The OMERACT Core Set of Outcome Measures for Use in Clinical Trials of ANCA-associated Vasculitis
Bibliographic record
Abstract
There has been a marked increase in the past 15 years in the number and quality of clinical trials in the idiopathic inflammatory vasculitides, especially the small-vessel vasculitides known as antineutrophil cytoplasmic autoantibody (ANCA)-associated vasculitis [AAV; granulomatosis, with polyangiitis (Wegener's)]. These trials have been conducted by multicenter, international groups in Europe and the United States with financial support provided by government agencies and biopharmaceutical companies. This increased clinical trial activity in vasculitis has been accompanied by the development and validation of new outcome measures--a challenging process for these complex, multiorgan system diseases. The international OMERACT Vasculitis Working Group has developed and implemented an iterative research agenda that has utilized accumulated experience and datasets from several multicenter clinical trials and large cohort studies. This work has led to the development, evaluation, validation, and endorsement, through the OMERACT consensus and validation processes, of a "core set" of outcome measurements for use in clinical trials of AAV. The core set includes domains of disease activity, damage assessment, patient-reported outcomes, and mortality; there is at least one validated outcome measurement instrument available for each domain. This report reviews the domains of illness in AAV included in the OMERACT core set, describes the instruments validated to measure these domains, and presents the approved core set.
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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 | 0.135 | 0.215 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".