of effect across subdomains in both cohorts. These results may be useful in shared treatment decision-making. [1.] Siebert S. Rheumatol Ther 2023;10:489.
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 | 0,005 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
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 ».