Real-world clinical outcomes and healthcare costs in patients with Crohn’s disease treated with vedolizumab versus ustekinumab in the United States
Bibliographic record
Abstract
Objective To compare real-world treatment persistence, dose escalation, rates of opportunistic or serious infections, and healthcare costs in patients with Crohn’s disease (CD) receiving vedolizumab (VDZ) vs ustekinumab (UST) in the United States.Methods A retrospective observational study in adults with CD initiated on VDZ or UST on/after 26 September 2016, was performed using the IBM Truven Health MarketScan databases (1 January 2009–30 September 2018). Rates of treatment persistence, dose escalation, opportunistic or serious infection–related encounters, and healthcare costs per patient per month (PPPM) were evaluated. Entropy balancing was used to balance patient characteristics between cohorts. Event rates were assessed using weighted Kaplan-Meier analyses and compared between cohorts using log-rank tests. Healthcare costs were compared between cohorts using weighted 2-part models.Results 589 VDZ and 599 UST patients were included (172 [29.2%] and 117 [19.5%] were bio-naïve, respectively). After weighting, baseline characteristics were comparable between cohorts. No significant difference in rates of treatment persistence (12-month: VDZ, 76.5%; UST, 82.1%; p = .17), dose escalation (12-month: VDZ, 29.3%; UST, 32.7%; p = .97), or opportunistic or serious infection–related encounters were observed between VDZ and UST. Total mean healthcare costs were significantly lower for patients treated with VDZ vs UST (mean cost difference = –$5051 PPPM; p < .01). Findings were consistent in bio-naïve patients.Conclusions In this real-world study, similar treatment persistence, dose escalation, and rates of opportunistic or serious infections were observed with VDZ- and UST-treated patients with CD. However, VDZ was associated with a significantly lower cost outlay for healthcare systems.
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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 | 0.001 |
| 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 | 0.001 |
| 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".