Efficacy of lebrikizumab in adolescent patients with moderate-to-severe atopic dermatitis: 16-week results from three randomized phase 3 clinical trials
Bibliographic record
Abstract
Background Lebrikizumab, a high-affinity monoclonal antibody targeting IL-13, previously demonstrated clinical efficacy in three randomized, double-blind, placebo-controlled Phase 3 trials that included adults and adolescents with moderate-to-severe atopic dermatitis (AD): ADvocate1, ADvocate2, and ADhere.Aim This subset analysis evaluated 16-week physician- and patient-reported outcomes of lebrikizumab in the adolescent patients enrolled in these three trials.Methods Eligible adolescents (≥12 to <18 years weighing ≥40kg) were randomized 2:1 to subcutaneous lebrikizumab (500 mg loading doses at baseline and Week 2 followed by 250 mg every 2 weeks) or placebo as monotherapy in ADvocate1&2, and in combination with topical corticosteroids (TCS) in the ADhere study. Week 16 analyses included clinical efficacy outcomes (IGA (0,1) with ≥2-point improvement, EASI 75, EASI 90), patient-reported Pruritus NRS ≥4-point improvement and Sleep-Loss Scale ≥2-point improvement.Results Pooled ADvocate1&2 16-week results in lebrikizumab (N = 67) vs placebo (N = 35) were: IGA (0,1) 46.6% vs 14.3% (p < 0.01), EASI 75 62.0% vs 17.3% (p < 0.001), EASI 90 40.7% vs 11.5% (p < 0.01), Pruritus NRS 48.9% vs 13.1% (p < 0.01), and Sleep-Loss Scale 26.9% vs 6.9% (p = 0.137). Corresponding results for ADhere, (lebrikizumab + TCS, N = 32; placebo + TCS, N = 14), were consistent.Conclusions Lebrikizumab treatment demonstrated efficacy in improving the signs and symptoms of AD in adolescent patients, consistent with the ADvocate and ADhere overall population results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".