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

ABSTRACT:

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 methods in machine learning were used to i) identify clusters with distinct disease patterns following MTX initiation; ii) predict cluster membership; and iii) compare clusters to existing treatment response measures.

Methods

Discovery and verification cohorts included CYP who first initiated MTX before January 2018 in one of four UK multicentre prospective cohorts of JIA within the CLUSTER consortium. JADAS components (active joint count, physician (PGA) and parental (PGE) global assessment

SUBMITTER: Shoop-Worrall SJW 

PROVIDER: S-EPMC10792564 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature