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Updated: Oct 19, 2026

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
Published on: July 24, 2019
Modeling disease progression among moderate-stage Parkinson's disease patients: A targeted literature review
Amy R Mulick1, Anna M Groß2, Jason Lott3
1Real-World Evidence Center of Excellence, Bayer AG, Müllerstraße 178, Berlin, 13353, Germany.
Background:
Predicting disease progression in Parkinson's disease (PD) is challenging, especially for moderate-stage patients already on dopaminergic therapy. Most models focus on early, untreated PD, but progression rates may differ in moderate-stage PD. Better understanding of these trajectories can improve clinical trial design, access to care, and value demonstration for new therapies that target this population.
Methods:
We conducted a targeted literature review of longitudinal human PD studies in PubMed (inception-December 9, 2024) that quantitatively modeled disease progression, extracting study-, population-, outcome-, and modeling-related details, and qualitatively compared approaches, with an emphasis on moderate-stage PD.
Results:
Of 1717 records, 30 unique studies were reviewed describing 45 statistical models. Seven of these studies describing twelve models included moderate-stage PD; of those that met quality criteria, one allowed for individual-level trajectory prediction for motor, non-motor, and general disease symptoms, while two supported population-level trajectories for non-motor and general disease symptoms. Progression was assessed using diverse outcomes. Models for longitudinal motor fluctuations were lacking.
Conclusions:
Few robust models exist for motor symptom progression in moderate-stage PD. The development of such models requires comprehensive, treated patient datasets, long follow-up, and standardized motor outcome measures. Transparently reported, validated models across diverse groups will aid innovative PD therapy development.
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