Antineutrophil Cytoplasmic Antibody-associated Vasculitis Management 2020: Where Are We Now?
Bibliographic record
Abstract
The management of antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) has come a long way from the first postmortem descriptions of the diseases in the 1930s and 1950s1. Pivotal phases have been the introduction of glucocorticoids (GC) and cyclophosphamide (CYC), the association with ANCA in the 1980s, and consensus classification and nomenclature systems from 1990 onwards2. These advances laid the foundations for larger-scale clinical investigations that have informed both the development of recommendations statements in the 2000s and the evaluation of newer therapies3. In parallel with these activities have been improvements in physician training and healthcare delivery, which have shortened diagnostic delay, and improved mortality and endstage renal disease risks4. Statements to guide AAV management have now been produced at national and international levels, and an update of the Canadian Vasculitis Society (CanVasc) 2015 statement is published in this edition of The Journal of Rheumatology 5. This is an extensive piece of work with 39 recommendation statements, 15 of them new for this update covering diagnosis, drug therapies, eosinophilic granulomatosis with polyangiitis (EGPA), children, monitoring, and prophylaxis. So what is new? Solid-phase assays for proteinase 3–ANCA and myeloperoxidase (MPO)-ANCA are the preferred initial serologic tests reflecting superior performance when compared to indirect immunofluorescence (cytoplasmic or perinuclear ANCA). There is more discussion on GC dosing as better data have emerged and momentum builds to limit doses. The place of rituximab (RTX) has been extended to relapse prevention; plasma exchange use is more restricted; and mycophenolate mofetil (MMF) is an alternative induction option. The use of biomarkers to guide drug dosing during remission maintenance, … Address correspondence to Dr. D. Jayne, Box 157, Department of Medicine, Addenbrookes Hospital, Cambridge CB22QQ, UK. Email: Dj106{at}cam.ac.uk.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.042 | 0.019 |
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".