Exploration, Development, and Validation of Patient-reported Outcomes in Antineutrophil Cytoplasmic Antibody–associated Vasculitis Using the OMERACT Process
Bibliographic record
Abstract
OBJECTIVE: Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a group of linked multisystem life- and organ-threatening diseases. The Outcome Measures in Rheumatology (OMERACT) vasculitis working group has been at the forefront of outcome development in the field and has achieved OMERACT endorsement of a core set of outcomes for AAV. Patients with AAV report as important some manifestations of disease not routinely collected through physician-completed outcome tools; and they rate common manifestations differently from investigators. The core set includes the domain of patient-reported outcomes (PRO). However, PRO currently used in clinical trials of AAV do not fully characterize patients' perspectives on their burden of disease. The OMERACT vasculitis working group is addressing the unmet needs for PRO in AAV. METHODS: Current activities of the working group include (1) evaluating the feasibility and construct validity of instruments within the PROMIS (Patient-Reported Outcome Measurement Information System) to record components of the disease experience among patients with AAV; (2) creating a disease-specific PRO measure for AAV; and (3) applying The International Classification of Functioning, Disability and Health to examine the scope of outcome measures used in AAV. RESULTS: The working group has developed a comprehensive research strategy, organized an investigative team, included patient research partners, obtained peer-reviewed funding, and is using a considerable research infrastructure to complete these interrelated projects to develop evidence-based validated outcome instruments that meet the OMERACT filter of truth, discrimination, and feasibility. CONCLUSION: The OMERACT vasculitis working group is on schedule to achieve its goals of developing validated PRO for use in clinical trials of AAV.
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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 | 0.291 | 0.348 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".