Risk for development of inflammatory bowel disease under inhibition of interleukin 17: A systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Cases of inflammatory bowel disease (IBD) during treatment with interleukin (IL)-17 antagonists have been reported from trials in psoriasis, psoriatic arthritis, and ankylosing spondylitis. The aim of this study was to assess the overall risk for development of IBD due to IL-17 inhibition. DESIGN: Systematic review and meta-analysis of studies conducted 2010-2018 of treatment with IL-17 antagonists in patients with psoriasis, psoriatic arthritis, ankylosing spondylitis, and rheumatoid arthritis. We compared risk of IBD development in anti-IL-17 treated patients compared to placebo treatments. We also computed incident rates of IBD overall. A 'worst case scenario' defining subjects ambiguous for prevalent versus incident cases for the latter was also applied. RESULTS: Sixty-six studies of 14,390 patients exposed to induction and 19,380 patients exposed to induction and/or maintenance treatment were included. During induction, 11 incident cases of IBD were reported, whereas 33 cases were diagnosed during the entire treatment period. There was no difference in the pooled risk of new-onset IBD during induction studies for both the best-case [risk difference (RD) 0.0001 (95% CI: -0.0011, 0.0013)] and worst-case scenario [RD 0.0008 (95% CI: -0.0005, 0.0022)]. The risk of IBD was not different from placebo when including data from maintenance and long-term extension studies [RD 0.0007 (95% CI: -0.0023, 0.0036) and RD 0.0022 (95% CI: -0.0010, 0.0055), respectively]. CONCLUSIONS: The risk for development of IBD in patients treated with IL-17 antagonists is not elevated. Prospective surveillance of patients treated with IL-17 antagonists with symptom and biomarker assessments is warranted to assess for onset of IBD in these patients.
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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 | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.043 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".