Replication Data for: Remote monitoring of amyotrophic lateral sclerosis using wearable sensors detects differences in disease progression and survival: a prospective cohort study

DOI

Background: There is an urgent need for objective and more sensitive measures to quantify clinical disease progression and gauge the response to treatment in clinical trials for amyotrophic lateral sclerosis (ALS). Here, we evaluate the ability of a novel accelerometer-derived outcome to detect differential clinical disease progression and assess its longitudinal associations with overall survival in patients with ALS.

Methods: Patients with ALS wore an accelerometer on the hip for 3-7 days, every 2-3 months during a multi-year observation period. An accelerometer-derived outcome, the Vertical Movement Index (VMI), was calculated, together with predicted disease progression rates, and jointly analyzed with overall survival. The clinical utility of VMI was evaluated with comparisons to patient-reported functionality, whereas the impact of various monitoring schemes on empirical power was explored through simulations.

Findings: In total, 97 patients wore the accelerometer for 1,995 days, for a total of 27,701 h. The VMI was highly discriminatory for predicted disease progression rates, revealing faster rates of decline in patients with a worse predicted prognosis compared to those with a better predicted prognosis (p < 0·0001). The VMI was strongly associated with the hazard for death (HR 0·20, 95% CI: 0·09 to 0·44, p = 0.0001), where a decrease of 0·19 to 0·41 unit was associated with reduced ambulatory status. Recommendations for future studies using accelerometry are provided.

Interpretation: The results serve as motivation to incorporate accelerometer-derived outcomes in clinical trials, which will be essential to further validate these markers to meaningful endpoints.

Funding: Stichting ALS Nederland (TRICALS-Reactive-II).

Identifier
DOI https://doi.org/10.34894/QPFHWV
Metadata Access https://dataverse.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34894/QPFHWV
Provenance
Creator van Unnik, Jordi; van Eijk, RPA
Publisher DataverseNL
Contributor van Unnik, JWJ; van Eijk, RPA; Datamanager
Publication Year 2024
Rights info:eu-repo/semantics/openAccess
OpenAccess true
Contact van Unnik, JWJ (UMC Utrecht); van Eijk, RPA (UMC Utrecht); Datamanager (UMC Utrecht)
Representation
Resource Type Dataset
Format application/pdf; text/csv
Size 530214; 767483; 447819; 728677; 75873; 63158
Version 1.0
Discipline Life Sciences; Medicine