MRP8/14 serum levels as a predictor of response to starting and stopping anti-TNF treatment in juvenile idiopathic arthritis
Bibliographic record
Abstract
INTRODUCTION: Approximately 30% of juvenile idiopathic arthritis (JIA) patients fail to respond to anti-TNF treatment. When clinical remission is induced, some patients relapse after treatment has been stopped. We tested the predictive value of MRP8/14 serum levels to identify responders to treatment and relapse after discontinuation of therapy. METHODS: Samples from 88 non-systemic JIA patients who started and 26 patients who discontinued TNF-blockers were analyzed. MRP8/14 serum levels were measured by in-house MRP8/14 ELISA and by Bühlmann Calprotectin ELISA at start of anti-TNF treatment, within 6 months after start and at discontinuation of etanercept in clinical remission. Patients were categorized into responders (ACRpedi ≥ 50 and/or inactive disease) and non-responders (ACRpedi < 50) within six months after start, response was evaluated by change in JADAS-10. Disease activity was assessed within six months after discontinuation. RESULTS: Baseline MRP8/14 levels were higher in responders (median MRP8/14 of 1466 ng/ml (IQR 1045-3170)) compared to non-responders (median MRP8/14 of 812 (IQR 570-1178), p < 0.001). Levels decreased after start of treatment only in responders (p < 0.001). Change in JADAS-10 was correlated with baseline MRP8/14 levels (Spearman's rho 0.361, p = 0.001). Patients who flared within 6 months after treatment discontinuation had higher MRP8/14 levels (p = 0.031, median 1025 ng/ml (IQR 588-1288)) compared to patients with stable remission (505 ng/ml (IQR 346-778)). Results were confirmed by Bühlmann ELISA with high reproducibility but different overall levels. CONCLUSION: High levels of baseline MRP8/14 are associated with good response to anti-TNF treatment, whereas elevated MRP8/14 levels at discontinuation of etanercept are associated with higher chance to flare.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".