Development of Inflammatory Bowel Disease in Patients with Juvenile Idiopathic Arthritis Treated with Etanercept
Bibliographic record
Abstract
OBJECTIVE: With the increasing use of etanercept for juvenile idiopathic arthritis (JIA) new possible adverse events are reported including new autoimmune diseases. Our purpose was to examine if the incidence of inflammatory bowel disease (IBD) in patients with JIA using etanercept is higher than in the healthy age-matched population. We give the clinical characteristics of the IBD in patients with JIA using etanercept. METHODS: The national JIA registries for etanercept of The Netherlands, Germany, Finland, Denmark, and Italy were searched for patients with JIA and IBD. The total number of patient-years was used to calculate incidence. The physicians of the identified patients were asked to give clinical details. RESULTS: Thirteen cases of IBD in JIA patients were identified in the registries between 1999 and 2008. The IBD incidence in JIA patients while using etanercept was 362 per 100,000 patient-years under etanercept, about 43 times higher than in the general pediatric population. Clinical presentation of IBD in JIA patients using etanercept was similar to that in non-JIA patients. The median time between onset of JIA and onset of IBD was 6 years and 10 months. The time between the start of etanercept and the first appearance of IBD symptoms was between 9 days and 4.5 years. CONCLUSION: The incidence of IBD in JIA patients using etanercept seems to be markedly increased, analyzing data from European registries. This incidence of IBD in the etanercept registries cannot be compared to the incidence of IBD in JIA patients using other treatment without etanercept, because such registries do not exist yet in all European countries. These findings are in keeping with a report of 8 new IBD cases occurring in French children with JIA using etanercept. These findings illustrate the need for large international disease-specific registries focused on outcome and pharmacovigilance.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 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".