Exposure–efficacy Relationships for Vedolizumab Induction Therapy in Patients with Ulcerative Colitis or Crohn’s Disease
Bibliographic record
Abstract
BACKGROUND AND AIMS: A positive relationship between vedolizumab trough serum concentrations and clinical outcomes in patients with ulcerative colitis [UC] or Crohn's disease [CD] has been reported. Here we further explore exposure-efficacy relationships for vedolizumab induction therapy in post hoc analyses of GEMINI study data. METHODS: Vedolizumab trough concentrations at Week 6 or 10 were grouped in quartiles and clinical outcome rates calculated. Exposure-efficacy relationships at Week 6 and potential baseline covariate effects were explored using logistic regression and individual predicted cumulative average concentration through Week 6 [Caverage] as exposure measure. RESULTS: Higher vedolizumab concentrations were associated with higher clinical remission rates; the exposure-efficacy relationship was steeper for UC than CD. Unadjusted analyses overestimated the relationship, more so for CD. From covariate-adjusted models, average probability of remission at Week 6 increased by approximately 15% for UC and 10% for CD between Caverage values of 35 and 84 µg/ml [5th and 95th percentiles, respectively]. On average, patients with higher albumin, lower faecal calprotectin [UC only], lower C-reactive protein [CD only], and no previous tumour necrosis factor-α [TNFα] antagonist use had a higher remission probability. Previous TNFα antagonist use had the greatest impact; remission probability was approximately 10% higher in treatment-naïve patients. CONCLUSIONS: Higher vedolizumab serum concentrations were associated with higher remission rates after induction therapy in patients with moderately to severely active UC or CD. This relationship is affected by several factors, including previous TNFα antagonist use. Prospective studies are needed to assess vedolizumab dose individualisation and optimisation.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".