Related Experiment Video
Updated: Jun 9, 2025
Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
Published on: July 24, 2019
Impacts on study design when implementing digital measures in Parkinson's disease-modifying therapy trials
Jennie S Lavine1, Anthony D Scotina1, Seth Haney1
1Research & Development, Koneksa Health, New York, NY, United States.
Introduction:
Parkinson's Disease affects over 8.5 million people and there are currently no medications approved to treat underlying disease. Clinical trials for disease modifying therapies (DMT) are hampered by a lack of sufficiently sensitive measures to detect treatment effect. Reliable digital assessments of motor function allow for frequent at-home measurements that may be able to sensitively detect disease progression.
Methods:
Here, we estimate the test-retest reliability of a suite of at-home motor measures derived from raw triaxial accelerometry data collected from 44 participants (21 with confirmed PD) and use the estimates to simulate digital measures in DMT trials. We consider three schedules of assessments and fit linear mixed models to the simulated data to determine whether a treatment effect can be detected.
Results:
We find at-home measures vary in reliability; many have ICCs as high as or higher than MDS-UPDRS part III total score. Compared with quarterly in-clinic assessments, frequent at-home measures reduce the sample size needed to detect a 30% reduction in disease progression from over 300 per study arm to 150 or less than 100 for bursts and evenly spaced at-home assessments, respectively. The results regarding superiority of at-home assessments for detecting change over time are robust to relaxing assumptions regarding the responsiveness to disease progression and variability in progression rates.
Discussion:
Overall, at-home measures have a favorable reliability profile for sensitive detection of treatment effects in DMT trials. Future work is needed to better understand the causes of variability in PD progression and identify the most appropriate statistical methods for effect detection.
Insights
Digital at-home motor assessments show high reliability for Parkinson's Disease clinical trials. These frequent measurements significantly reduce the sample size needed to detect treatment effects in disease-modifying therapies.
Area of Science:
- Neurology
- Biomedical Engineering
- Clinical Trials
Background:
- Parkinson's Disease (PD) impacts over 8.5 million individuals globally.
- Current treatments for PD do not address the underlying disease.
- Clinical trials for disease-modifying therapies (DMTs) require sensitive outcome measures to detect treatment efficacy.
Purpose of the Study:
- To estimate the test-retest reliability of at-home motor function assessments using accelerometry data.
- To simulate digital measures in DMT trials to assess their sensitivity in detecting treatment effects.
- To compare the efficiency of at-home assessments with traditional in-clinic evaluations.
Main Methods:
- Collected triaxial accelerometry data from 44 participants (21 with PD).
- Estimated reliability of various at-home motor measures.
- Simulated digital measures in DMT trials using three assessment schedules.
- Fitted linear mixed models to simulated data to detect treatment effects.
Main Results:
- At-home motor measures demonstrated variable but often high reliability, with some exceeding the MDS-UPDRS Part III total score.
- Frequent at-home assessments substantially reduced required sample sizes for detecting disease progression compared to quarterly in-clinic assessments.
- At-home assessments proved superior for detecting change over time, even with relaxed assumptions on disease progression variability.
Conclusions:
- At-home digital motor assessments possess a favorable reliability profile for sensitive detection of treatment effects in Parkinson's Disease DMT trials.
- Further research is necessary to understand PD progression variability and optimize statistical methods for effect detection.
