Tumor Necrosis Factor-blocking Agents for Children with Enthesitis-related Arthritis — Data from the Dutch Arthritis and Biologicals in Children Register, 1999–2010
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effectiveness and safety of biological agents in children with enthesitis-related arthritis (ERA). METHODS: All patients with ERA in whom a biological agent was initiated between 1999 and 2010 were selected from the Dutch Arthritis and Biologicals in Children (ABC) register. In this ongoing multicenter observational register, data on the course of the disease and medication use are retrieved prospectively at the start of the biological agent, after 3 months, and yearly thereafter. Inactive disease was assessed in accordance with the Wallace criteria. RESULTS: Twenty-two patients with ERA started taking 1 or more biological agents: 20 took etanercept, 2 took adalimumab (1 switched from etanercept to adalimumab), and 2 took infliximab (1 switched from etanercept to infliximab). Characteristics: 77% were male, 77% had enthesitis, 68% were HLA-B27-positive. The median age of onset was 10.4 (IQR 9.4-12.0) years; median followup from the start of the biological agent was 1.2 (IQR 0.5-2.4) years. Intention-to-treat analysis shows that inactive disease was achieved in 7 of 22 patients (32%) after 3 months, 5 of 13 patients (38%) after 15 months, and 5 of 8 patients (63%) after 27 months of treatment. Two patients discontinued etanercept because of ineffectiveness, and switched to adalimumab (inactive disease achieved) or infliximab (decline in joints with arthritis after 3 months of treatment). One patient discontinued etanercept because of remission, but had flare and restarted treatment, with good clinical response. No serious adverse events occurred. CONCLUSION: Tumor necrosis factor (TNF)-blocking agents seem effective and safe for patients with ERA that was previously unresponsive to 1 or more DMARD. However, a sustained disease-free state could not be achieved, and none discontinued TNF-blocking agents successfully.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".