Peanut Oral Immunotherapy Using 30 and 300 mg Maintenance Doses
Bibliographic record
Abstract
Background The lowest dose of peanut oral immunotherapy (P-OIT) has not been determined. Objective To evaluate if very low dose OIT (30mg) may safely and effectively increase tolerated doses and induce immunological changes. Methods Peanut-allergic children reactive to /=443 and >/=1043mg PP were compared to Group-Avoid by DBPCFC planned at 1yr. Safety and laboratory parameters (sIgE, sIgG4) were assessed. Results We enrolled 51 children (26 (51%) male, median age 10yrs (IQR 7-13)), with initial cumulative-tolerated dose of 44mg (IQR 14-144). In Group-30mg, 15/17 completed DBPCFC (2/17 withdrawn). In Group-300mg, 12/17 completed DBPCFC (5/17 withdrawn). In Group-Avoid, 12/17 completed DBPCFC (5/17 lost to follow-up). By intention to treat, Group-30mg, 13/17 (p<<0.001 vs. Group-Avoid) tolerated >/=443 and 7/17 (p=0.007 vs. Group-Avoid) tolerated >/=1043mg PP. In the Group-300mg 10/17 (p=<0.001 vs. Group-Avoid) tolerated >/=443 and 8/17 (p=0.003 vs Group-Avoid) tolerated >/=1043mg PP. No Group-Avoid (0/17) tolerated >/=443 or >/=1043mg PP. Laboratory parameters (sIgE, sIgG4) were similar between Group-30mg and Group-300mg and significantly improved from Group-Avoid. Systemic adverse events were fewer in Group-30mg vs Group-300mg. Conclusions A 30mg maintenance dose for P-OIT significantly increases threshold over strict avoidance, clinically similarly to 300mg, and may allow for a simplified and safer OIT regimen and less treatment drop-outs. NCT03532360
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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 | 0.000 |
| 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) | 0.002 | 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".