Scleritis: A Paradoxical Effect of Etanercept? Etanercept-associated Inflammatory Eye Disease
Bibliographic record
Abstract
OBJECTIVE: To describe 3 cases of scleritis associated with etanercept use for rheumatoid arthritis (RA) and to review the literature related to inflammatory eye diseases associated with the use of etanercept. METHODS: Three cases of severe scleritis during etanercept therapy were analyzed. A systematic review of the literature in PubMed, Embase, and the Cochrane Library was performed, from 1962 to July 2010. RESULTS: Three patients with seropositive RA developed scleritis 7-28 months after initiation of etanercept, for the first time during their long-lasting disease. In all patients the underlying disease had responded well to anti-tumor necrosis factor therapy. Ocular inflammation went into remission after discontinuation of etanercept, and no other relapses were observed. One patient experienced a dechallenge-rechallenge phenomenon (improvement in symptoms following discontinuation of the agent, then reappearance or worsening of symptoms on reexposure to the agent). Forty-two cases of inflammatory eye diseases believed to be associated with the use of etanercept have been reported in the literature: 33 uveitis, 8 scleritis, 1 orbital myositis, concerning 16 patients with RA, 10 with juvenile idiopathic arthritis, 14 with ankylosing spondylitis, and 2 with psoriatic spondyloarthropathy. Dechallenge was performed in 28 patients, leading to resolution of symptoms. Rechallenge was done in 6 cases, with clear exacerbation. CONCLUSION: Ocular inflammation is paradoxically a potential adverse effect of etanercept, even in previously uninvolved eyes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".