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Objective: Explore endpoints computed from consumer wearable devices that can differentiate patients with Multiple Sclerosis (MS) from matched non-MS patients in everyday life.

Background: Passively collected data from consumer wearable devices (CWD) presents an opportunity to capture patient-relevant outcomes in everyday life. However, clinical relevance and applicability remains to be further explored, as research using CWD data to characterize MS patients in everyday life is lacking. Novel endpoints and/or digital biomarkers for multiple sclerosis have implications for clinical development and treatment of multiple sclerosis.

Design/Methods: From medical claims of a large national insurer, we identified 9,015 individuals with MS and 18,030 age, sex and geography matched controls without MS. Of these, 498 (5.5%) MS and 1,473 (8.2%) non-MS individuals also had wearable devices data that they shared as part of a wellbeing program in which they participated. Several daily summaries of step and sleep data recorded at minute-level granularity were computed and combined with claims and demographic data over one year. Statistical tests for between-group comparisons were controlled for false discovery rate (FDR) which was set at <5%.

Compared to non-MS, MS patients had a lower percentage of days in which they recorded steps and lower mean daily step counts

Results: Compared to non-MS, MS patients had a lower percentage of days in which they recorded steps (73% vs 77%, p-val <0.001) and lower mean daily step counts (6,379 vs 7,188, p-val <0.001). MS patients were less mobile in their least active days: the total step count in the 5th percentile of the daily most-active 6-minute window was significantly lower for them (184.8 vs 221.8, p-val <0.001). While difference in hours slept per night was not significant (6.3 hrs vs 6.5 hrs, p-val NS), we found MS patients took longer to fall asleep (18.6 min vs 13.9 min, p-val <0.001).

Conclusions: Mobility and sleep endpoints computed from CWD significantly differ between MS and non-MS patients. Data collected from CWD could be used for passively assessing quality of life and wellbeing conditions in patients with MS.

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