330. TREATMENT RESPONSE CRITERIA FOR ANCA-ASSOCIATED VASCULITIS: RESULTS OF A SCOPING REVIEW
Bibliographic record
Abstract
Background: A review of outcome measures to assess response to treatment in ANCA-associated vasculitis (AAV) will help advance methodology for clinical trials in this disease. Methods: As part of an ongoing international project to develop response criteria, we performed a scoping review to assess the tools used as outcome measures in randomized clinical trials (RCTs) of AAV. Medline, Embase, Cochrane Central, and ClinicalTrials.gov were searched from inception until November 2018 to identify RCTs enrolling patients with granulomatosis with polyangiitis and/or microscopic polyangiitis. Results: Among the 24 RCTs included in the review (Figure 1), various versions of the Birmingham Vasculitis Activity Score (BVAS) were the most widely used instruments for disease assessment. BVAS was almost always reduced to a dichotomous variable (0 or > 0) providing distinction between remission and active disease. Reduction in BVAS and/or achievement of BVAS=0 represented a main study outcome (primary or secondary endpoint) in 20/24 (83%) RCTs; 6 of these trials used the BVAS/WG. Damage, mainly assessed by the Vasculitis Damage Index (VDI), was an outcome for 14/24 (58%) RCTs. Physician global assessment and patient-reported outcomes (PROs) [measures of health-related quality of life (HRQoL) and/or patient global assessment] were assessed in 7 (29%) and 14 (58%) RCTs, respectively. Assessment of renal function or activity was a major outcome or specifically included in definitions of remission/relapse in 23/24 (96%) RCTs. Timing for outcome measure assessment differed substantially, with baseline, 6 months (15/20 RCTs), and 12 months (14/20) after enrollment being the most common time points for reporting BVAS and VDI. Assessment of disease state occurred as early as 1-4 weeks after enrollment, with 6/24 (25%) RCTs assessing disease activity at 6 weeks and 13/24 (54%) at 3 months. Conclusion: Outcome measures used in RCTs of AAV include the repeated use of vasculitis specific tools to assess disease state, but with heterogeneity in the definitions for remission/relapse and timing of assessment. Intermediate states of disease activity are currently poorly defined or evaluated. Furthermore, other important outcomes in AAV, including PROs, damage measures, and global assessments are often not included as primary or confirmatory secondary outcomes in RCTs in AAV. This review highlights the need for more homogeneous outcome assessment in RCTs for AAV and the current lack of a composite measure that integrates various endpoints relevant to physicians and patients. Overview of outcomes assessed in randomized controlled trials of ANCA-associated vasculitis Disclosures: Dr. Robin Christensen reports to be, as an employee at the Parker Institute, Bispebjerg and Frederiksberg Hospital (RC), supported by a core grant from the Oak Foundation (OCAY-13-309)Dr. Alfred Mahr received consultant fees and speaker honoraria from Celgene and Roche Chugai.Dr. Pagnoux reports receiving funds for the following activities: Consulting: ChemoCentryx, Genentech/Roche, Genzyme/Sanofi.Dr. Merkel reports receiving funds for the following activities: Consulting: AbbVie, Biogen, AstraZeneca, Boeringher-Ingelheim, Bristol-Myers Squibb, Celgene, ChemoCentryx, Genentech/Roche, Genzyme/Sanofi, GlaxoSmithKline, InflaRx, Insmed, Jannsen, Kiniksa; Research Support: AstraZeneca, Boeringher-Ingelheim, Bristol-Myers Squibb, Celgene, ChemoCentryx, Genentech/Roche, GlaxoSmithKline, Kypha, TerumoBCT; Royalties: UpToDateDr. David Jayne has received research grants from Chemocentryx, GSK, Roche/Genentech and Sanofi-Genzyme. He has received consultancy fees from Astra-Zeneca, Boehringer-Ingelheim, Celgene, ChemoCentryx, Chugai, GSK, Infla-RX, Insmed and Takeda.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".