393 Comparative efficacy of targeted systemic therapies for moderate-to-severe atopic dermatitis without topical corticosteroids: an updated network meta-analysis
Notice bibliographique
Résumé
Abstract The landscape of targeted systemic treatments for moderate-to-severe atopic dermatitis (AD) continues to expand. With limited head-to-head randomized controlled trials conducted in AD, a network meta-analysis (NMA) helps inform treatment decisions by providing indirect comparisons across therapies. This study aims to update an NMA presented in Silverberg et al. (2022), assessing the comparative efficacy of targeted systemic treatments without concomitant topical corticosteroids in moderate-to-severe AD by including the latest Phase 3 monotherapy data for lebrikizumab. Data from the two most recently published Phase 3 monotherapy trials for lebrikizumab in moderate-to-severe AD [ADvocate1 (NCT04146363); ADvocate2 (NCT04178967)] were included in the analyses along with other eligible Phase 3 or 4 randomized placebo-controlled trials for abrocitinib, baricitinib, dupilumab, tralokinumab and upadacitinib identified through a systemic literature review in Silverberg et al. (2022). Prespecified efficacy outcomes included ≥90% and ≥75% improvement in Eczema Area and Severity Index (EASI 90, EASI 75) from baseline, ≥4-point improvement in Pruritus Numerical Rating Scale from baseline (ΔNRS ≥4) and Investigator Global Assessment (IGA) score of 0 or 1 (clear or almost clear) with a ≥2-point reduction from baseline (IGA 0/1), at the primary endpoint timepoint for each study (Week 12 for abrocitinib, Week 16 for all other therapies). Bayesian NMA was performed with fixed-effect, random-effect and baseline risk-adjusted models; fit statistics and diagnostics were assessed. The odds ratio (OR), number needed to treat (NNT), placebo-unadjusted absolute response rate (ARR) and Surface Under the Cumulative RAnking curve (SUCRA) scores were estimated. Statistical significance was assessed by OR 95% credible intervals excluding 1. The updated NMA analysed 13 unique placebo-controlled trials involving 7105 patients in 32 arms across six targeted therapies. Fit statistics and diagnostics supported fixed-effect models for all outcomes analysed. All targeted therapies had significantly greater response rates compared with placebo across all outcomes. For EASI 90, upadacitinib 30 mg had the most favorable response estimates (ARR = 58.3%, OR = 23.1, NNT = 1.9, SUCRA = 98.5%), followed by abrocitinib 200 mg (ARR = 45.2%, OR = 13.5, NNT = 2.5, SUCRA = 84.3%), upadacitinib 15 mg (ARR = 43.7%, OR = 12.8, NNT = 2.6, SUCRA = 82.0%), dupilumab 300 mg (ARR = 27.3%, OR = 6.2, NNT = 4.7, SUCRA = 52.8%), abrocitinib 100 mg (ARR = 26.8%, OR = 6.0, NNT = 4.8, SUCRA = 48.4%), baricitinib 4 mg (ARR = 25.0%, OR = 5.5, NNT = 5.2, SUCRA = 45.5%) and lebrikizumab 250 mg (ARR = 23.6%, OR = 5.1, NNT = 5.6, SUCRA = 40.0%). A similar rank order was observed for EASI 75 [upadacitinib 30 mg (ARR = 72.3%, OR = 19.1, NNT = 1.7, SUCRA = 98.5%), abrocitinib 200 mg (ARR = 64.6%, OR = 13.3, NNT = 1.9, SUCRA = 87.3%), upadacitinib 15 mg (ARR = 59.8%, OR = 10.9, NNT = 2.1, SUCRA = 80.2%), dupilumab 300 mg (ARR = 45.3%, OR = 6.0, NNT = 3.0, SUCRA = 55.4%), abrocitinib 100 mg (ARR = 44.9%, OR = 5.9, NNT = 3.1, SUCRA = 53.5%) and lebrikizumab 250 mg (ARR = 44.7%, OR = 5.9, NNT = 3.1, SUCRA = 53.9%)]. For ΔNRS ≥4, upadacitinib 30 mg also had the most favorable response (ARR = 56.1%, OR = 12.9, NNT = 2.1, SUCRA = 99.0%), followed by abrocitinib 200 mg (ARR = 45.4%, OR = 8.3, NNT = 2.8, SUCRA = 83.6%), upadacitinib 15 mg (ARR = 42.9%, OR = 7.6, NNT = 3.0, SUCRA = 79.2%), dupilumab 300 mg (ARR = 33.9%, OR = 5.2, NNT = 4.0, SUCRA = 54.2%), lebrikizumab 250 mg (ARR = 33.9%, OR = 5.1, NNT = 4.1, SUCRA = 54.1%) and abrocitinib 100 mg (ARR = 31.5%, OR = 4.6, NNT = 4.5, SUCRA = 46.1%). For IGA 0/1, upadacitinib 30 mg (ARR = 61.8%, OR = 19.4, NNT = 1.9, SUCRA = 99.9%) and upadacitinib 15 mg (ARR = 48.1%, OR = 11.1, NNT = 2.5, SUCRA = 86.9%) had the most favorable estimates, followed by abrocitinib 200 mg (ARR = 39.3%, OR = 7.7, NNT = 3.2, SUCRA = 75.5%), dupilumab 300 mg (ARR = 32.4%, OR = 5.7, NNT = 4.1, SUCRA = 62.1%) and lebrikizumab 250 mg (ARR = 28.0%, OR = 4.7, NNT = 5.0, SUCRA = 49.1%). Baricitinib 2 mg and tralokinumab 300 mg were generally ranked lower across outcomes. Among targeted treatments for moderate-to-severe AD used without concomitant topical corticosteroids for 12–16 weeks, upadacitinib 30 mg remains the most efficacious therapy in this NMA, generally followed by abrocitinib 200 mg, upadacitinib 15 mg, dupilumab 300 mg and lebrikizumab 250 mg or abrocitinib 100 mg.
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 | 0,027 | 0,043 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,011 | 0,048 |
| Bibliométrie | 0,005 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 ».