OMERACT Endorsement of Patient-reported Outcome Instruments in Antineutrophil Cytoplasmic Antibody–associated Vasculitis
Bibliographic record
Abstract
OBJECTIVE: The antineutrophil cytoplasmic antibody-associated vasculitides (AAV) are multiorgan diseases. Patients with AAV report impairment in their health-related quality of life (HRQOL) and have different priorities regarding disease assessment compared with physicians. The Outcome Measures in Rheumatology (OMERACT) Vasculitis Working Group previously received endorsement for a core set of domains in AAV. Two approaches to measure patient-reported outcomes (PRO) were presented at OMERACT 2016. METHODS: A novel 5-step tool was used to facilitate assessment of the instruments by delegates: the OMERACT Filter 2.0 Instrument Selection Algorithm, with a red-amber-green checklist of questions, including (1) good match with domain (face and content validity), (2) feasibility, (3) do numeric scores make sense (construct validity)?, (4) overall ratings of discrimination, and (5) can individual thresholds of meaning be defined? Delegates gave an overall endorsement. Three generic Patient-Reported Outcomes Measurement Information System (PROMIS) instruments (fatigue, physical functioning, and pain interference) and a disease-specific PRO, the AAV-PRO (6 domains related to symptoms and HRQOL), were presented. RESULTS: OMERACT delegates endorsed the use of the PROMIS instruments for fatigue, physical functioning, and pain interference (87.6% overall endorsement) and the disease-specific AAV-PRO instrument (89.4% overall endorsement). CONCLUSION: The OMERACT Vasculitis Working Group gained endorsement by OMERACT for use of the PROMIS and the AAV-PRO in clinical trials of vasculitis. These instruments are complementary to each other. The PROMIS and the AAV-PRO need further work to assess their utility in longitudinal settings, including their ability to discriminate between treatments of varying efficacy in the setting of a randomized controlled trial.
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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 | 0.039 | 0.100 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".