Digital endpoints for self‐administered home‐based functional assessment in pediatric Friedreich’s ataxia

Abstract

Background Friedreich’s ataxia is an inherited, progressive, neurodegenerative disease that typically begins in childhood. Disease severity is commonly assessed with rating scales, such as the modified Friedreich’s Ataxia Rating Scale, which are usually administered in the clinic by a neurology specialist. Objective This study evaluated the utility of home‐based, self‐administered digital endpoints in children with Friedreich’s ataxia and unaffected controls and their relationship to standard clinical rating scales. Methods In a cross‐sectional study with 25 participants (13 with Friedreich’s ataxia and 12 unaffected controls, aged 6–15 years), home‐based digital endpoints that reflect activities of daily living were recorded over 1 week. Domains analyzed were hand motor function with a digitized drawing, automated analysis of speech with a recorded oral diadochokinesis test, and gait and balance with wearable sensors. Results Hand‐drawing and speech tests were easy to conduct and generated high‐quality data. The sensor‐based gait and balance tests suffered from technical limitations in this study setup. Several parameters discriminated between groups or correlated strongly with modified Friedreich’s Ataxia Rating Scale total score and activities of daily living total score in the Friedreich’s ataxia group. Hand‐drawing parameters also strongly correlated with standard 9‐hole peg test scores. Interpretation Deploying digital endpoints in home settings is feasible in this population, results in meaningful and robust data collection, and may allow for frequent sampling over longer periods of time to track disease progression. Care must be taken when training participants, and investigators should consider the complexity of the tasks and equipment used.

Natural History and Real‐World Data in Rare Diseases: Applications, Limitations, and Future Perspectives

“…A new or existing clinical outcome assessment can be used and evaluated in a natural history study to assess change or progression in a particular disease along with its performance and reproducibility for use in a clinical investigation. In addition, natural history studies can be used to assess correlation of COAs; understand minimal clinically important differences; and explore digital end points, such as gait, stride, or other digital functional assessments, as well as digital therapeutics 28–30 …”

“…In addition, natural history studies can be used to assess correlation of COAs; understand minimal clinically important differences; and explore digital end points, such as gait, stride, or other digital functional assessments, as well as digital therapeutics. [28][29][30] Biomarker Development. Identification and validation of robust biomarkers are integral parts of rare disease S41 drug development and even more important for sponsors managing early development portfolio.…”

“…In addition, natural history studies can be used to assess correlation of COAs; understand minimal clinically important differences; and explore digital end points, such as gait, stride, or other digital functional assessments, as well as digital therapeutics. 28 , 29 , 30 …”

Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint

“…Examples of the most advanced clinical applications of multimodal digital data are in Parkinson disease [57][58][59][60] and multiple sclerosis [60,61] with focus on motor function; cognitive decline in Alzheimer disease [62]; and diagnosis of depression [3], Friedreich's ataxia [63], chronic obstructive pulmonary disease [60,64], and COVID-19 [7,65,66]. Interest in multimodal digital measures is also growing among early drug discovery researchers, where personalized medicine approaches can be enabled by capturing longitudinal information on patients behaviors and in real-world settings, sometimes referred to as "digital phenotyping" [67][68][69][70].…”

SARAspeech—Feasibility of automated assessment of ataxic speech disturbance

“…Although impairment of speech strongly contributes to reduced quality of life of ataxia patients 4 , development of objective assessment methods employing computer-assisted voice analysis has only begun. Previous work characterized ataxic speech in distinctive ataxias, differentiated between healthy controls, preataxic and ataxic patients and attempts were made to automate standardized speech tasks [5][6][7] . Given the prominence of speech disturbance in ataxia, computer-assisted analysis of speech allows an objective assessment, including features that are not accessible to the hearing of the human examiner.…”