Safety of Epicutaneous Immunotherapy in Peanut-Allergic Children: REALISE Randomized Clinical Trial Results
Bibliographic record
Abstract
BACKGROUND: Treatment options for peanut allergy are limited. In previous clinical trials, epicutaneous immunotherapy with a patch containing 250-μg peanut protein (Viaskin Peanut 250 μg [VP250]) was well tolerated and statistically superior to placebo in desensitizing peanut-allergic children. OBJECTIVE: To examine the safety of VP250 in children, using a study design approximating potential real-world use. METHODS: REAL LIfe Use and Safety of EPIT (REALISE) is a phase 3 multicenter study consisting of a 6-month, randomized, double-blind, placebo-controlled period followed by open-label active treatment. Children aged 4 to 11 years with physician diagnosis of peanut allergy received daily treatment with placebo (6 months) or VP250 (up to 36 months). Data from the 6-month, randomized, controlled phase of REALISE are reported. RESULTS: Three hundred ninety-three children were randomized 3:1 to receive VP250 (n = 294) or placebo (n = 99) for 6 months; 284 (72.3%) children had a history of peanut anaphylaxis. According to parent diary, all participants receiving VP250 and 83.8% receiving placebo reported at least 1 episode of local skin reaction, with frequency decreasing over time. Only 4 participants (1.4%) receiving VP250 discontinued because of adverse events (AEs). Epinephrine was administered for allergic reactions attributed to VP250 in 7 children (2.4%), of whom 5 remained in the study; none involved severe anaphylaxis. Overall, AE rates were similar among participants with and without a history of peanut anaphylaxis. CONCLUSIONS: In a study designed to mirror real-world use, VP250 was observed to be well tolerated in peanut-allergic children, consistent with previous phase 2b and 3 studies.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".