O32 Impact of patient baseline characteristics on SLE Responder Index-4 (SRI[4]) responses to deucravacitinib, a first-in-class, oral, selective, allosteric tyrosine kinase 2 inhibitor in the phase 2 PAISLEY trial in systemic lupus erythematosus
Notice bibliographique
Résumé
Objective Deucravacitinib is a first-in-class, oral, selective, allosteric tyrosine kinase 2 (TYK2) inhibitor approved in multiple countries for the treatment of adults with moderate to severe plaque psoriasis. Deucravacitinib inhibits TYK2-mediated signaling of cytokines, such as type 1 interferons, involved in systemic lupus erythematosus (SLE). In the 48-week, double-blind, phase 2 PAISLEY trial in patients with active SLE (NCT03252587), all primary and secondary endpoints were met at the 3 mg twice-daily (BID) deucravacitinib dose, including SLE Responder Index-4 (SRI[4]) response rates vs placebo at weeks 32 (primary endpoint) and 48. Week 32 response rates were 34.4% vs 58.2%, 49.5%, and 44.9% with placebo vs deucravacitinib 3 mg BID, 6 mg BID, and 12 mg once daily (QD), respectively. This exploratory analysis assessed the efficacy of deucravacitinib according to patient baseline characteristics. Methods In the PAISLEY trial, patients with active SLE were randomized 1:1:1:1 to receive placebo (n=90) or deucravacitinib 3 mg BID (n=91), 6 mg BID (n=93), or 12 mg QD (n=89). SRI(4) response rates at week 32 in the phase 2 PAISLEY trial were evaluated according to select baseline demographics and disease characteristics. Point estimates for response rates with asymptotic CIs were calculated for each treatment arm within each subgroup. All analyses were descriptive. Results SRI(4) response rates in most analyzed subgroups were consistent with the observed response rates in the overall population and favored the 3 mg BID deucravacitinib dose. SRI(4) response rates in subgroups defined by race, baseline SLEDAI-2K and glucocorticoid dose, and years since initial diagnosis are provided below (figure 1). Of these, Black/African American race, other race, baseline SLEDAI-2K of <10, baseline glucocorticoid dose of ≥10 mg/day, and 3–6 and ≥6 years since diagnosis showed the greatest difference in SRI(4) responses for those receiving deucravacitinib vs placebo. Conclusion Deucravacitinib was associated with improved SRI(4) response rates at week 32 across race, SLEDAI-2K, glucocorticoid dose, and years since diagnosis at baseline subgroups. Data interpretation for some subgroups was limited by low patient numbers. These findings support the efficacy of deucravacitinib in the treatment of patients with active SLE, regardless of patient baseline characteristics. Acknowledgements We thank the patients and their families who made this study possible, as well as the clinical teams who participated. This study was sponsored by Bristol Myers Squibb. Professional medical writing assistance was provided by Angela R. Eder, PhD, of SciMentum, Inc, a Nucleus Group Holdings, Inc, company, and funded by Bristol Myers Squibb. COI Disclosures EM: Research support: AbbVie, Amgen, AstraZeneca, Biogen, Bristol Myers Squibb, Eli Lilly, EMD Serono, Genentech, GSK, Janssen, and UCB; Consultancy: AstraZeneca, Biogen, Bristol Myers Squibb, Eli Lilly, EMD Serono, Genentech, Gilead, Novartis, and Servier CA: Grant support: AstraZeneca and Bristol Myers Squibb; Advisor or review panel: AstraZeneca, Aurinia, Bristol Myers Squibb, GSK, and Kezar; Speaker/honoraria: AstraZeneca and Aurinia LGP: Consultancy: Aurinia and Bristol Myers Squibb AC: Research support: AstraZeneca and GSK; Consultancy/Speaker: AstraZeneca and GSK; Consultancy: Bristol Myers Squibb, Otsuka, and Roche SP, CH, TW, and SB: Employees and shareholders: Bristol Myers Squibb RK: Employee of Syneos Health, providing statistical services to Bristol Myers Squibb RvV: Research support: Bristol Myers Squibb, GSK, and Eli Lilly; Research support, consultancy, and speaker: UCB; Support for educational programs, consultancy, and speaker: Pfizer; Support for educational programs: Roche; Consultancy and speaker: AbbVie, Galapagos, and Janssen; Consultancy: AstraZeneca, Biogen, Biotest, Celgene, Gilead, and Servier
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 | 0,003 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 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 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 ».