Clinical patterns in Parkinson's disease

Abstract

The clinical heterogeneity of Parkinson__s disease (PD) patients may reflect the existence of subtypes of the disease. PD subtypes have often been defined by a classification according to researcher-specified criteria, such as age-at-onset or predominant clinical motor features. The general objective of this thesis was to identify and characterize clinical subtypes in PD by a data-driven approach, based on a comprehensive assessment of all relevant PD domains. In order to obtain insight in the associations and coherence of impairments that are involved in the disease, we evaluated the contributions of impairment and disability domains to health-related quality of life in patients with PD. Subsequently, the data of the PROPARK cohort was used to study coherency patterns within the motor domain and in the spectrum of motor and nonmotor domains. In our study on subtypes, first, we systematically evaluated the result s of earlier studies that performed cluster analysis to identify subtypes in PD, after which we applied cluster analysis on data of the PROPARK cohort in order to identify subtypes of the disease