Objective: To determine the reliability and validity of a novel, comprehensive digital biomarker remote monitoring approach to actively and passively measure motor symptom progression in Parkinson’s disease (PD).

Background: Clinical assessments necessarily provide only a snapshot of PD patients’ clinical status, which is prone to substantial fluctuation. Remote and frequent symptom monitoring with smartphones and –watches promises to improve the assessment of motor symptom progression in PD and may open new avenues for patient care in the future.

Method: A smartphone application (app) comprised of 10 active tests (tremor, bradykinesia, rigidity/postural stability, cognition) and continuous passive monitoring is deployed in a Phase II study of Prasinezumab (PASADENA) in recently diagnosed PD patients. The current data cut-off is n=205, and results for all 316 patients will be shown at the conference. Sensor features were extracted from each active test and during passive monitoring and aggregated over two-week periods centered at baseline clinical visits. Intra-class correlation coefficients and Spearman correlations quantified test-retest reliability and validity compared to MDS-UPDRS item/subscale scores, respectively.

Results: Average adherence was high with 93% (median) of all possible active tests performed during the first two study weeks. Active test test-retest reliability was high (median 0.95, range 0.90-0.99). All active tests demonstrated strong correlations with MDS-UPDRS scores, ranging = from r=-0.24 (p<0.001; digit symbol) to r=0.61 (p<0.001; rest tremor). Average turn speed during daily life correlated with MDS-UPDRS Part III (r=-0.26, p<0.001) and bradykinesia composite scores (r=-0.34, p<0.001).

Conclusion: These results suggest that a comprehensive remote monitoring approach with smartphones and smartwatches is feasible and provide preliminary evidence of that sensor features are reliable and valid measures of motor symptom severity in recently diagnosed PD patients. The frequent sampling enabled by the remote monitoring approach, coupled with the high sensitivity of smartphone/-watch sensors, promises to increase signal-to-noise in measurements of motor symptom progression in clinical research and, in the future, also routine clinical assessments.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/preliminary-validation-of-a-novel-comprehensive-digital-biomarker-smartphone-application-to-assess-motor-symptoms-in-de-novo-diagnosed-parkinson-patients/