Factors Associated with Radiographic Progression in Patients with Rheumatoid Arthritis Who Were Treated with Methotrexate
Bibliographic record
Abstract
OBJECTIVE: To identify factors associated with radiographic progression at 52 weeks in patients with rheumatoid arthritis (RA) after 12 weeks of methotrexate (MTX) therapy. METHODS: The study population consisted of patients from the MTX arm of the Trial of Etanercept and Methotrexate with Radiographic Patient Outcomes (TEMPO). Logistic regression analysis was used to identify clinical and laboratory assessments performed at Week 12 of MTX therapy that might be associated with Week 52 radiographic outcome (modified total Sharp score). Classification and regression tree (CART) modeling of the Week 12 assessments was used to determine the subgroups of patients with the best and worst radiographic outcomes. RESULTS: A total of 169 patients were analyzed: 116 patients in the best radiographic outcome group and 53 patients in the worst radiographic outcome group. Logistic regression analysis showed that Week 12 C-reactive protein (CRP) level, erythrocyte sedimentation rate, tender joint count, swollen joint count (SJC), and Health Assessment Questionnaire scores were significantly associated with radiographic progression at Week 52 (p < 0.05 for each assessment). CART modeling showed that patients with Week 12 CRP > 0.67 mg/dl and SJC > 1 and patients with Week 12 CRP ≤ 0.67 mg/dl and SJC > 10 were likely to show the worst radiographic progression at Week 52. The CART model had a sensitivity of 85%, specificity of 60%, and overall classification accuracy of 68%. CONCLUSION: In patients with RA, measures of CRP and SJC after 12 weeks of MTX therapy emerged as the factors most associated with radiographic progression at Week 52.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".