The Effectiveness of Medical Therapies for Joint, Skin and Eye Extraintestinal Manifestations in IBD—An Umbrella Review
Bibliographic record
Abstract
BACKGROUND: Extraintestinal manifestations (EIMs) occur commonly in patients with inflammatory bowel disease (IBD), affecting joints, skin, eyes and other organs, and contributing to morbidity and long-term disability. AIMS: To synthesise evidence from systematic reviews (SRs) on the effectiveness and safety of medical treatments for IBD EIMs in IBD of joints, skin and eyes. METHODS: For this umbrella review, we searched three databases for relevant SRs published until May 30, 2024. Two independent reviewers performed screening, data extraction and quality appraisal (AMSTAR-2). RESULTS: Ten, 12 and six SRs, respectively, provided data on medical therapies for articular, dermatological and ocular manifestations. Anti-TNF therapy showed high response rates for axial (59.1%-61.8%) and peripheral arthritis (73.4%-81.2%). The lowest improvement was in patients treated with vedolizumab for joint manifestations. Ustekinumab was effective for arthralgia and psoriatic arthritis, but not for axial spondylarthritis. High heterogeneity of response was reported for anti-TNF, vedolizumab, ustekinumab and tofacitinib (21%-100%) depending on the dermatological manifestation. No SRs evaluated IL-23 p40 antagonists or other oral small molecules. The incidence of new ocular EIMs was 1% for vedolizumab and ustekinumab. Anti-TNF agents were effective for most ocular EIM cases. Ustekinumab improved ocular symptoms in 55%-59%. Safety data were limited, with evidence certainty ranging from moderate to low. CONCLUSIONS: Evidence for medical therapies for joint, skin and eye EIMs in IBD is heterogeneous and of low quality. Further research is needed, including a multidisciplinary approach and novel and practical methods for endpoint evaluation.
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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 | 0.017 | 0.066 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.018 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".