382 Lebrikizumab provides clinically meaningful improvements in atopic dermatitis in patients previously treated with dupilumab
Notice bibliographique
Résumé
Abstract Dupilumab is a treatment option for moderate-to-severe atopic dermatitis (AD). Not all patients treated with dupilumab achieve and maintain clinically meaningful responses; some experience adverse events and some discontinue dupilumab for other reasons. For these patients, prospective data are needed to better understand the efficacy of systemic medications administered after discontinuation of dupilumab. Lebrikizumab (LEB) is a monoclonal antibody that binds with high affinity and slow off-rate to interleukin (IL)-13, thereby blocking the downstream effects of IL-13 with high potency. ADhere (NCT04250337) is a randomized, double-blind phase 3 trial evaluating the efficacy of lebrikizumab in combination with topical corticosteroids (TCS) over 16 weeks in adults and adolescents with moderate-to-severe AD. The results of this study, previously reported, showed statistically and clinically meaningful improvements in the signs and symptoms of AD in patients treated with LEB plus TCS vs. placebo (PBO) plus TCS. Of the patients randomized to LEB plus TCS, 20 reported prior dupilumab exposure. This study aims to evaluate the efficacy of LEB plus low to mid-potency TCS for the treatment of moderate-to-severe AD in the subpopulation of ADhere patients with prior exposure to dupilumab. At baseline, eligible patients in ADhere were randomized 2 : 1 to LEB 250 mg plus TCS or PBO plus TCS. Patients with prior exposure to dupilumab were permitted, with at least 8 weeks of washout prior to entering the study. Reported medical history was used to identify patients with prior exposure to dupilumab. Efficacy was measured through Investigator’s Global Assessment (IGA), Eczema Area and Severity Index (EASI) and Pruritus Numeric Rating Scale (NRS). ADhere analyses were performed on a modified population, excluding 17 patients (from a single study site) whose eligibility could not be confirmed. All analyses are descriptive summaries using post hoc, as-observed analyses. The Pruritus NRS analysis only includes patients with baseline values ≥4. Observed results exclude data collected after use of rescue medication or treatment discontinuation. In ADhere, 211 patients were randomized 2 : 1 to LEB plus TCS (n = 145) or PBO plus TCS (n = 66). Of the patients randomized to LEB plus TCS, 20 reported prior dupilumab exposure. Of these 20 patients, the reason for dupilumab discontinuation was loss of response or inadequate response (10 patients), subject decision (four patients) or intolerance to medication (one patient). The final five patients discontinued due to affordability, treatment availability or unspecified reasons. In patients treated with LEB plus TCS, baseline disease characteristics were comparable between the overall LEB-treated population (n = 145) and the subpopulation with prior dupilumab exposure (n = 20). Of the 20 patients with prior dupilumab exposure, 13 patients presented with an IGA of three and seven patients presented with an IGA of 4. The mean [standard deviation (SD)] body surface area reported at baseline was 37.3 (15.7). The mean (SD) baseline scores for EASI and Pruritus NRS were 25.9 (8.1) and 7.8 (1.9), respectively. The mean (SD) duration since AD onset was longer in patients with prior dupilumab experience vs. the overall LEB-treated population 27.0 (22.5) vs. 21.0 (17.4) years, respectively]. In patients treated with LEB plus TCS, two of the 20 with prior dupilumab exposure were excluded due to use of rescue medication or treatment discontinuation. The IGA 0/1 with 2-point improvement was achieved by 6/18 patients, EASI 75 was achieved by 13/18 patients and Pruritus NRS 4-point improvement was achieved by 8/15 patients at Week 16. One patient reported rescue medication use. The results of this subpopulation analysis suggest that patients with prior dupilumab exposure can benefit from lebrikizumab treatment in combination with TCS. Additional data are needed to confirm this finding due to the small number of patients in the subpopulation.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».