OP-072 Dupilumab versus immunosuppressants for atopic dermatitis in children <12 years
Bibliographic record
Abstract
Aim In phase 3 studies, dupilumab significantly improved disease severity in children with moderate-to-severe atopic dermatitis (AD). This study investigates the impact of dupilumab on children in real-world treatment settings in comparison to other systemic treatments.Material and Method PEDISTAD ( NCT03687359) is an ongoing study in patients aged < 12 years with moderate-to-severe AD. Effects of dupilumab, methotrexate (MTX) and cyclosporine (CsA) on Eczema Area and Severity Index (EASI) total score and% affected body surface area (BSA) were assessed from first treatment episode (FTE) to last observation (LO).Results 129 patients received dupilumab (median treatment observation period: 17.0 months; 3-year discontinuation rate: 10.1%), 70 CsA (12.2 months; 40.0%), and 77 MTX (21.3 months; 22.1%). The proportion of patients with clear/mild AD (EASI < 7 [range 0–72]) increased for dupilumab (FTE: 27.0%; LO: 78.8%), CsA (18.8%; 54.6%), and MTX (13.3%; 58.7%). Mean (± SE) EASI scores significantly improved with dupilumab (FTE: 18.4 ± 1.3; LO: 5.0 ± 0.7; P < 0.0001), CsA (16.9 ± 1.4; 10.0 ± 1.4; P < 0.0001), and MTX (16.6 ±1.3; 8.4 ± 1.1; P < 0.0001). Mean (± SE) BSA affected also significantly decreased for dupilumab (37.5 ± 2.2; 15.6 ± 2.3; P < 0.0001), CsA (36.9 ± 2.8; 24.0 ± 2.8; P = 0.0001), and MTX (34.3 ± 2.3; 20.3 ±2.5; P < 0.0001). The exposure-adjusted AE/serious AE rate per 100 patient-years was 29.2/1.5 for dupilumab; 43.5/0.9 for CsA; and 30.7/0.6 for MTX, and the rate of patients with any AE requiring corrective treatment or therapy was 1.0, 4.4 and 4.2 per 100 patient-years respectively.Conclusions Dupilumab treatment led to numerically greater improvement in disease severity and was also associated with lower treatment discontinuation and fewer AEs compared with MTX and CsA.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 | 0.001 |
| 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".