Frontiers in immunology
The predictive value of machine learning for the response to anti-TNF-α therapy in patients with Crohn's disease: a systematic review and meta-analysis
Par Lin Y, Sun S, Yang S et 1 autres.
Contenu en anglais
Résumé
Background
This meta-analysis aimed to evaluate the performance of machine learning (ML) in predicting the response to anti-tumor necrosis factor-α (anti-TNF-α) therapy in individuals with Crohn's disease (CD), providing an evidence-based basis for the construction or update of prediction tools.
Methods
PubMed, Cochrane Library, Embase, and Web of Science were comprehensively searched for studies published up to November 18, 2025 on ML predictive models for the therapeutic response to anti-TNF treatment in individuals with CD. The Prediction model Risk Of Bias Assessment Tool (PROBAST) was used to assess the risk of bias in the eligible articles. Model performance was assessed using the concordance index (C-index), and a meta-analysis was conducted.