Comparative Efficacy of Targeted Systemic Therapies for Moderate to Severe Atopic Dermatitis without Topical Corticosteroids: Systematic Review and Network Meta-analysis
Bibliographic record
Abstract
INTRODUCTION: The comparative efficacy of targeted systemic therapies for moderate to severe atopic dermatitis (AD) has not been systematically assessed using recent phase 3 data. This network meta-analysis assesses 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: The systematic literature review searched through 17 May 2021 for phase 3/4 trials with upadacitinib, interleukin-4 (IL-4), interleukin-13 (IL-13), or JAK inhibitors compared with placebo or active intervention for adults and adolescents with moderate to severe AD with inadequate response to TCS/TCI or for whom TCS/TCI was medically inadvisable, without restrictions on year or region. Researchers assessed data using PRISMA guidelines. The proportion of patients achieving trial co-primary endpoints [Investigator Global Assessment (IGA) score of 0 or 1 (clear or almost clear) and reduction of ≥ 2 points from baseline; proportion of patients achieving Eczema Area and Severity Index (EASI) improvement ≥ 75% from baseline (EASI-75)]; EASI improvement ≥ 90% from baseline (EASI-90); and ≥ 4-point improvement on Pruritus Numerical Rating Scale from baseline (ΔNRS ≥ 4) were evaluated using Bayesian network meta-analysis. RESULTS: Of 3415 initially identified records, network meta-analysis (NMA) ultimately included 6 records representing 9 unique studies. Two upadacitinib trials were also included. Eleven clinical trials including 6254 patients were analyzed. Upadacitinib 30 mg daily was the most efficacious therapy across all endpoints at the primary endpoint (week 12 or 16) and at earlier timepoints, followed by upadacitinib 15 mg daily and abrocitinib 200 mg daily. DISCUSSION: Many factors need to be considered for treatment selection for AD. These findings can help healthcare providers when personalizing a patient's treatment. CONCLUSION: Upadacitinib 30 mg daily, upadacitinib 15 mg daily, and abrocitinib 200 mg daily may be the most efficacious targeted systemic therapies over 12-16 weeks of therapy in AD.
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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 | 0.028 | 0.058 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.038 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".