Systemic treatments for atopic dermatitis (eczema): Systematic review and network meta-analysis of randomized trials
Bibliographic record
Abstract
BACKGROUND: Atopic dermatitis (AD) is an inflammatory skin condition with multiple systemic treatments and uncertainty regarding their comparative impact on AD outcomes. OBJECTIVE: We sought to systematically synthesize the benefits and harms of AD systemic treatments. METHODS: For the 2023 American Academy of Allergy, Asthma & Immunology and American College of Allergy, Asthma, and Immunology Joint Task Force on Practice Parameters AD guidelines, we searched MEDLINE, EMBASE, CENTRAL, Web of Science, and GREAT databases from inception to November 29, 2022, for randomized trials addressing systemic treatments and phototherapy for AD. Paired reviewers independently screened records, extracted data, and assessed risk of bias. Random-effects network meta-analyses addressed AD severity, itch, sleep, AD-related quality of life, flares, and harms. The Grading of Recommendations Assessment, Development and Evaluation approach informed certainty of evidence ratings. This review is registered in the Open Science Framework (https://osf.io/e5sna). RESULTS: The 149 included trials (28,686 patients with moderate-to-severe AD) evaluated 75 interventions. With high-certainty evidence, high-dose upadacitinib was among the most effective for 5 of 6 patient-important outcomes; high-dose abrocitinib and low-dose upadacitinib were among the most effective for 2 outcomes. These Janus kinase inhibitors were among the most harmful in increasing adverse events. With high-certainty evidence, dupilumab, lebrikizumab, and tralokinumab were of intermediate effectiveness and among the safest, modestly increasing conjunctivitis. Low-dose baricitinib was among the least effective. Efficacy and safety of azathioprine, oral corticosteroids, cyclosporine, methotrexate, mycophenolate, phototherapy, and many novel agents are less certain. CONCLUSIONS: Among individuals with moderate-to-severe AD, high-certainty evidence demonstrates that high-dose upadacitinib is among the most effective in addressing multiple patient-important outcomes, but also is among the most harmful. High-dose abrocitinib and low-dose upadacitinib are effective, but also among the most harmful. Dupilumab, lebrikizumab, and tralokinumab are of intermediate effectiveness and have favorable safety.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.055 | 0.015 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".