Exploring the feasibility and validity of online assessment tools for motor and cognitive impairment in multiple sclerosis
File(s)
Author(s)
Lerede, Annalaura
Type
Thesis
Abstract
Multiple Sclerosis (MS) can result in both motor and cognitive impairment. This thesis is dedicated to the development and validation of online assessment tools to measure these impairments.
The first part introduces a novel approach for analysing 11 years of patient-reported outcome (PRO) data from 15,976 users of the UK MS Register. Using this approach, robust associations were shown between physical disability and disease subtype and duration. Results indicated progressive deterioration over time for most subtypes and significant differences among subtypes, underscoring the potential of PROs for capturing physical disability progression.
The second part focuses on developing and validating an online cognitive assessment tool for people with MS (pwMS) and comprises two studies. The first study evaluated 22 online cognitive tasks on a cohort of 3,066 pwMS to demonstrate the feasibility of online cognitive assessment in pwMS and form a concise battery for measuring cognitive deficits in this population. The second study validated this battery on an overlapping cohort of 2,696 pwMS. The high participation and completion rates demonstrated the feasibility of the tool in pwMS. The tasks selected for the optimal battery exhibited consistent sensitivity to MS-related deficits across timepoints and aligned with cognitive domains reported to be affected in the literature. Additionally, data collected with the battery enabled confirming known associations with disease subtype and duration with greater statistical power.
In the final part, PROs and cognitive performance measures were combined to derive symptoms-driven subtypes. Clustering analysis identified four clusters with diverse combinations and severities of motor and cognitive symptoms, distinct from traditional clinical phenotypes.
Altogether these findings highlight the value of online assessment tools in MS and provide a battery of online cognitive tasks for longitudinal monitoring of MS-related deficits. The integration of these tools within clinical registries holds tremendous potential to advance our understanding of MS.
The first part introduces a novel approach for analysing 11 years of patient-reported outcome (PRO) data from 15,976 users of the UK MS Register. Using this approach, robust associations were shown between physical disability and disease subtype and duration. Results indicated progressive deterioration over time for most subtypes and significant differences among subtypes, underscoring the potential of PROs for capturing physical disability progression.
The second part focuses on developing and validating an online cognitive assessment tool for people with MS (pwMS) and comprises two studies. The first study evaluated 22 online cognitive tasks on a cohort of 3,066 pwMS to demonstrate the feasibility of online cognitive assessment in pwMS and form a concise battery for measuring cognitive deficits in this population. The second study validated this battery on an overlapping cohort of 2,696 pwMS. The high participation and completion rates demonstrated the feasibility of the tool in pwMS. The tasks selected for the optimal battery exhibited consistent sensitivity to MS-related deficits across timepoints and aligned with cognitive domains reported to be affected in the literature. Additionally, data collected with the battery enabled confirming known associations with disease subtype and duration with greater statistical power.
In the final part, PROs and cognitive performance measures were combined to derive symptoms-driven subtypes. Clustering analysis identified four clusters with diverse combinations and severities of motor and cognitive symptoms, distinct from traditional clinical phenotypes.
Altogether these findings highlight the value of online assessment tools in MS and provide a battery of online cognitive tasks for longitudinal monitoring of MS-related deficits. The integration of these tools within clinical registries holds tremendous potential to advance our understanding of MS.
Version
Open Access
Date Issued
2024-02-16
Date Awarded
01/08/2024
License URL
Advisor
Hampshire, Adam
Nicholas, Richard
Publisher Department
Department of Computing
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)