Influence de la localisation des maladies inflammatoires chroniques de l’intestin sur l’efficacité du Védolizumab : une étude multicentrique
Bibliographic record
Abstract
Background: influence of inflammatory bowel disease (IBD) location on Vedolizumab effectiveness is unclear. Objective: determine if IBD location is a predictive factor of steroid-free clinical remission (SFCR) at week 24 under Vedolizumab. Methods: from 2014 to 2017, all patients with moderate to severe Crohn disease (CD) and Ulcerative Colitis (UC) receiving Vedolizumab in Grenoble and Lyon-Sud University Hospitals were included in a retrospective multicenter study. SFCR was defined by a Harvey-Bradshaw Index (HBI) < or = 4 for CD and a Partial Mayo Score (PMS) < or = 2 with each sub-score of 1 or less for UC, with corticosteroids withdrawn for at least 1 month. Disease location was defined according to Montreal classification. Results: 133 CD and 90 UC were included. At week 24, SFCR was achieved in 33.1 % (n=44/133) CD patients and 33.3% (n=30/90) UC patients. In CD, SFCR rates were 33%, 36% and 35%, respectively for L1, L2 and L3 disease locations (p=0.906), with no difference when isolated colonic disease (L2) was compared to ileal disease (L1 and L3), (p=0.928). In UC, SFCR rates were 37% and 31%, respectively for distal UC (E1, E2) and pancolitis (E3), (p=0.594). SFCR at week 24 was achieved in 17% of CD patients with active perineal disease versus 42% of CD patients without active perineal disease (p=0.037). Conclusion: apart for active perineal CD, SFCR at week 24 under Vedolizumab therapy was not associated with IBD location. A prospective study, with rigorous assessment of disease and flare locations is required.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".