Machine learning identifies a profile of inadequate responder to methotrexate in rheumatoid arthritis.

Date publication

novembre 2022

Journal

Rheumatology (Oxford, England)

Auteurs

Membres identifiés du Cancéropôle Est :
Pr GUILLEMIN Francis

Tous les auteurs :
Duquesne J, Bouget V, Cournède PH, Fautrel B, Guillemin F, de Jong PHP, Heutz JW, Verstappen M, van der Helm-van Mil AHM, Mariette X, Bitoun S

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/36416134

Résumé

Around 30% of patients with rheumatoid arthritis (RA) have an inadequate response to methotrexate (MTX). We aimed to use routine clinical and biological data to build machine learning models predicting EULAR inadequate response to MTX and to identify simple predictive biomarkers.

Mots clés

Biomarker, Machine Learning, Methotrexate, Rheumatoid Arthritis, Treatment Response

Référence

Rheumatology (Oxford). 2022 11 23;: