Evaluation of Proposed Criteria for Remission and Evidence‐Based Development of Criteria for Complete Response in Patients With Chronic Refractory Gout
Bibliographic record
Abstract
OBJECTIVE: The objective of this study is to assess criteria for gout remission and to use the results to inform criteria for a complete response (CR). METHODS: A post hoc analysis of two clinical trials was undertaken to determine the frequency with which subjects with chronic refractory gout who were treated with pegloticase met remission criteria. Mixed modeling was then employed to identify the components that best correlated with time to maximum benefit. RESULTS: Of the 56 subjects treated with biweekly pegloticase for whom adequate data were collected, 48.2% met the remission criteria. When subjects with persistent lowering of urate levels were examined separately, 27 of 32 (84.4%) met the criteria for remission. In contrast, even when the requirement for lowering of serum urate levels was waived, only 2 of 24 (8.3%) subjects without persistent lowering of urate levels and 0 of 43 subjects receiving placebo met criteria. Mixed modeling indicated that in addition to urate levels, assessment of tophi, swollen joints, and tender joints and patient global assessment best correlated with time to maximum benefit. Using these criteria of CR, 23 of the responders (71.9%) met the criteria. All patients who achieved a CR maintained it for a mean duration of 507.4 days. Finally, 64% of persistent responders to monthly pegloticase also met criteria for CR. CONCLUSION: These results have validated the proposed remission criteria for gout and have helped define criteria for CR in individuals with chronic gout treated with pegloticase. This composite CR index can serve as an evidence-based target to inform the design and end points of future clinical trials.
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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 | 0.306 | 0.362 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.012 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".