Cost Effectiveness of Sequencing Vedolizumab as First-Line Biologic in Ulcerative Colitis and Crohn's Disease in Canada: An Analysis Using Real-World Evidence from the EVOLVE Study
Bibliographic record
Abstract
INTRODUCTION: Vedolizumab is a gut-selective anti-lymphocyte trafficking biologic indicated for the treatment of adult patients with moderately to severely active ulcerative colitis (UC) and Crohn's disease (CD) in Canada. OBJECTIVE: The objective of this study was to evaluate the cost effectiveness of treatment sequencing for UC and CD from a public healthcare payer perspective, leveraging new real-world evidence from the literature and the EVOLVE study, a retrospective chart review. METHODS: Using separate decision tree/Markov models to assess cost effectiveness for UC and CD, two sequencing approaches were estimated for adult patients (≥ 18 years) diagnosed with UC or CD who were biologic-naïve: vedolizumab as first-line biologic followed by anti-tumor necrosis factor (TNF)-α versus first-line anti-TNFα followed by vedolizumab. Treatment effectiveness (response and remission), surgery rates, dose escalation and regain of response and safety inputs were estimated from EVOLVE, a retrospective chart review of real-world data, and evidence synthesis from the literature, whereas costs and utilities were estimated from health technology assessment reports, clinical trials, and the literature. Biosimilar costs were used for anti-TNFα. Both models simulated a 5-year time horizon and discounted costs and outcomes at 1.5%. Probabilistic base-case analyses (n = 10,000) reported total costs (2023 Canadian dollars) and quality-adjusted life-years (QALYs). Several scenario analyses were conducted to explore robustness of results. RESULTS: In UC, vedolizumab as a first-line biologic followed by anti-TNFα resulted in an incremental gain of 0.09 QALYs (2.46 vs. 2.55) and saved $7179 ($134,028 vs. $126,848), making this a dominant strategy compared with first-line anti-TNFα followed by vedolizumab. In CD, use of vedolizumab as a first-line biologic resulted in an incremental gain of 0.04 QALYs (3.35 vs. 3.39) at an incremental cost of $50,631 ($89,850 vs. $140,381) versus first-line anti-TNFα followed by vedolizumab (incremental cost-effectiveness ratio of $1,265,775 per QALY). CONCLUSIONS: Based on this analysis, sequencing vedolizumab as a first-line biologic prior to anti-TNFα in UC and CD provided additional clinical benefit to patients. In UC, vedolizumab as a first-line biologic also saved healthcare system costs compared with anti-TNFα, whereas in CD, vedolizumab provided incremental benefit at an incremental cost, which was not considered cost effective at a threshold of $50,000/QALY.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".