Parkinson’s Disease Severity at 3 Years Can Be Predicted from Non-Motor Symptoms at Baseline

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Abstract
Objective: The aim of this study is to present a predictive model of PD global severity, measured with the Clinical Impression of Severity Index for Parkinson’s Disease (CISI-PD). Methods: This is an observational, longitudinal study with annual follow-up assessments over three years (four time-points). A multi-level analysis and multiple imputation techniques were performed to generate a predictive model that estimates changes in the CISI-PD at 1, 2 and 3 years. Results: The clinical state of patients (CISI-PD) significantly worsened in the three-year follow-up. However, this change was of small magnitude (effect size: 0.44). The following baseline variables were significant predictors of the global severity change: baseline global severity of disease, levodopa equivalent dose, depression and anxiety symptoms, autonomic dysfunction, and cognitive state. The goodness-of-fit of the model was adequate and the sensitive analysis showed that the data imputation method applied was suitable. Conclusion: Disease progression depends more on the individual’s baseline characteristics than on the three-year time period. Results may contribute to a better understanding of the evolution of PD including the non-motor manifestations of the disease.

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