Background – Despite years of research, treatment options remain very limited for patients with amyotrophic lateral sclerosis (ALS). This low productivity in clinical development is partially attributed to the lack of meaningful and sensitive endpoints for ALS clinical trials. Novel digital endpoints enabled by wearable digital health technologies (DHTs) provide objective and continuous measures for tracking ALS progression with minimal patient burden, with great potential to improve and accelerate clinical development.
Methods – ActiGraph GT9X (ActiGraph, Pensacola, FL) placed on non-dominant wrists of 103 patients with ALS and 57 age-matched controls continuously recorded accelerometer data for 7-8 consecutive days. For the ALS group, data were recorded longitudinally (»3 sessions participant separated by 3-4 months). We applied a state-of-the-art algorithm to derive daily measures of gait (step count, cadence [steps per minute], gait speed [meters per second], and distance [meters]). Group differences, association with clinical outcomes (ALSFRS-R), and longitudinal changes were assessed.
Results – We found significantly lower daily averaged step counts (p<0.05), cadence (p<0.05), gait speed (p<0.05), and distance (p<0.05) in ALS. The 95th percentiles of gait speed and cadence were not significantly different between the two groups (p>0.7). Significant differences in daily steps (p<0.05), gait speed (p=0.01), and distance (p<0.05) were observed when patients were sub-categorized into low (<=24), medium (>24 and <=36) and high (>36) functional status based on ALSFRS-R scores. The longitudinal analyses (N=37) showed significant declines in step count (D=-1175.98, p=0.009), gait speed (D=-0.07, p=0.006) and distance (D=-389.02, p=0.021) concurrent with the ALS progression as assessed by ALSFRS total and motor sub-scores.
Conclusion – Wrist-accelerometry can provide rich data to extract objective and sensitive measures of functional gait that reflect meaningful changes in daily life to patients with ALS. These results will inform the use of wearable data as novel clinical endpoints in ongoing and future clinical trials in ALS.