The Allergic Rhinitis – Clinical Investigator Collaborative (AR-CIC): nasal allergen challenge protocol optimization for studying AR pathophysiology and evaluating novel therapies
Bibliographic record
Abstract
BACKGROUND: The Nasal Allergen Challenge (NAC) model allows the study of Allergic Rhinitis (AR) pathophysiology and the proof of concept of novel therapies. The Allergic Rhinitis - Clinical Investigator Collaborative (AR-CIC) aims to optimize the protocol, ensuring reliability and repeatability of symptoms to better evaluate the therapies under investigation. METHODS: 20 AR participants were challenged, with 4-fold increments of their respective allergens every 15 minutes, to determine the qualifying allergen concentration (QAC) at which the Total Nasal Symptom Score (TNSS) of ≥10/12 OR a Peak Nasal Inspiratory Flow (PNIF) reduction of ≥50% from baseline was achieved. At the NAC visit, the QAC was used in a single challenge and TNSS and PNIF were recorded at baseline, 15 minutes, 30 minutes, 1 hour, and hourly up to 12 hours. 10 additional ragweed allergic participants were qualified at TNSS of ≥8/12 AND ≥50% PNIF reduction; the Cumulative Allergen Challenge (CAC) of all incremental doses was used during the NAC visit. 4 non-allergic participants were challenged with the highest allergen concentration. RESULTS: In the QAC study, a group qualified by only meeting PNIF criteria achieved lower TNSS than those achieving either TNSS criteria or PNIIF+TNSS (p<0.01). During the NAC visit, participants in both studies reached their peak symptoms at 15minutes followed by a gradual decline, significantly different from non-allergic participants. The "PNIF only" group experienced significantly lower TNSS than the other groups during NAC visit. QAC and CAC participants did not reach the same peak TNSS during NAC that was achieved at screening. QAC participants qualifying based on TNSS or TNSS+PNIF managed to maintain PNIF scores. CONCLUSIONS: Participants experienced reliable symptoms of AR in both studies, using both TNSS and PNIF reduction as part of the qualifying criteria proved better for qualifying participants at screening. Phenotyping based on pattern of symptoms experienced is possible and allows the study of AR pathophysiology and can be applied in evaluation of efficacy of a novel medication. The AR-CIC aims to continue to improve the model and employ it in phase 2 and 3 clinical trials.
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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 | 0.090 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".