Association Between Cognitive Trajectories and Disability Progression in Patients With Relapsing-Remitting Multiple Sclerosis.

Background and Objectives Longitudinal cognitive trajectories in multiple sclerosis are heterogenous and difficult to measure. We aimed to identify discrete longitudinal reaction time trajectories in relapsing remitting multiple sclerosis using a computerized cognitive battery and assess the association between trajectories of reaction time and disability progression. Methods All participants serially completed computerized reaction time tasks measuring psychomotor speed, visual attention and working memory. Participants completed at least three testing sessions over a minimum of 180 days. Longitudinal reaction times were modelled using Latent Class Mixed Models to identify groups of individuals sharing similar latent characteristics. Optimal models were validated for consistency and baseline associations with class membership tested using multinomial logistic regression. Inter-class differences in the probability of reaction time worsening and the probability of 6-month confirmed disability progression were assessed using survival analysis. Results A total of 460 people with relapsing remitting multiple sclerosis were included in the analysis. For each task of the MSReactor battery, the optimal model comprised of 3 latent classes. All MSReactor tasks could identify a group with high probability of reaction time slowing. The visual attention and working memory tasks could identify a group of participants who were 3.7 and 2.6 times more likely to experience a 6-month confirmed disability progression, respectively. Participants could be classified into predicted cognitive trajectories after just 5 tests with between 64% and 89% accuracy. Discussion Latent class modelling of longitudinal cognitive data collected by a computerized battery identified patients with worsening reaction times and increased risk of disability progression. Slower baseline reaction time, age and disability increased assignment into this trajectory. Monitoring of cognition in clinical practice using computerized tests may enable detection of cognitive change trajectories and people with relapsing remitting multiple sclerosis at risk of disability progression.