Towards stratified treatment of JIA: machine learning identifies subtypes in response to methotrexate from four UK cohortsResearch in context

Towards stratified treatment of JIA: machine learning identifies subtypes in response to methotrexate from four UK cohortsResearch in context

Summary: Background: Methotrexate (MTX) is the gold-standard first-line disease-modifying anti-rheumatic drug for juvenile idiopathic arthritis (JIA), despite only being either effective or tolerated in half of children and young people (CYP). To facilitate stratified treatment of early JIA, novel...

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Bibliographic Details
Main Authors: Stephanie J.W. Shoop-Worrall, Saskia Lawson-Tovey, Lucy R. Wedderburn, Kimme L. Hyrich, Nophar Geifman, Aline Kimonyo, Alyssia McNeece, Andrew Dick, Andrew Morris, Annie Yarwood, Athimalaipet Ramanan, Bethany R. Jebson, Chris Wallace, Daniela Dastros-Pitei, Damian Tarasek, Elizabeth Ralph, Emil Carlsson, Emily Robinson, Emma Sumner, Fatema Merali, Fatjon Dekaj, Helen Neale, Hussein Al-Mossawi, Jacqui Roberts, Jenna F. Gritzfeld, Joanna Fairlie, John Bowes, John Ioannou, Melissa Kartawinata, Melissa Tordoff, Michael Barnes, Michael W. Beresford, Michael Stadler, Paul Martin, Rami Kallala, Sandra Ng, Samantha Smith, Sarah Clarke, Soumya Raychaudhuri, Stephen Eyre, Sumanta Mukherjee, Teresa Duerr, Thierry Sornasse, Vasiliki Alexiou, Victoria J. Burton, Wei-Yu Lin, Wendy Thomson, Zoe Wanstall
Format: Article
Language:English
Published: Elsevier 2024-02-01
Series:EBioMedicine
Subjects:
Juvenile idiopathic arthritis
Machine learning
Treatment outcome
Epidemiology
Methotrexate
Online Access:http://www.sciencedirect.com/science/article/pii/S2352396423005121

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http://www.sciencedirect.com/science/article/pii/S2352396423005121

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