Smartphone-based symbol-digit modalities test reliably captures brain damage in multiple sclerosis

Abstract

As the burden of neurodegenerative diseases increases, time-limited clinic encounters do not allow quantification of complex neurological functions. Patient-collected digital biomarkers may remedy this, if they provide reliable information. However, psychometric properties of digital tools remain largely un-assessed. We developed a smartphone adaptation of the cognitive test, the Symbol-Digit Modalities Test (SDMT) by randomizing the test’s symbol-number codes and testing sequences. The smartphone SDMT showed comparable psychometric properties in 154 multiple sclerosis (MS) patients and 39 healthy volunteers (HV). E.g., smartphone SDMT achieved slightly higher correlations with cognitive subscores of neurological examinations and with brain injury measured by MRI (R2 = 0.75, Rho = 0.83, p < 0.0001) than traditional SDMT. Mathematical adjustment for motoric disability of the dominant hand, measured by another smartphone test, compensates for the disadvantage of touch-based test. Averaging granular home measurements of the digital biomarker also increases accuracy of identifying true neurological decline.

A smartphone sensor-based digital outcome assessment of multiple sclerosis

“…The Spearman rho of 0.82 is comparable to the previously reported correlation between other smartphone-based versions of the SDMT and the pen-and-paper version of the SDMT (r = 0.71-0.85). 11,12 In our study, we noted that the e-SDMT scores tended to be lower than the oral SDMT scores in PwMS and HC. This is likely due to the longer time required to select the correct response on a smartphone display compared with saying the correct response out loud.…”

“…Test-retest reliability was consistent with ICCs reported for standard clinical measures in PwMS. 22 As 11,12 upper extremity function, 13 and gait domains, 10 despite differences in test design and features. The active tests and passive monitoring also showed mostly fair correlations with EDSS and respective MSIS-29 subscales and items, indicating that measurements obtained with the Floodlight PoC app agree both with the overall level of MS-related disability and participant's perception of the impact of their disease.…”

“…7 They are also rater-independent, offering more objective measures of functional ability. [8][9][10] In recent years, sensor-based tests have been increasingly used to assess functional ability in MS, [7][8][9][10][11][12][13][14] as well as in Parkinson's disease 15 and Huntington's disease. 16,17 The Floodlight Proof-of-Concept (PoC) app was designed to remotely measure, at home in an unsupervised setting, functional ability in cognitive, upper extremity, and gait and balance domains using a smartphone device without additional hardware.…”

Assessment of Smartphone-Based Spiral Tracing in Multiple Sclerosis Reveals Intra-Individual Reproducibility as a Major Determinant of the Clinical Utility of the Digital Test

“…However, these solutions are useless when the lack of expert medical professionals, limited time for patient encounters, or inability to examine patients in person due to pandemics deprives patients of the benefit of this historically validated tool. Therefore, there is a strong movement to supplement neurological examination or, in some instances, to replace it, by patient-autonomous tests of neurological functions (both cognitive and physical) acquired via smartphones, tablets, or web interphase (6)(7)(8)(9)(10)(11)(12)(13)(14)(15).…”

Intra-individual reproducibility as essential determinant of clinical utility of smartphone-based neurological disability tests

“…Therefore, there is a strong movement to supplement neurological examination or, in some instances, to replace it, by patient-autonomous tests of neurological functions (both cognitive and physical) acquired via smartphones, tablets or web interphase (Balto, Kinnett-Hopkins, & Motl, 2016; Alexandra K. Boukhvalova et al, 2018; Bove et al, 2015; A. Creagh et al, 2020; Erasmus et al, 2001; Longstaff & Heath, 2006; Maillart et al, 2019; Midaglia et al, 2019; Pham et al, 2021; A. Vianello, L. Chittaro, S. Burigat, & R. Budai, 2017).…”