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

OBJECTIVES: Around 30% of patients with RA have an inadequate response to 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. METHODS: Models were trained on RA patients f...

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Detalles Bibliográficos
Autores principales: Duquesne, Julien, Bouget, Vincent, Cournède, Paul Henry, Fautrel, Bruno, Guillemin, Francis, de Jong, Pascal H P, Heutz, Judith W, Verstappen, Marloes, van der Helm-van Mil, Annette H M, Mariette, Xavier, Bitoun, Samuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Clinical Science
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10321123/
https://www.ncbi.nlm.nih.gov/pubmed/36416134
http://dx.doi.org/10.1093/rheumatology/keac645

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10321123/
https://www.ncbi.nlm.nih.gov/pubmed/36416134
http://dx.doi.org/10.1093/rheumatology/keac645

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