198 AAAAI Survey on Immunotherapy Practice Patterns Concerning Dosing, Dose-Adjustment after Missed Doses and Duration of Immunotherapy
Bibliographic record
Abstract
BACKGROUND: Several practical issues dealing with the exact application of allergen immunotherapy (AIT) among European and US allergists are not well known. Guidelines on AIT give recommendations and suggestions for only some of them. We present this unique survey with worldwide response. METHODS: The AAAAI immunotherapy committee conducted a web-based practice patterns survey (program: Survey Monkey) among all members in&outside US on dosing, dose-adjustment after missed doses and duration of AIT. RESULTS: 1201 Returned questionnaires (almost 25% response rate). 21% were non-US-Canada members. Maintenance doses in USCan are (mean/median): Dermatophagoides farinae (Df) combined with Dermatophagoides pteronyssinus (Dpt): 2155/1000AU; Df solo 2484/1000AU. Dpt when combined with Df 1937/1000AU; Dpt solo: 2183/1000AU.Cat 3224/2000BAU. Grass 11,410/4000BAU. 57-65% of the dosing falls within the recommended Practice Parameters recommended ranges. Non-USCan allergists expressed maintenance doses in many different units making analysis impossible. Dose-adjustment after missed doses is based on ‘time elapsed since the last applied dose’ by 77% of USCan and 58% of non-USCan allergists and on ‘time since missed scheduled dose’ by the rest. Doses are adjusted when a patient comes in more than 14 d/5 wk after the last administration at build-up/maintenance by both USCan and non-USCan colleagues. The mostly followed dose-adjustment schedules after 1, 2, 3 missed doses are: Build-up: repeat last dose, reduce by one dose, reduce by 2 doses; maintenance: reduce by one dose, reduce by 2 doses, reduce by 3 doses. 26% uses a different approach reducing doses by a certain percentage or volume. AIT is restarted after a gap in build-up of >30 days and of >12 weeks during maintenance in both groups (median). Outside USCan AIT is prescribed for 3 years (Median). However, 75% of USCan allergists prescribes AIT for 5 years. Main reasons why to continue AIT beyond 5 years: ‘symptoms came back after stopping’ or “patient afraid to relapse.” CONCLUSIONS: These results show regional differences on some points (especially AIT duration) and they suggest in which direction to plan further research in 2 areas to establish universal dose-adjustment plans for missed applications and define the usefulness (or lack of) of long-term AIT. Moreover, there is still room for improvement in the way AIT is dosed.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".