A birch sublingual allergy immunotherapy tablet reduces rhinoconjunctivitis symptoms when exposed to birch and oak and induces IgG<sub>4</sub> to allergens from all trees in the birch homologous group
Bibliographic record
Abstract
BACKGROUND: This randomized, double-blind trial was conducted to determine the optimal dose for clinical efficacy of the SQ tree SLIT-tablet. An environmental exposure chamber (EEC) was used to reduce variability of allergen exposure and allow investigation of symptom reduction towards different species from the birch homologous group in separate EEC sessions. METHODS: Eligible subjects (N = 219) were randomized to receive treatment with placebo or the SQ tree SLIT-tablet (2, 7, or 12 DU) for 24 weeks. EEC pollen challenges were conducted outside the birch pollen season and included four birch and two oak EEC sessions. The primary efficacy endpoint was the average allergic rhinoconjunctivitis (ARC) total symptom score (TSS) after 24 weeks of treatment. RESULTS: There was a statistically significantly lower TSS during the 24-week birch EEC session for 7 DU and 12 DU compared to placebo with relative differences of 24% (P = 0.03) and 25% (P = 0.02). For the 24-week oak EEC session, there was a statistically significant difference for 12 DU (24%, P = 0.03). IgE and IgG4 measurements supported these findings and demonstrated cross-reactivity to all other species within the birch homologous group. Treatment was well-tolerated with the most frequently reported adverse reactions being the local reactions in the oral cavity of mild-to-moderate severity. CONCLUSION: This trial demonstrates that the SQ tree SLIT-tablet reduce ARC symptoms triggered by birch or oak pollen. The optimal dose for further development was 12 DU. Clinical and immunological findings suggest that the tablet may be used to treat allergies to all species within the birch homologous group.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".