Comparative Efficacy of Targeted Systemic Therapies for Moderate-to-Severe Atopic Dermatitis without Topical Corticosteroids: An Updated Network Meta-analysis
Bibliographic record
Abstract
INTRODUCTION: The treatment landscape for moderate-to-severe atopic dermatitis (AD) continues to expand. This network meta-analysis (NMA) updates a previously conducted NMA to include data from the most recent phase 3 trials to assess the comparative efficacy of targeted systemic therapies without the addition of topical corticosteroids (TCS) and/or topical calcineurin inhibitors (TCI) in adults with moderate-to-severe AD. METHODS: Data from recent phase 3 monotherapy trials of lebrikizumab, ADvocate1 (NCT04146363) and ADvocate2 (NCT04178967), were included in the analyses, along with other eligible phase 3/4 randomized placebo-controlled trials for abrocitinib, baricitinib, dupilumab, tralokinumab, and upadacitinib identified through a systemic literature review in Silverberg et al. (Dermatol Ther (Heidelb) 12(5):1181-1196, 2022). The proportion of patients achieving Eczema Area and Severity Index (EASI) improvement ≥ 90% from baseline (EASI-90), EASI improvement ≥ 75% from baseline (EASI-75), ≥ 4-point improvement on Pruritus Numerical Rating Scale from baseline (ΔNRS ≥ 4), and Investigator Global Assessment (IGA) score of 0 or 1 (clear or almost clear) and reduction of ≥ 2 points from baseline (IGA 0/1) were evaluated using a Bayesian network meta-analysis. RESULTS: The updated NMA analyzed 13 unique placebo-controlled trials involving 7105 patients in 32 arms across 6 targeted therapies. Upadacitinib 30 mg was the most efficacious therapy across all endpoints at the primary timepoint (week 12 or 16) and at earlier timepoints, generally followed by abrocitinib 200 mg, upadacitinib 15 mg, dupilumab 300 mg, and lebrikizumab 250 mg or abrocitinib 100 mg. Baricitinib 2 mg and tralokinumab were generally ranked lower across outcomes. CONCLUSIONS: Many factors need to be considered for treatment selection for AD, especially as new treatments continue to emerge. After incorporating recent placebo-controlled phase 3 data of lebrikizumab, upadacitinib 30 mg, upadacitinib 15 mg, and abrocitinib 200 mg remain the most efficacious targeted systemic therapies over 12-16 weeks of therapy in AD. These updated findings can help healthcare providers when creating a patient's personalized treatment plan.
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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 | 0.027 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.046 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".