Identifying key clinical and biochemical predictors of treatment outcomes in inflammatory bowel disease: a real-world evidence study.

ABSTRACT: Inflammatory bowel disease (IBD), including Crohn's disease and Ulcerative colitis, often shows variable responses to biological therapies. Identifying the most significant variables for predicting the response to these therapies could help prioritize efforts in data collection and preprocessing. This study evaluated the predictive performance of machine learning models in forecasting remission and response to vedolizumab and ustekinumab in the treatment of IBD. The goal was not to compare the two therapies, but rather to identify the variables most influential in predicting response for each treatment. Data from 227 IBD patients treated at Virgen Macarena University Hospital (2015-2022) were analyzed. Clinical, demographic, and laboratory variables were used to develop Extreme gradient bo

SUBMITTER: Rodriguez JLG 

PROVIDER: S-EPMC12638824 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature