Impacts on study design when implementing digital measures in Parkinson's disease-modifying therapy trials

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.