ArticleCrohn's & colitis 3602022
Probability of Response as Defined by a Clinical Decision Support Tool Is Associated With Lower Healthcare Resource Utilization in Vedolizumab-Treated Patients With Crohn's Disease.
Article in Crohn's & colitis 360, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The trial behind it
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Who cites it
7 citing papers in PubMed.
- Predictive Utility of the Vedolizumab Clinical Decision Support Tool in a Real-World IBD Cohort: Differential Performance in Crohn's Disease and Ulcerative Colitis.Medicina (Kaunas, Lithuania) · 2026Article
- Five-Year Persistence of Vedolizumab in Crohn's Disease: Results from a Real-World Cohort.Journal of clinical medicine · 2026Article
- Vedolizumab clinical decision support tool predicts clinically relevant targets in patients with Crohn's disease.Therapeutic advances in gastroenterology · 2026Article
- Artificial Intelligence in Advancing Inflammatory Bowel Disease Management: Setting New Standards.Cancers · 2025Review
- Predictive, preventive and personalised approach as a conceptual and technological innovation in primary and secondary care of inflammatory bowel disease benefiting affected individuals and populations.The EPMA journal · 2024Review
- Vedolizumab in Mild-to-Moderate Crohn's Disease Patients Naïve to Biological Therapy: A Multicentric Observational Study.Crohn's & colitis 360 · 2023Article
- Impact of artificial intelligence on prognosis, shared decision-making, and precision medicine for patients with inflammatory bowel disease: a perspective and expert opinion.Annals of medicine · 2023Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: A previously developed clinical decision support tool (CDST) identified patients with Crohn's disease (CD) most likely to respond to vedolizumab. This study evaluated the ability of the CDST to predict real-world healthcare resource utilization (HRU). Methods: The Optum and Truven healthcare databases were searched for patients with CD treated with vedolizumab (Optum, Results: In the Optum data set, the 5- and 3-variable CDSTs identified lower rates of surgery or hospitalization in CD patients with higher probability of vedolizumab response. Per-patient total costs were 2.5 times lower for CD patients with high versus low probability of vedolizumab response ($12 943 vs $32 931). The 5- and 3-variable CDSTs did not consistently identify anti-TNF-treated CD patients with higher HRU. The 3-variable CDST also identified vedolizumab-treated CD patients with higher probability of response and lower probability for surgery or hospitalization in the Truven data set. Conclusions: The 5-variable CDST identified CD patients treated with vedolizumab, but not an anti-TNF agent, at higher risk for HRU. The 3-variable CDST offers similar performance but more flexibility by removing laboratory data requirements for prediction. These validated CDSTs can be integrated into population health monitoring algorithms using real-world data.
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