3115 Longitudinal trajectories of digital cognitive biomarkers for multiple sclerosis

BackgroundCognitive impairment is one of the most common and debilitating symptoms of relapsing remitting multiple sclerosis (RRMS). Digital cognitive biomarkers require less time and resources and are rapidly gaining popularity in clinical settings. We examined the longitudinal trajectory of the iPad-based Processing Speed Test (PST) and predictors of change over time.MethodsWe prospectively enrolled relapsing-remitting multiple sclerosis (RRMS) patients with an EDSS score of less than four. Longitudinal data was analysed with mixed effect modelling and latent class mixed models.ResultsAt a population level, PST trajectory was stable. A small practice effect was present up to the 4th visit. Age, baseline disability, T2 lesion volume, male gender and depression were associated with less correct PST responses, whilst years of education and full/part-time employment were associated with more correct PST responses.We identified four trajectories of processing speed with latent class analysis. The lowest latent class was typified by the lack of a practice effect and was associated with a greater hazard of time to sustained 5% decrease in PST (HR 2.84, 95%CI 1.16–6.94, p=0.02).ConclusionIn this cohort of mild to moderate RRMS, PST scores remained largely stable over time. Membership in the worst latent class trajectory was associated with a sustained 5% PST decrease. Poor cognitive performance at baseline and the lack of a practice effect is a predictor of future cognitive decline and should prompt early intervention for maximising cognitive function such as treatment escalation.