Jorine F van der Heeden1, Johan Marinus, Pablo Martinez-Martin, Jacobus J van Hilten. 1. From the Department of Neurology (J.F.v.d.H., J.M., J.J.v.H.), Leiden University Medical Center, Leiden, the Netherlands; and Alzheimer Center Reina Sofia Foundation and CIBERNED (P.M.-M.), Carlos III Institute of Health, Madrid, Spain.
Abstract
OBJECTIVE: 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). METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
OBJECTIVE: 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). METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
Authors: Laura J de Schipper; Jeroen van der Grond; Johan Marinus; Johanna M L Henselmans; Jacobus J van Hilten Journal: Neuroimage Clin Date: 2017-06-09 Impact factor: 4.881
Authors: Chiara Milanese; César Payán-Gómez; Marta Galvani; Nicolás Molano González; Maria Tresini; Soraya Nait Abdellah; Willeke M C van Roon-Mom; Silvia Figini; Johan Marinus; Jacobus J van Hilten; Pier G Mastroberardino Journal: Mov Disord Date: 2019-05-28 Impact factor: 10.338
Authors: Michael Lawton; Fahd Baig; Michal Rolinski; Claudio Ruffman; Kannan Nithi; Margaret T May; Yoav Ben-Shlomo; Michele T M Hu Journal: J Parkinsons Dis Date: 2015 Impact factor: 5.568