Evaluating the Utility of Smartphone-Based Sensor Assessments in Persons With Multiple Sclerosis in the Real-World Using an App (elevateMS): Observational, Prospective Pilot Digital Health Study.

Abhishek Pratap,Daniel Grant,Larsson Omberg,Ashok Vegesna,Meghasyam Tummalacherla,Lara Mangravite,Stanley Cohan,Chinmay Deshpande

doi:10.2196/22108

Abstract

BackgroundMultiple sclerosis (MS) is a chronic neurodegenerative disease. Current monitoring practices predominantly rely on brief and infrequent assessments, which may not be representative of the real-world patient experience. Smartphone technology provides an opportunity to assess people’s daily-lived experience of MS on a frequent, regular basis outside of episodic clinical evaluations.ObjectiveThe objectives of this study were to evaluate the feasibility and utility of capturing real-world MS-related health data remotely using a smartphone app, “elevateMS,” to investigate the associations between self-reported MS severity and sensor-based active functional tests measurements, and the impact of local weather conditions on disease burden.MethodsThis was a 12-week, observational, digital health study involving 3 cohorts: self-referred participants who reported an MS diagnosis, clinic-referred participants with neurologist-confirmed MS, and participants without MS (controls). Participants downloaded the elevateMS app and completed baseline assessments, including self-reported physical ability (Patient-Determined Disease Steps [PDDS]), as well as longitudinal assessments of quality of life (Quality of Life in Neurological Disorders [Neuro-QoL] Cognitive, Upper Extremity, and Lower Extremity Function) and daily health (MS symptoms, triggers, health, mobility, pain). Participants also completed functional tests (finger-tapping, walk and balance, voice-based Digit Symbol Substitution Test [DSST], and finger-to-nose) as an independent assessment of MS-related cognition and motor activity. Local weather data were collected each time participants completed an active task. Associations between self-reported baseline/longitudinal assessments, functional tests, and weather were evaluated using linear (for cross-sectional data) and mixed-effects (for longitudinal data) regression models.ResultsA total of 660 individuals enrolled in the study; 31 withdrew, 495 had MS (n=359 self-referred, n=136 clinic-referred), and 134 were controls. Participation was highest in clinic-referred versus self-referred participants (median retention: 25.5 vs 7.0 days). The top 5 most common MS symptoms, reported at least once by participants with MS, were fatigue (310/495, 62.6%), weakness (222/495, 44.8%), memory/attention issues (209/495, 42.2%), and difficulty walking (205/495, 41.4%), and the most common triggers were high ambient temperature (259/495, 52.3%), stress (250/495, 50.5%), and late bedtime (221/495, 44.6%). Baseline PDDS was significantly associated with functional test performance in participants with MS (mixed model–based estimate of most significant feature across functional tests [β]: finger-tapping: β=–43.64, P<.001; DSST: β=–5.47, P=.005; walk and balance: β=–.39, P=.001; finger-to-nose: β=.01, P=.01). Longitudinal Neuro-QoL scores were also significantly associated with functional tests (finger-tapping with Upper Extremity Function: β=.40, P<.001; walk and balance with Lower Extremity Function: β=–99.18, P=.02; DSST with Cognitive Function: β=1.60, P=.03). Finally, local temperature was significantly associated with participants’ test performance (finger-tapping: β=–.14, P<.001; DSST: β=–.06, P=.009; finger-to-nose: β=–53.88, P<.001).ConclusionsThe elevateMS study app captured the real-world experience of MS, characterized some MS symptoms, and assessed the impact of environmental factors on symptom severity. Our study provides further evidence that supports smartphone app use to monitor MS with both active assessments and patient-reported measures of disease burden. App-based tracking may provide unique and timely real-world data for clinicians and patients, resulting in improved disease insights and management.

Highlights

Multiple SclerosisMultiple sclerosis (MS) is a chronic neurodegenerative disease that affects more than 2 million people worldwide, with prevalence rates equating to greater than 400,000 cases in the United States [1,2]
Baseline Patient-Determined Disease Steps (PDDS) was significantly associated with functional test performance in participants with MS
Our study provides further evidence that supports smartphone app use to monitor MS with both active assessments and patient-reported measures of disease burden

Summary

Introduction

Multiple SclerosisMultiple sclerosis (MS) is a chronic neurodegenerative disease that affects more than 2 million people worldwide, with prevalence rates equating to greater than 400,000 cases in the United States [1,2]. Routine clinical care for MS typically involves brief assessments performed during infrequent neurologist visits and, often relies on retrospective self-reporting of symptoms and treatment responses, which can be subject to recall bias or affected by MS-associated cognitive impairment [14,15,16,17] As such, this approach may fail to fully capture an individual’s day-to-day experience of living with MS and contribute to reduced accuracy and timeliness in detecting changes in symptom burden, disease severity/relapses, therapeutic outcomes, and the need for timely therapeutic agent change [17,18], while patient-reported outcomes (PROs) are increasingly used in MS clinical care, there is a lack of universal guidance on MS-specific PROs, and their usage and interpretation can differ between individual clinicians [17]. Smartphone technology provides an opportunity to assess people’s daily-lived experience of MS on a frequent, regular basis outside of episodic clinical evaluations

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