Serum Osteopontin as a Predictive Marker of Responsiveness to Methotrexate in Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
OBJECTIVE: To evaluate if serum concentrations of osteopontin (OPN) at baseline in patients with juvenile idiopathic arthritis (JIA) represent a potential predictor of responsiveness to methotrexate (MTX). METHODS: At diagnosis, 60 children with active JIA received MTX in addition to nonsteroidal antiinflammatory drugs. After 12 months of MTX treatment, 30 patients were defined as responders; the 30 nonresponders received anti-tumor necrosis factor-alpha therapy (etanercept) in addition to MTX; this group was then enrolled for an additional 12-month study period. No patient had received steroids within 6 weeks before entering the study. Fifty healthy children matched for sex and age acted as controls. OPN serum levels were measured at baseline, before MTX, and then at 6 and 12 months. In the nonresponder patients, OPN was evaluated again after 6 and 12 months of etanercept treatment. RESULTS: At baseline, OPN values were significantly higher (p = 0.0003) in JIA patients than in controls, with no significant differences among the different JIA subtypes. At baseline, OPN levels were lower in responders than in nonresponder patients (14.16 +/- 10.1 microg/ml vs 33.2 +/- 18.1 microg/ml, respectively). After 12 months of MTX treatment, OPN levels were significantly reduced in comparison to baseline in both responder and nonresponder groups (p = 0.0017, p = 0.0048, respectively). In nonresponders, etanercept significantly reduced OPN levels at 6 and 12-month followup in comparison to baseline (p = 0.002, p = 0.008, respectively). No significant differences were found among OPN levels and disease activity. CONCLUSION: Serum levels of OPN at baseline represent a possible marker to predict the responsiveness to MTX in patients with JIA.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".