Long‐term efficacy and safety of etanercept in children with polyarticular‐course juvenile rheumatoid arthritis: Interim results from an ongoing multicenter, open‐label, extended‐treatment trial
Bibliographic record
Abstract
OBJECTIVE: To evaluate the long-term efficacy and safety of etanercept in children with juvenile rheumatoid arthritis (JRA) participating in an ongoing multicenter, open-label, extended-treatment trial. All patients had been participants in an initial randomized efficacy and safety trial of etanercept. METHODS: Etanercept was administered at a dosage of 0.4 mg/kg (maximum 25 mg) subcutaneously twice each week. Safety and efficacy evaluations were performed every 3-4 months. The JRA 30% definition of improvement (DOI) was defined as improvement of > or =30% in at least 3 of 6 response variables used to assess disease activity, with no more than 1 variable worsening by more than 30%. RESULTS: At the time of analysis, 48 of the 58 patients (83%) were still enrolled in the study; 43 of them (74%) had completed 2 years of treatment. Of these 43 patients, 81% met the JRA 30% DOI, 79% met the JRA 50% DOI, and 67% met the JRA 70% DOI. Ten children started low-dose methotrexate after year 1. Of the 32 children taking prednisone, the dosage was decreased to <5 mg/day in 26 (81%). Two children had serious infections (varicella with aseptic meningitis in one and complicated sepsis in the other). In general, adverse events were of the types seen in a general pediatric patient population. CONCLUSION: Children with severe, longstanding, methotrexate-resistant polyarticular JRA demonstrated sustained clinical improvement with >2 years of continuous etanercept treatment. Etanercept was generally well-tolerated. There were no increases in the rates of adverse events over time. However, children taking etanercept should be monitored closely for infections.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".