Protocol for a double-blind, randomized controlled trial on the dose-related efficacy of omalizumab in multi-food oral immunotherapy
Bibliographic record
Abstract
Abstract Background Previous proof-of-concept studies have shown that a short course of omalizumab can safely accelerate the oral immunotherapy schedule for multiple allergens simultaneously. Considering the high cost of medication, the dose-related efficacy of omalizumab at decreasing the duration of oral immunotherapy up-dosing phase must be objectively quantified before cost–benefit analyses can be performed. The primary objective of this trial will be to compare the efficacy of 2 omalizumab dosages to placebo at decreasing time-to-maintenance dose during a symptom-driven multi-food OIT protocol. Methods A total of 90 participants aged 6 to 25 with multiple food allergies (3 or more) will be enrolled at four sites in Canada. Participants will be randomized to: (A) Omalizumab 8 mg/kg per month (n = 36); (B) Omalizumab 16 mg/kg per month (n = 36); or (C) Placebo (n = 18). Study drug will be administered at full dosage for 12 weeks, then progressively tapered at 50% dosage (8 mg/kg vs 4 mg/kg vs placebo) for 4 weeks and at 25% dosage (4 mg/kg vs 2 mg/kg vs placebo) for another 4 weeks. After a pre-treatment period of 8 weeks, participants will undergo an initial food escalation (IFE) to an OIT mix containing 3 allergens and start daily home dosing with biweekly increases until a target daily maintenance of 1500 mg protein is achieved. The amount escalated at each visit will vary based on treatment tolerance according to a standardized up-dosing algorithm. Participants will be followed for at least 12 months following the initial food escalation. The primary endpoint will be time from IFE to the target maintenance dose of 1500 mg protein. Time-to-event analytic methods, including the log-rank test, will be used to compare the 3 arms. Discussion This trial uses a novel pragmatic approach to compare OIT with omalizumab to OIT without omalizumab in a blinded manner, which allows to single out the effect of this anti-IgE medication on treatment effectiveness speed without the recourse to predetermined schedules. The innovative patient-centered up-dosing algorithm allows to maximise treatment effectiveness speed without compromising patient safety, regardless of whether the patient is on omalizumab or not. This study will also provide novel prospective data to inform on the optimal and most cost-effective dosage for this indication. Trial registration ClinicalTrials.gov, NCT04045301, Registered 5 August 2019, https://clinicaltrials.gov/ct2/show/NCT04045301
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".