Discrepancy Between Clinical and Radiological Responses to Tocilizumab Treatment in Patients with Systemic-onset Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
OBJECTIVE: Tocilizumab (TCZ), an antiinterleukin-6 receptor monoclonal antibody, is clinically beneficial in patients with systemic-onset juvenile idiopathic arthritis (sJIA). We investigated the clinical and radiological outcomes of TCZ therapy in patients with sJIA. METHODS: We retrospectively evaluated 2 clinical trials (NCT00144599 and NCT00144612) involving 40 patients with sJIA who received intravenous TCZ (8 mg/kg) every 2 weeks. Clinical data and radiographs of the hands and large joints were assessed before and during TCZ treatment. The Poznanski score, modified Larsen scores of the hands and large joints, and Childhood Arthritis Radiographic Score of the Hip (CARSH) were recorded. RESULTS: After a mean duration of 4.5 years of TCZ treatment, clinical data had improved significantly, the mean Poznanski score improved from -1.5 to -1.1, the mean Larsen score of the hands deteriorated from 7.0 to 10.0, the mean Larsen score for the large joints deteriorated from 5.9 to 6.8, and the CARSH worsened from 3.9 to 6.2. The Larsen score for the large joints improved in 11 cases (28%), remained unchanged in 8 cases (20%), and worsened in 21 cases (52%). Matrix metalloproteinase 3 (MMP-3) levels remained significantly higher (278 mg/dl) in patients with worsened Larsen scores than in patients with improved or unchanged scores (65 mg/dl). Logistic regression analysis showed that older age at disease onset was a significant risk factor for radiographic progression. CONCLUSION: The modified Larsen score of the large joints deteriorated in half the patients who had high MMP-3 levels during TCZ treatment and who were significantly older at disease onset.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".