516 - Comparative efficacy of targeted systemic therapies with topical corticosteroids for moderate-to-severe atopic dermatitis: an updated network meta-analysis
Notice bibliographique
Résumé
Abstract Introduction Network meta-analysis (NMA) provides useful information for medical decision makers via comprehensive indirect comparisons across therapies. As the targeted systemic therapy options for moderate-to-severe atopic dermatitis (AD) continue to grow, it is critical to update NMAs as well. Objectives To assess the comparative efficacy of targeted systemic therapies with concomitant topical corticosteroids (TCS) in moderate-to-severe AD by including the latest Phase 3 combination therapy data for abrocitinib, lebrikizumab, and dupilumab in the NMA presented in Thyssen et al, 2021.1 Methods Data from the Phase 3 combination therapy trial for lebrikizumab in moderate-to-severe AD (ADhere [NCT04250337]) as well as an additional abrocitinib-dupilumab head-to-head Phase 3 trial (JADE DARE [NCT04345367]) were included in the analyses along with other eligible trials for abrocitinib, baricitinib, dupilumab, tralokinumab, and upadacitinib identified through a systematic literature review in Thyssen et al., 2021. 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 week 16 timepoint of each study. Bayesian NMA was performed with fixed and random effects models, with and without baseline risk-adjustment; fit statistics were assessed. Inconsistency was assessed via unrelated mean relative effects models. 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. Results The updated NMA analyzed 8 unique placebo-controlled trials and 1 active-controlled trial involving 4391 patients in 23 arms across 6 targeted therapies. Fit statistics supported fixed effects models across outcomes. All therapies were statistically more efficacious than placebo across all outcomes except baricitinib 2 mg for EASI-90. For EASI-90, upadacitinib 30 mg had the most favorable response estimates (ARR=63.2%, OR=11.3, NNT=2.0, SUCRA=98.3%), followed by abrocitinib 200 mg (ARR=55.8%, OR=8.3, NNT=2.4, SUCRA=90.0%), dupilumab 300 mg (ARR=44.8%, OR=5.3, NNT=3.2, SUCRA=68.3%), abrocitinib 100 mg (ARR=44.0%, OR=5.2, NNT=3.3, SUCRA=65.8%), upadacitinib 15 mg (ARR=42.9%, OR=4.9, NNT=3.4, SUCRA=64.3%), and the newly added lebrikizumab 250 mg (ARR=28.9%, OR=2.7, NNT=6.6, SUCRA=39.9%). The rank order for EASI-75 was similar (upadacitinib 30 mg [ARR=78.3%, OR=9.5, NNT=2.0, SUCRA=98.5%], abrocitinib 200 mg [ARR=73.0%,OR=7.1, NNT=2.3, SUCRA=89.1%], upadacitinib 15 mg [ARR=66.1%, OR=5.1, NNT=2.7, SUCRA=71.0%], dupilumab 300 mg [ARR=65.3%, OR=5.0, NNT=2.7, SUCRA=69.2%], abrocitinib 100 mg [ARR=60.3%, OR=4.0, NNT=3.2, SUCRA=54.0%], and lebrikizumab 250 mg [ARR=54.5%, OR=3.1, NNT=3.8, SUCRA=41.2%]). For ΔNRS ≥4, upadacitinib 30 mg had the most favorable response (ARR=68.9%, OR=10.0, NNT=2.1, SUCRA=99.9%), followed by upadacitinib 15 mg (ARR=56.6%, OR=5.9, NNT=2.7, SUCRA=84.0%), abrocitinib 200 mg (ARR=51.6%, OR=4.8, NNT=3.1, SUCRA=75.6%), dupilumab 300 mg (ARR=49.3%, OR=4.4, NNT=3.3, SUCRA=67.0%), baricitinib 4 mg (ARR=44.4%, OR=3.6, NNT=4.0, SUCRA=57.7%), and abrocitinib 100 mg (ARR=35.9%, OR=2.5, NNT=5.9, SUCRA=36.1%); lebrikizumab 250 mg ranked eighth (ARR=33.4%, OR=2.3, NNT=7.0, SUCRA=31.3%). For IGA 0/1, upadacitinib 30 mg (ARR=66.5%,OR=11.7, NNT=2.0, SUCRA=99.6%) had the most favorable estimates, followed by abrocitinib 200 mg (ARR=53.5%, OR=6.8, NNT=2.6, SUCRA=86.6%), upadacitinib 15 mg (ARR=48.0%, OR=5.4, NNT=3.0, SUCRA=76.2%), dupilumab 300 mg (ARR=42.1%, OR=4.3, NNT=3.7, SUCRA=64.7%), abrocitinib 100 mg (ARR=39.1%, OR=3.8, NNT=4.1, SUCRA=56.1%), and baricitinib 4 mg (ARR=30.6%, OR=2.6, NNT=6.4, SUCRA=39.9%); lebrikizumab 250 mg ranked seventh (ARR=29.2%, OR=2.4, NNT=7.0, SUCRA=35.8%). Baricitinib 2 mg and tralokinumab 300 mg were generally ranked lower across outcomes. Conclusions Among targeted therapies for moderate-to-severe AD used with concomitant TCS for 16 weeks, upadacitinib 30 mg remained the most efficacious therapy in this NMA, generally followed by abrocitinib 200 mg, upadacitinib 15 mg or dupilumab 300 mg, abrocitinib 100 mg, and baricitinib 4 mg or lebrikizumab 250 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 | 0,059 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,011 | 0,051 |
| Bibliométrie | 0,005 | 0,005 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| 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 ».