Development of explainable machine learning models to predict side effects in patients with rheumatoid arthritis taking methotrexate treatment: a nationwide multicentre cohort study.

ABSTRACT:

Objectives

Methotrexate (MTX) effectively controls rheumatoid arthritis (RA) but often leads to side effects (SE) such as gastrointestinal (GI) issues, liver toxicity and bone marrow suppression. To develop clinically interpretable machine learning (ML) models that accurately predict MTX-related SE in patients with RA taking MTX. The aim was to enhance predictive accuracy and to identify patient-specific risk factors using explainable artificial intelligence (XAI), thereby enabling transparent clinical interpretation. We specifically sought to address the unmet need for individualised risk stratification using real-world, multicentre observational data.

Design

Retrospective case-control study.

Setting

Across 23 rheumatology clinics in South Korea, based on data from a

SUBMITTER: Jang J 

PROVIDER: S-EPMC12666182 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature