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Digital Outcome Measures Are Associated with Brain Atrophy in Patients with Multiple Sclerosis

Abstract

Background: Digital monitoring of people with multiple sclerosis (PwMS) using smartphone-based monitoring tools is a promising method to assess disease activity and progression.

Objective: To study cross-sectional and longitudinal associations between active and passive digital monitoring parameters and MRI volume measures in PwMS.

Methods: In this prospective study, 92 PwMS were included. Clinical tests [Expanded Disability Status Scale (EDSS), Timed 25 Foot Walk test (T25FW), 9-Hole Peg Test (NHPT), and Symbol Digit Modalities Test (SDMT)] and structural MRI scans were performed at baseline (M0) and 12-month follow-up (M12). Active monitoring included the smartphone-based Symbol Digit Modalities Test (sSDMT) and 2 Minute Walk Test (s2MWT), while passive monitoring was based on smartphone keystroke dynamics (KD). Linear regression analyses were used to determine cross-sectional and longitudinal relations between digital and clinical outcomes and brain volumes, with age, disease duration and sex as covariates.

Results: In PwMS, both sSDMT and SDMT were associated with thalamic volumes and lesion volumes. KD were related to brain, ventricular, thalamic and lesion volumes. No relations were found between s2MWT and MRI volumes. NHPT scores were associated with lesion volumes only, while EDSS and T25FW were not related to MRI. No longitudinal associations were found for any of the outcome measures between M0 and M12.

Conclusion: Our results show clear cross-sectional correlations between digital biomarkers and brain volumes in PwMS, which were not all present for conventional clinical outcomes, supporting the potential added value of digital monitoring tools.

References
1.
Stenager E . A global perspective on the burden of multiple sclerosis. Lancet Neurol. 2019; 18(3):227-228. DOI: 10.1016/S1474-4422(18)30498-8. View

2.
McGinley M, Goldschmidt C, Rae-Grant A . Diagnosis and Treatment of Multiple Sclerosis: A Review. JAMA. 2021; 325(8):765-779. DOI: 10.1001/jama.2020.26858. View

3.
Wattjes M, Ciccarelli O, Reich D, Banwell B, De Stefano N, Enzinger C . 2021 MAGNIMS-CMSC-NAIMS consensus recommendations on the use of MRI in patients with multiple sclerosis. Lancet Neurol. 2021; 20(8):653-670. DOI: 10.1016/S1474-4422(21)00095-8. View

4.
Lublin F, Reingold S, Cohen J, Cutter G, Soelberg Sorensen P, Thompson A . Defining the clinical course of multiple sclerosis: the 2013 revisions. Neurology. 2014; 83(3):278-86. PMC: 4117366. DOI: 10.1212/WNL.0000000000000560. View

5.
Zivadinov R, Jakimovski D, Gandhi S, Ahmed R, Dwyer M, Horakova D . Clinical relevance of brain atrophy assessment in multiple sclerosis. Implications for its use in a clinical routine. Expert Rev Neurother. 2016; 16(7):777-93. DOI: 10.1080/14737175.2016.1181543. View