Andrea Perra

Vedolizumab in inflammatory bowel disease: Real-world outcomes and their prediction with machine learning—the IG-IBD LIVE study

Onali, Sara;
2025-01-01

Abstract

Background and aims: Real-world studies on vedolizumab in inflammatory bowel disease (IBD) are often limited by small sample size and short follow-up. In this study, we investigated the 2-year effectiveness and safety of vedolizumab in patients with IBD, and applied eXplainable Artificial Intelligence (XAI) to identify predictors of both. Methods: The Long-term Italian Vedolizumab Effectiveness (LIVE) study is multicentric, ambispective, observational study enrolling 1111 IBD patients (563 Crohn's disease, CD, 542 ulcerative colitis, UC). Steroid-free clinical remission (SFCR) at 24 months was the primary endpoint. A XAI model (eXtreme Gradient Boosting, XGB) was applied to identify the main clinical predictors of SFCR and development of adverse events (AEs). Results: Rates of SFCR at 24 months were 31.6 % and 39.7 % in CD and UC patients, and 0.14 AEs per patient-year was recorded. On XGB analysis, previous exposure to anti-TNFα and older age were the most important drivers for the prediction of SFCR; lower baseline CRP levels and fewer comorbidities were the most important features associated with no development of AEs. Conclusions: Vedolizumab is effective and safe in IBD patients. XAI yielded promising results in identifying the most important predictors of SFCR and development of AEs.
2025
Inglese
57
7
1393
1402
10
Esperti anonimi
scientifica
Anti-integrin therapy
Machine learning (ML)
Shapley values (SHAP)
Goal 3: Good health and well-being
no
Pugliese, Daniela; Privitera, Giuseppe; Cersullo, Nicola; Bordekar, Harsh; Crispino, Federica; Mezzina, Nicolò; Pellegrini, Lucienne; Allocca, Mariang ...espandi
1.1 Articolo in rivista
info:eu-repo/semantics/article
1 Contributo su Rivista::1.1 Articolo in rivista
262
62
none
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