Core Outcome Set for <scp>IgE</scp>‐mediated food allergy clinical trials and observational studies of interventions: International Delphi consensus study ‘<scp>COMFA</scp>’
Bibliographic record
Abstract
BACKGROUND: IgE-mediated food allergy (FA) is a global health concern with substantial individual and societal implications. While diverse intervention strategies have been researched, inconsistencies in reported outcomes limit evaluations of FA treatments. To streamline evaluations and promote consistent reporting, the Core Outcome Measures for Food Allergy (COMFA) initiative aimed to establish a Core Outcome Set (COS) for FA clinical trials and observational studies of interventions. METHODS: The project involved a review of published clinical trials, trial protocols and qualitative literature. Outcomes found as a result of review were categorized and classified, informing a two-round online-modified Delphi process followed by hybrid consensus meeting to finalize the COS. RESULTS: The literature review, taxonomy mapping and iterative discussions with diverse COMFA group yielded an initial list of 39 outcomes. The iterative online and in-person meetings reduced the list to 13 outcomes for voting in the formal Delphi process. One more outcome was added based on participant suggestions after the first Delphi round. A total of 778 participants from 52 countries participated, with 442 participating in both Delphi rounds. No outcome met a priori criteria for inclusion, and one was excluded as a result of the Delphi. Thirteen outcomes were brought to the hybrid consensus meeting as a result of Delphi and two outcomes, 'allergic symptoms' and 'quality of life' achieved consensus for inclusion as 'core' outcomes. CONCLUSION: In addition to the mandatory reporting of adverse events for FA clinical trials or observational studies of interventions, allergic symptoms and quality of life should be measured as core outcomes. Future work by COMFA will define how best to measure these core outcomes.
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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 | 0.415 | 0.439 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.016 | 0.008 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".