Importance of nondopaminergic features in evaluating disease severity of Parkinson disease

The aim of this study was to explore the role of predominantly nondopaminergic (PND) features in evaluating disease severity and progression of Parkinson disease (PD).

Principal component analysis was used on the baseline data of 396 patients to explore consistency of interrelations between important PND domains (cognitive impairment, depressive symptoms, excessive daytime sleepiness, psychotic symptoms, autonomic dysfunction, and postural instability and gait difficulty) across different ranges of disease duration. Hereafter, we evaluated the reliability and validity of a composite score of all PND domains and examined reproducibility of the findings in a large independent cohort.

Principal component analysis revealed a consistent 1-factor solution across groups with different disease durations. Cronbach α of the total group was 0.75 for the PND composite score, and corrected item-total correlations were all above the criterion value of 0.3. Validity of the PND composite score was confirmed by significant positive correlations with Hoehn and Yahr stage, severity of motor symptoms, disease duration, and age. Findings were replicated in the independent cohort.

Our findings show the robustness of a composite score of PND domains as a measure of disease severity across the disease course of PD. Composite measures of PND domains, which largely are insensitive to dopaminergic medication, may provide a more complete and accurate evaluation of disease severity and progression in PD.