A novel prognostic score to assess the risk of progression in relapsing-remitting multiple sclerosis patients.

ABSTRACT:

Background

At the patient level, the prognostic value of several features that are known to be associated with an increased risk of converting from relapsing-remitting (RR) to secondary phase (SP) multiple sclerosis (MS) remains limited.

Methods

Among 262 RRMS patients followed up for 10 years, we assessed the probability of developing the SP course based on clinical and conventional and non-conventional magnetic resonance imaging (MRI) parameters at diagnosis and after 2 years. We used a machine learning method, the random survival forests, to identify, according to their minimal depth (MD), the most predictive factors associated with the risk of SP conversion, which were then combined to compute the secondary progressive risk score (SP-RiSc).

Results

During the obse

SUBMITTER: Pisani AI 

PROVIDER: S-EPMC8360167 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature