A200 VEDOLIZUMAB IS AN EFFECTIVE TREATMENT OPTION FOR NON INFLAMMATORY BOWEL DISEASE RELATED ENTEROPATHY
Bibliographic record
Abstract
Abstract Background Vedolizumab is an α4β7 integrin antagonist which inhibits intestinal T-cell translocation by blocking integrin interactions with mucosal vascular addressin cell adhesion molecule 1, reducing lymphocyte mediated inflammation. Its gut selective mode of action and safety profile have lead to reports of off-label use of vedolizumab for non-IBD related inflammatory intestinal disorders. Aims We conducted a literature review to assess clinical, endoscopic and histologic improvement in patients treated with Vedolizumab for non-IBD enteropathies refractory to conventional therapy. Methods EMBASE, Medline, Clinicaltrials.gov and Cochrane CENTRAL were searched on September 12, 2019 for case studies, case series and cohort studies without language restriction yielding 356 studies with 164 duplicates, 74 non-applicable studies, leaving 118 studies. After full text review, 98 studies were excluded, leaving 20 included studies. Results 65% of patients (51/79) achieved clinical response. 40.5% (15/37) of patients experienced endoscopic improvement and 33% (17/51) of patients experienced histologic improvement. The duration of treatment varied from patients receiving only induction doses to up to 70 months for maintenance therapy. There were four reported cases of withdrawal due to adverse events from Vedolizumab. Conclusions In a treatment refractory population, over 60% of patients reported to have a clinical response and one-third endoscopic/histologic response, indicating that Vedolizumab is a viable option for patients with refractory non-IBD enteropathy. Funding Agencies None
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".