315. Development of an ANCA-Associated Vasculitis Patient-Reported Outcome Measure: Identification of Salient Themes and Candidate Questionnaire Item Development
Bibliographic record
Abstract
Background: Patients with ANCA-associated vasculitides (AAVs), granulomatosis with polyangiitis, eosinophilic granulomatosis with polyangiitis (Churg–Strauss) and microscopic polyangiitis often suffer from persistent disease activity, disease-associated damage, or treatment side effects, all of which may impact quality of life. There is currently no disease-specific patient-reported outcome (PRO) for AAV. The development of a new PRO involves questionnaire item development; item reduction and scale generation; and testing scale properties such as reliability, validity and responsiveness. It is essential that a PRO is developed in compliance with U.S. Food and Drug Administration recommendations in order to legitimize its use in clinical trials and in supporting labelling claims for medications. Following these principles, a multi-national collaboration of researchers and patient-partners has been conducting the first stage of questionnaire item development. A collaborative approach involving patients from the UK, USA and Canada was feasible and desirable due to the relative rarity of the disease and the ability to create a tool with content validity (and cultural/linguistic equivalence) appropriate for use in all three countries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".