Predicting the progression of difficult-to-treat rheumatoid arthritis by a machine learning scoring system, from the FIRST registry
Masanobu Ueno, Koshiro Sonomoto, Hiroaki Tanaka, Atsushi Nagayasu et autres
OBJECTIVES: This study aimed to develop and validate a prediction model for the future progression of difficult-to-treat rheumatoid arthritis (D2T RA) and support the precise use of biologic and targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs). METHODS: Data were analysed from 1221 patients …
jp (code pays fourni par la source)