A smartphone sensor-based digital outcome assessment of multiple sclerosis

Abstract

Background: Sensor-based monitoring tools fill a critical gap in multiple sclerosis (MS) research and clinical care. Objective: The aim of this study is to assess performance characteristics of the Floodlight Proof-of-Concept (PoC) app. Methods: 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. Results: 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 ( r = 0.82, p < 0.001), upper extremity function (|r|= 0.40–0.64, all p < 0.001), and gait and balance domains ( r = −0.25 to −0.52, all p < 0.05; except for Static Balance Test: r = −0.20, p > 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. Conclusion: The Floodlight PoC app captures reliable and clinically relevant measures of functional impairment in MS, supporting its potential use in clinical research and practice.

Practice Effects of Mobile Tests of Cognition, Dexterity, and Mobility on Patients With Multiple Sclerosis: Data Analysis of a Smartphone-Based Observational Study

“…We used publicly available data from the Floodlight Open study, which collects smartphone-based test data from self-declared persons with MS with a number of different tests implemented in the Floodlight Open app [ 22 ]. The study is the successor of a small, closed feasibility study [ 9 , 17 ], and the data are openly available to researchers [ 23 ]. Currently, several phase 3 studies are using variations of the Floodlight app as part of their test batteries, for example, the CONSONANCE trial, a single-arm interventional trial evaluating ocrelizumab treatment in participants with progressive MS (NCT03523858) [ 17 ].…”

“…Wearable technologies, such as smartphones and smartwatches, are expected to capture more representative data at a higher resolution not only in the patients’ natural environments in MS but also in other neurological diseases such as Parkinson disease and Huntington disease [ 9 - 11 ]. Data can be collected passively during the patient’s everyday activities (eg, capturing step counts, turn speed, or keyboard dexterity [ 9 , 12 , 13 ]) or actively during specific functional tests [ 14 - 16 ]. They can possibly improve both clinical trials by providing more sensitive outcome measures and clinical practice by allowing more personalized disease course monitoring [ 14 , 17 ].…”

Digital Biomarkers in Multiple Sclerosis

“…Apps such as Floodlight (Roche, Switzerland), Konectom (TM) (Biogen, Cambridge, MA, USA), MSCopilot ® (Ad Scientiam, Paris, France) or MS Sherpa (Orikami, Nijmegen, The Netherlands), some of which are still in evaluation and only used in research, collect data regarding mobility (2or 6-min-walk, U-turns, standing still: distance, speed, balance, etc. ), cognition (matching symbols: cognitive processing speed), hand motor function (squeezing objects, drawing lines: coordination, pressure, speed and accuracy of hand and finger movement) and mood (questionnaires), or leaving options for patients to make notes [149][150][151][152]. The benefit of such apps lies in the collection of data from daily life, the possibility to perform functional tests independent of clinical visits, enabling patients to use them for self-evaluation or in cases where they feel as though they are experiencing a worsening of symptoms and, of course, for pwMS and treating neurologists in order to include these data in therapy decisions as well.…”

“…The implementation of such apps could overcome the challenge of often infrequent and rare clinic visits and capture all, sometimes daily, even subtle symptom changes. Thus, a more accurate monitoring of the individual disease course and associated optimized therapeutic decisions becomes achievable [66,148,150]. Furthermore, daily patient self-made tasks via a smartphone may contribute to more disease responsibility and informed discussions in clinical visits about subsequent therapeutic steps.…”

Charting a global research strategy for progressive MS—An international progressive MS Alliance proposal

“…While still in the early stages, recent work demonstrated that an app-based tool-Floodlight PoC-along with a smartwatch accurately captured reliable and clinically relevant measures of functional impairment in MS, in this area points to a future where ubiquitous digital tools could be leveraged to enhance research and clinical care. 82,83 Finally, the ongoing challenge of phenotypic classification of the disease continues to impact clinical trials of progressive MS agents. This challenge introduced a measure of confusion due to the differing applications of the 2013 clinical course descriptors used in the review and approval of ocrelizumab and siponimod by both the US Food and Drug Administration (FDA) and the European Medicines Agency and compounded by the FDA's retroactively expanding approval of agents for RMS to include active SPMS.…”