Efficacy of Vedolizumab in Fistulising Crohn’s Disease: Exploratory Analyses of Data from GEMINI 2
Bibliographic record
Abstract
BACKGROUND AND AIMS: Medical management of fistulising Crohn's disease [CD] is constrained by the limited number of available therapies. We evaluated the efficacy of vedolizumab, a gut-selective α4β7 integrin antagonist approved for treating moderately to severely active CD, in a subpopulation of patients with fistulising CD who participated in the GEMINI 2 trial [NCT00783692]. METHODS: Exploratory analyses of data from the GEMINI 2 trial were conducted in 461 responders to 6-week vedolizumab induction therapy who received maintenance placebo [VDZ/PBO, N = 153] or vedolizumab [VDZ/VDZ, N = 308]. Fistula closure rates were assessed at Weeks 14 and 52, and the time to fistula closure was analysed by the Cox proportional hazards model with adjustments for significant covariates. RESULTS: At entry into the maintenance period, 153 [33%] patients had a history of fistulising disease and 57 [12%] patients had ≥1 active draining fistula. By Week 14, 28% of VDZ/VDZ-treated patients compared with 11% of VDZ/PBO-treated patients (95% confidence interval [CI], -11.4 to 43.9) achieved fistula closure. Corresponding rates at Week 52 were 31% and 11% (absolute risk reduction [ARR]: 19.7%; 95% CI, -8.9 to 46.2). Similarly, VDZ/VDZ-treated patients had faster time to fistula closure and were more likely to have fistula closure at Week 52 [33% vs 11%; HR: 2.54; 95% CI, 0.54-11.96]. Prior failure of antibiotic therapy was a negative predictor of fistula closure [HR: 0.217; 95% CI, 0.059-0.795; p = 0.021], whereas trough vedolizumab concentrations did not affect closure rates. CONCLUSIONS: Our findings are consistent with the beneficial effect of vedolizumab treatment for fistulising CD.
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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 | 0.019 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".