Factors Associated with Achievement of Inactive Disease in Children with Juvenile Idiopathic Arthritis Treated with Etanercept
Bibliographic record
Abstract
OBJECTIVE: To evaluate the rate of inactive disease in children with juvenile idiopathic arthritis (JIA) treated with etanercept, and to identify clinical characteristics associated with attainment of inactive disease. METHODS: Clinical charts of patients who were given etanercept between January 2002 and January 2011 were evaluated retrospectively. For each patient, all visits from initiation of etanercept to the last followup evaluation in which the patient was still receiving etanercept were examined to establish whether the patient had reached the state of inactive disease and to identify the first visit in which inactive disease was documented. Clinical characteristics associated with achievement of inactive disease were determined through univariate analyses and Cox regression procedures. RESULTS: A total of 173 patients who received etanercept for a median of 2.2 years (range 0.5-10.5 yrs) were studied. Eighty-seven patients (50.3%) achieved inactive disease after a median of 0.6 years (range 0.1-2.5 yrs) of therapy. At last followup evaluation, 85 patients (49.1%) still had inactive disease and 70 (40.5%) were in clinical remission on medication. The probability of achievement of inactive disease after 6, 12, and 24 months of therapy was 24%, 46% and 57%, respectively. On Cox regression analysis, the attainment of inactive disease was associated with lack of wrist involvement and an age at disease onset < 3.6 years. CONCLUSION: Around half of our patients with JIA treated with etanercept achieved a state of inactive disease. Children who lacked wrist involvement and were younger at disease onset had a greater likelihood of achieving inactive disease.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".