Use of Extended Dosing Intervals of Dupilumab in Treatment of Atopic Dermatitis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Dupilumab is a biological agent used in atopic dermatitis (AD) with 2-weekly dosing. Extending dosing intervals in patients with a good response to dupilumab can lead to increased convenience, cost savings, and possibly fewer adverse events (AEs). There has been no systematic review or meta-analysis so far to assess the feasibility of extending dupilumab dosing intervals in well-controlled patients. This study aims to determine the efficacy and ocular AE occurrence in extended dosing intervals of dupilumab in comparison to the standard 2-weekly dosing regimen. We performed a systematic review and meta-analysis of articles using MEDLINE, EMBASE, Cochrane, and ClinicalTrials.gov which reported either efficacy (by measure of Eczema Area and Severity Index) or ocular AE occurrence in extended dosing interval regimens (3-weekly or 4-weekly dosing) in comparison to standard dosing regimens. Random effects analysis was used to obtain the pooled mean difference for efficacy and relative risk for ocular AEs. Thirteen reports from 11 studies were analysed. The pooled mean difference in the extended dosing interval regimen is 0.04 lower (95% confidence interval [CI]: -0.77 to 0.69) than the standard dosing regimen. The relative risk of ocular AEs in the extended dosing interval regimen in comparison to the standard dosing regimen is 0.58 (95% CI: 0.28-1.21). We conclude that extended dosing interval dupilumab regimens are at least as effective as standard dosing regimens in the treatment of AD in well-controlled patients. It cannot be concluded that ocular AEs are reduced with dose tapering. More work can be done to improve the current body of evidence for extended dosing intervals of dupilumab 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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.040 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".