Current Status of Outcome Measure Development in Vasculitis
Bibliographic record
Abstract
The conduct of randomized controlled trials for vasculitis, especially for the antineutrophil cytoplasmic antibody-associated vasculitides [AAV, granulomatosis with polyangiitis (Wegener's) and microscopic polyangiitis], has been greatly advanced by the development, use, and acceptance of validated outcome measures. Trials have subsequently provided the opportunity to validate and refine reliable, valid outcome measures for these multisystemic and relapsing rare diseases. The Outcome Measures in Rheumatology (OMERACT) Vasculitis Working Group was formed in 2004 to foster development of validated and widely accepted outcomes in vasculitis using data-driven analyses, a dedication to building consensus, and adherence to, and guidance by, the principles of the OMERACT approach. This work led to the endorsement by OMERACT of the core set of domains and associated outcome measures for AAV. Next steps for the study of existing outcome tools in AAV include better definition of response criteria through development of more data-driven weighting of the elements of activity and damage assessment. The Working Group is now also embarking on a series of linked projects to develop validated patient-reported outcomes for use in clinical research in vasculitis. Additionally, the Working Group is studying how current methods of disease assessment and plans for new outcomes can be informed by the conceptual framework of the International Classification of Function of the World Health Organization. The success of the Group's work in AAV has also led to a formal process for developing outcomes for the large vessel vasculitides (Takayasu arteritis and giant cell arteritis) and Behçet disease.
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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 | 0.445 | 0.525 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.009 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.015 | 0.008 |
| Research integrity | 0.008 | 0.016 |
| 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; 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".