Multicenter Canadian case series of pediatric patients less than 12 years of age with moderate‐to‐severe atopic dermatitis treated with dupilumab
Bibliographic record
Abstract
BACKGROUND: Dupilumab is approved for moderate-severe atopic dermatitis (AD) in patients aged ≥6 months by the US Food and Drug Administration and Health Canada; however, there are little real-world data because providers have limited practical experience with this recently approved therapy. OBJECTIVES: To describe the real-world effectiveness and safety in patients aged <12 years with moderate-severe AD currently receiving or previously having received dupilumab. METHODS: A multicenter retrospective study was conducted at six Canadian sites. Cases were divided into Group 1 ≤2 years old, Group 2 >2 to <6 years old, and Group 3 ≥6 to <12 years old. Medical history and details of dupilumab treatment were collected. The primary outcome was to measure the improvement in eczema area and severity index. Secondary outcomes examined included the children's dermatology life quality index/infant's dermatitis quality of life, peak pruritus numerical rating scale, and delay to dupilumab access for patients who were considered off-label for dupilumab due to their age. RESULTS: Sixty three pediatric patients (37 males) with moderate-to-severe AD were included; the mean age was 6.4 years old (range: 2-11) when dupilumab treatment was started. Overall, 75% (36/48) achieved EASI-75% and 71% (34/48) achieved EASI-90. EASI-75 and EASI-90 were achieved in 90% (17/19) and 73% (12/19) in patients <6 years old, and 76% (22/29) and 59% (17/29) in patients >6 years old, respectively. No serious adverse events were reported. CONCLUSIONS: Dupilumab is safe and effective for patients under the age of 12. However, even for experienced providers, access to the medication was challenging.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".