The relationship among vedolizumab drug concentrations, biomarkers of inflammation, and clinical outcomes in a Canadian real-world study
Bibliographic record
Abstract
Abstract Background and Aims Therapeutic drug monitoring is used to optimize anti-tumour necrosis factor biologic effectiveness in inflammatory bowel disease, but its role with other biological classes is unclear. This study explores relationships between post-induction vedolizumab trough concentrations and biochemical outcomes in a real-world study of individuals with inflammatory bowel disease. Methods This retrospective analysis of data from a national patient support program between 2018 and 2020, included 436 individuals with Crohn’s disease or ulcerative colitis receiving vedolizumab. Optimal vedolizumab concentration thresholds (at weeks 6 and 14) were determined based on their ability to predict biochemical normalization (week 30 faecal calprotectin [<250 µg/g], C-reactive protein [<5 mg/l]). Thresholds best associated with each outcome were evaluated in multivariate analyses. Results Among patients with Crohn’s disease, week 6 serum vedolizumab concentrations (>41.65 µg/ml) predicted normalization defined by C-reactive protein: Spearman correlation coefficient [ρ] = −0.26, P = 0.002 and multivariate analysis (MVA)—OR: 3.22, 95% CI: 1.32–7.87, P = 0.01, and at week 14 (>22.25 µg/ml): ρ = −0.38, P < 0.0001, and MVA—OR: 3.21, 95% CI: 1.26–8.17 but not faecal calprotectin. Similarly, among patients with ulcerative colitis, week 6 vedolizumab concentrations (>39.65 g/ml) predicted normalization defined by C-reactive protein: ρ = −0.26, P = 0.005 and MVA—OR: 4.03, 95% CI: 1.30–12.52, P = 0.016, and at week 14 (>17.35 µg/ml): ρ = −0.39, P = 0.0001 and MVA—OR: 6.95, 95% CI: 1.81–26.77, P = 0.005, but not faecal calprotectin. Conclusions Induction and post-induction serum vedolizumab were not consistently associated with biochemical normalization. As such, proactive therapeutic drug monitoring for vedolizumab should not be routinely incorporated in a treat to target strategy for inflammatory bowel disease. Clinical Trial Registration Number NCT04567628.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".