Systematic review: the safety of vedolizumab for the treatment of inflammatory bowel disease
Bibliographic record
Abstract
BACKGROUND: Vedolizumab specifically recognises the α4β7 integrin and selectively blocks gut lymphocyte trafficking: potentially, it offers gut-specific immunosuppression. AIM: To review the safety of vedolizumab and summarise post-marketing data to assess if any safety concerns that differ from registration trials have emerged. METHOD: A systematic bibliographic search identified six registration trials and nine cohort studies. RESULTS: Integrated data from registration trials included 2830 vedolizumab-exposed patients (4811 person-years exposure [PYs]) and 513 placebo patients. This reported lower exposure-adjusted incidence rates of infection (63.5/100 PYs; 95% CI: 59.6-67.3) and serious adverse events (20.0/100 PYs; 95% CI: 18.5-21.5) compared to placebo (82.9/100 PYs; 95% CI: 68.3-97.5) and (28.3/100 PYs 95% CI: 20.6-35.9) respectively. Higher, but statistically insignificant rates of enteric infections occurred in vedolizumab-exposed patients (7.4/100 PYs; 95% CI: 6.6-8.3) compared to placebo (6.7 PYs; 95% CI: 3.2-10.1). Six post-marketing cohort studies (1049 patients, 403 PYs) demonstrated rates of infection of 8% (82/1049); enteric infection of 2% (21/1049) and adverse events of 16% (166/1049). Multivariate analysis in one cohort study suggested increased risk of surgical site infection with perioperative VDZ. Human experience in pregnancy is limited. CONCLUSIONS: Post-marketing data confirm the excellent safety of vedolizumab observed in registration trials. The signal of post-operative complications should be interpreted with caution, but warrants further study. Although comparative studies are needed, Vedolizumab may be a safe alternative in patients who best avoid systematic immunosuppression, including those pre-disposed to infection, malignancy or the elderly.
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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 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".