Four questions to predict cognitive decline in de novo Parkinson’s disease

Abstract Early identification of cognitive decline (CD) in de novo Parkinson’s disease (PD) is crucial for choosing appropriate therapies and recruiting for clinical trials. However, existing prognostic models lack flexibility, scalability and require costly instrumentation. This study explores the...

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Main Authors: Jan Hlavnička, Josef Mana, Ondrej Bezdicek, Martin Čihák, Filip Havlík, Dominik Škrabal, Tereza Bartošová, Karel Šonka, Evžen Růžička, Petr Dušek
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:npj Parkinson's Disease
Online Access:https://doi.org/10.1038/s41531-025-00958-5
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author Jan Hlavnička
Josef Mana
Ondrej Bezdicek
Martin Čihák
Filip Havlík
Dominik Škrabal
Tereza Bartošová
Karel Šonka
Evžen Růžička
Petr Dušek
author_facet Jan Hlavnička
Josef Mana
Ondrej Bezdicek
Martin Čihák
Filip Havlík
Dominik Škrabal
Tereza Bartošová
Karel Šonka
Evžen Růžička
Petr Dušek
author_sort Jan Hlavnička
collection DOAJ
description Abstract Early identification of cognitive decline (CD) in de novo Parkinson’s disease (PD) is crucial for choosing appropriate therapies and recruiting for clinical trials. However, existing prognostic models lack flexibility, scalability and require costly instrumentation. This study explores the utility of standard clinical questionnaires and criteria to predict CD in de novo PD. A total of 186 patients from the Parkinson Progression Markers Initiative (PPMI) and 48 patients from the Biomarkers of Parkinson’s Disease project (BIO-PD) underwent clinical interviews, comprehensive tests, and questionnaires. A model based only on age of disease onset, history of stroke, history of fainting, and vocalization during dreams predicted CD in 2 and 4-year horizons with an area under curve (AUC) of 70% ± 10% standard deviation (cross-validated PPMI), 79% (overall PPMI), and 78% (validation in BIO-PD). This approach enables rapid preliminary screening using just four simple questions, achieving predictive accuracy comparable to instrumentation-based methods while reducing assessment time.
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spelling doaj-art-583802c14c644d649614cdb0fabfd8bd2025-08-20T03:14:09ZengNature Portfolionpj Parkinson's Disease2373-80572025-04-0111111010.1038/s41531-025-00958-5Four questions to predict cognitive decline in de novo Parkinson’s diseaseJan Hlavnička0Josef Mana1Ondrej Bezdicek2Martin Čihák3Filip Havlík4Dominik Škrabal5Tereza Bartošová6Karel Šonka7Evžen Růžička8Petr Dušek9Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University HospitalDepartment of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University HospitalDepartment of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University HospitalDepartment of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University HospitalDepartment of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University HospitalDepartment of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University HospitalDepartment of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University HospitalDepartment of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University HospitalDepartment of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University HospitalDepartment of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University HospitalAbstract Early identification of cognitive decline (CD) in de novo Parkinson’s disease (PD) is crucial for choosing appropriate therapies and recruiting for clinical trials. However, existing prognostic models lack flexibility, scalability and require costly instrumentation. This study explores the utility of standard clinical questionnaires and criteria to predict CD in de novo PD. A total of 186 patients from the Parkinson Progression Markers Initiative (PPMI) and 48 patients from the Biomarkers of Parkinson’s Disease project (BIO-PD) underwent clinical interviews, comprehensive tests, and questionnaires. A model based only on age of disease onset, history of stroke, history of fainting, and vocalization during dreams predicted CD in 2 and 4-year horizons with an area under curve (AUC) of 70% ± 10% standard deviation (cross-validated PPMI), 79% (overall PPMI), and 78% (validation in BIO-PD). This approach enables rapid preliminary screening using just four simple questions, achieving predictive accuracy comparable to instrumentation-based methods while reducing assessment time.https://doi.org/10.1038/s41531-025-00958-5
spellingShingle Jan Hlavnička
Josef Mana
Ondrej Bezdicek
Martin Čihák
Filip Havlík
Dominik Škrabal
Tereza Bartošová
Karel Šonka
Evžen Růžička
Petr Dušek
Four questions to predict cognitive decline in de novo Parkinson’s disease
npj Parkinson's Disease
title Four questions to predict cognitive decline in de novo Parkinson’s disease
title_full Four questions to predict cognitive decline in de novo Parkinson’s disease
title_fullStr Four questions to predict cognitive decline in de novo Parkinson’s disease
title_full_unstemmed Four questions to predict cognitive decline in de novo Parkinson’s disease
title_short Four questions to predict cognitive decline in de novo Parkinson’s disease
title_sort four questions to predict cognitive decline in de novo parkinson s disease
url https://doi.org/10.1038/s41531-025-00958-5
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