biostudies-literatureUnknown28(4)Montalban X<h4>Background</h4>Sensor-based monitoring tools fill a critical gap in multiple sclerosis (MS) research and clinical care.<h4>Objective</h4>The aim of this study is to assess performance characteristics of the Floodlight Proof-of-Concept (PoC) app.<h4>Methods</h4>In a 24-week study (clinicaltrials.gov: NCT02952911), smartphone-based active tests and passive monitoring assessed cognition (electronic Symbol Digit Modalities Test), upper extremity function (Pinching Test, Draw a Shape Test), and gait and balance (Static Balance Test, U-Turn Test, Walk Test, Passive Monitoring). Intraclass correlation coefficients (ICCs) and age- or sex-adjusted Spearman's rank correlation determined test-retest reliability and correlations with clinical and magnetic resonance imaging (MRI) outcome measures, respectively.<h4>Results</h4>Seventy-six people with MS (PwMS) and 25 healthy controls were enrolled. In PwMS, ICCs were moderate-to-good (ICC(2,1) = 0.61-0.85) across tests. Correlations with domain-specific standard clinical disability measures were significant for all tests in the cognitive (<i>r</i> = 0.82, <i>p</i> < 0.001), upper extremity function (|r|= 0.40-0.64, all <i>p</i> < 0.001), and gait and balance domains (<i>r</i> = -0.25 to -0.52, all <i>p</i> < 0.05; except for Static Balance Test: <i>r</i> = -0.20, <i>p</i> > 0.05). Most tests also correlated with Expanded Disability Status Scale, 29-item Multiple Sclerosis Impact Scale items or subscales, and/or normalized brain volume.<h4>Conclusion</h4>The Floodlight PoC app captures reliable and clinically relevant measures of functional impairment in MS, supporting its potential use in clinical research and practice.Multiple sclerosis (Houndmills, Basingstoke, England)654-664https://www.ebi.ac.uk/biostudies/studies/S-EPMC8961252biostudies-literatureA smartphone sensor-based digital outcome assessment of multiple sclerosis.PMC8961252Belachew SMidaglia LMulero PGossens CGanzetti MScotland ALipsmeier FJulian LBaker MLindemann MSchadrack JGraves JMontalban XBernasconi CHauser SLvan Beek JfalseA smartphone sensor-based digital outcome assessment of multiple sclerosis.<h4>Background</h4>Sensor-based monitoring tools fill a critical gap in multiple sclerosis (MS) research and clinical care.<h4>Objective</h4>The aim of this study is to assess performance characteristics of the Floodlight Proof-of-Concept (PoC) app.<h4>Methods</h4>In a 24-week study (clinicaltrials.gov: NCT02952911), smartphone-based active tests and passive monitoring assessed cognition (electronic Symbol Digit Modalities Test), upper extremity function (Pinching Test, Draw a Shape Test), and gait and balance (Static Balance Test, U-Turn Test, Walk Test, Passive Monitoring). Intraclass correlation coefficients (ICCs) and age- or sex-adjusted Spearman's rank correlation determined test-retest reliability and correlations with clinical and magnetic resonance imaging (MRI) outcome measures, respectively.<h4>Results</h4>Seventy-six people with MS (PwMS) and 25 healthy controls were enrolled. In PwMS, ICCs were moderate-to-good (ICC(2,1) = 0.61-0.85) across tests. Correlations with domain-specific standard clinical disability measures were significant for all tests in the cognitive (<i>r</i> = 0.82, <i>p</i> < 0.001), upper extremity function (|r|= 0.40-0.64, all <i>p</i> < 0.001), and gait and balance domains (<i>r</i> = -0.25 to -0.52, all <i>p</i> < 0.05; except for Static Balance Test: <i>r</i> = -0.20, <i>p</i> > 0.05). Most tests also correlated with Expanded Disability Status Scale, 29-item Multiple Sclerosis Impact Scale items or subscales, and/or normalized brain volume.<h4>Conclusion</h4>The Floodlight PoC app captures reliable and clinically relevant measures of functional impairment in MS, supporting its potential use in clinical research and practice.2022-01-01T00:00:00Z2022 Apr2024-11-09T07:54:09.168Z2024-11-09T07:54:09.168ZS-EPMC89612523425958810.1177/13524585211028561