Evaluation of Serum Biomarkers Associated with Radiographic Progression in Methotrexate-naive Rheumatoid Arthritis Patients Treated with Methotrexate or Golimumab
Bibliographic record
Abstract
OBJECTIVE: To evaluate associations between biomarkers and radiographic progression in methotrexate (MTX)-naive patients with rheumatoid arthritis (RA) treated with MTX or golimumab, a tumor necrosis factor inhibitor (with or without MTX). METHODS: Serum samples from 152 MTX-naive adults with active RA who received placebo + MTX (n = 37) or golimumab (combined 50 mg + MTX or 100 mg ± MTX; n = 115) were analyzed for selected markers of inflammation and bone/cartilage turnover. One hundred patients were randomly selected for additional protein profiling using multianalyte profiles (HumanMap v1.6, Rules Based Medicine). Radiographs at baseline, Week 28, and Week 52 were scored using van der Heijde-Sharp (vdH-S) methodology. Correlations were assessed between biomarker levels (baseline and change at Week 4) and joint space narrowing, erosion, and total vdH-S scores (changes at Weeks 28 and 52). Statistical significance was defined as a correlation coefficient with an absolute value ≥ 0.3 and p < 0.05. RESULTS: Biomarker correlations with changes in vdH-S scores at Week 28 and/or 52 were observed predominantly in the placebo + MTX group and rarely in the combined golimumab treatment group. Changes in epidermal growth factor (EGF) and CD40 ligand (CD40L) at Week 4 were positively correlated with changes in total vdH-S scores at Weeks 28 and 52 in the placebo + MTX group. CONCLUSION: These preliminary findings indicate that EGF and CD40L may have utility in monitoring MTX-treated patients with RA who are more likely to have radiographic progression as measured by increases in vdH-S scores.
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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) | 0.001 | 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".