Early Intervention With Vedolizumab and Longer-term Surgery Rates in Crohn’s Disease: Post Hoc Analysis of the GEMINI Phase 3 and Long-term Safety Programmes
Bibliographic record
Abstract
BACKGROUND: Crohn's disease (CD) is a chronic inflammatory bowel disease that, with progression, may require surgical intervention. AIM: To determine whether vedolizumab treatment of CD earlier in the disease course (≤2 or ≤5 years disease duration) influences risk of CD-related surgery after accounting for probability of response. METHODS: Post hoc analyses of data from CD patients treated with vedolizumab in the GEMINI 2, GEMINI 3, and GEMINI LTS trials (N=1253) evaluated CD-related surgery (bowel resection or colectomy) with stratification by probability of response to vedolizumab (low/intermediate or high). Analyses used a previously validated clinical decision support tool and both logistic regression and Cox proportional hazard analyses. RESULTS: In total, 113 (9.0%) vedolizumab-treated patients required CD-related surgery. Surgical rates were 6.1% and 9.8% for the high and low/intermediate probability of response groups, respectively. Risk of surgery was lower for patients with a high probability of response versus those with a low/intermediate probability of response (HR 0.50; 95%CI 0.29 to 0.85). For patients with a low/intermediate probability of vedolizumab response, there was a consistent trend for association between earlier treatment (≤2 or ≤5 years since diagnosis) and a lower risk of surgery relative to later treatment (≤2 years versus >2 years: OR 0.77, 95%CI 0.38 to 1.58; ≤5 years versus >5 years: OR 0.61, 95%CI 0.37 to 1.00). CONCLUSIONS: Earlier intervention with vedolizumab may be associated with lower rates of surgery. Use of the clinical decision support tool may help identify patients most likely to benefit from earlier intervention with vedolizumab.
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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 | 0.015 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".