Serum ARGS-aggrecan in a phase 2 clinical trial targeting osteoarthritis
Bibliographic record
Abstract
Objective To monitor serum concentrations of the aggrecan alanine-arginine-glycine-serine (ARGS) neoepitope in a clinical trial of a disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS)-5 inhibition as disease-modifying therapy of knee osteoarthritis, and to investigate relationships between reduction in ARGS and change in cartilage thickness, knee-related pain and function. Design ROCCELLA trial participants received once-daily oral S201086 75, 150 or 300 mg, or placebo, for 52 weeks. Serum was collected at baseline, 4, 12, 28 and 52 weeks, and 2 weeks post-treatment with ARGS measured by an in-house immunoassay. Change from baseline to week 52 in central medial femorotibial compartment cartilage thickness was measured by magnetic resonance imaging, function and pain by Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) subscores. Associations between cumulative change in ARGS and change in cartilage thickness or WOMAC subscores were evaluated by linear regression. Results S201086 reduced serum levels of ARGS in a dose-dependent manner throughout the treatment period. Maximal reduction was at 4 weeks with a 58.5% [95% CI 60.8%, 56.2%] reduction of ARGS compared to baseline for 300 mg S201086. Two weeks post-treatment, ARGS concentrations rebounded with a dose-dependent overshoot compared to baseline levels. Cumulative change of ARGS concentration from baseline to week 52 had no effect on change in cartilage thickness (slope −0.8×10 −6 [−2.9×10 −6 , 1.3×10 −6 ]) or change in WOMAC pain and function (slopes −30×10 −6 [−64×10 −6 , 5.2×10 −6 ] and −97×10 −6 [−214×10 −6 , 20×10 −6 ], respectively) at week 52. Conclusion Systemic inhibition of ADAMTS-5 resulted in markedly reduced serum ARGS, but change in serum ARGS concentrations showed no association with the progression of cartilage thinning, or patient reported pain and function.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".