Efficacy of Dupilumab in Children 6 Months to 11 Years Old with Atopic Dermatitis: A Retrospective Real-World Study in China
Bibliographic record
Abstract
Abstract: Background: Atopic dermatitis (AD) is a common skin disease that affects patients' quality of life, especially in the pediatric population. Dupilumab has shown good efficacy and safety in the treatment of AD in adolescents and adults, but the real data on younger children using dupilumab are scarce. Objectives: We investigated the doses, efficacy, and safety of dupilumab in children with moderate-to-severe AD aged ≥6 months to 11 years. Methods: This single-center retrospective cohort analysis included dupilumab-treated patients with severe AD under 12 years of age. Primary endpoints included the proportion of Validated Investigator Global Assessment (vIGA) 0/1 achieved and the percentage change from baseline in eczema area and severity index (EASI) and SCORing Atopic Dermatitis (SCORAD) at week 24 (W24). Secondary endpoints were mean change in pruritus numerical rating score (P-NRS) and body surface area (BSA) after W24 of treatment, description of adverse events, and Children's Dermatology Life Quality Index (CDLQI) improvement from baseline in endpoints. Results: Fifty-seven patients were included (mean age 7.2 ± 3.0 years). The primary endpoint (vIGA = 0/1) was achieved by 51 of 57 (89.5%) patients at W24. Significant improvements in EASI, SCORAD, P-NRS, and CDLQI scores were observed from baseline to W24 with dupilumab treatment and remained until W40. In different age groups, the endpoint vIGA achieved 0/1: 95.2% (20/21) of younger children and 88.9% (32/36) of older children. No serious adverse drug reactions were reported. Conclusions: This study aimed to describe the safety and efficacy of dupilumab in pediatric patients and examined differences of efficacy with various doses. The outcomes are comparable with those of existing clinical trials. Phase III Clinical Trial: NCT03346434.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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; a candidate call from one teacher head, 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".