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Published VersionCC BY V4.0, Open Access
CorrectionCC BY V4.0, Open Access
Journal article
Parkinson’s disease prognostic scores for progression of cognitive decline
Scientific Reports, Vol.9, 17485
2019
Abstract
Clinical and biochemical diversity of Parkinson's disease (PD) presents a major challenge for accurate diagnosis and prediction of its progression. We propose, develop and optimize PD clinical scores as efficient integrated progression biomarkers for prediction of the likely rate of cognitive decline in PD patients. We considered 269 drug-naïve participants from the Parkinson's Progression Marker Initiative database, diagnosed with idiopathic PD and observed between 4 and 6 years. Nineteen baseline clinical and pathological measures were systematically considered. Relative variable importance and logistic regressions were used to optimize combinations of significant baseline measures as integrated biomarkers. Parkinson's disease cognitive decline scores were designed as new clinical biomarkers using optimally categorized baseline measures. Specificities and sensitivities of the biomarkers reached ~93% for prediction of severe rate of cognitive decline (with more than 5 points decline in 4 years on the Montreal Cognitive Assessment scale), and up to ~73% for mild-to-moderate decline (between 1 and 5 points decline). The developed biomarkers and clinical scores could resolve the long-standing clinical problem about reliable prediction of PD progression into cognitive deterioration. The outcomes also provide insights into the contributions of individual clinical and pathological measures to PD progression, and will assist with better-targeted treatment regiments, stratification of clinical trial and their evaluation.
Details
- Title
- Parkinson’s disease prognostic scores for progression of cognitive decline
- Authors
- Galina Gramotnev (Author) - Research and Data Analysis CentreDmitri K Gramotnev (Author) - Research and Data Analysis CentreAlexandra Gramotnev (Author) - University of the Sunshine Coast
- Publication details
- Scientific Reports, Vol.9, 17485
- Publisher
- Nature Publishing Group
- Date published
- 2019
- DOI
- 10.1038/s41598-019-54029-w
- ISSN
- 2045-2322
- Copyright note
- Copyright © The Author(s) 2019. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
- Organisation Unit
- University of the Sunshine Coast, Queensland
- Language
- English
- Record Identifier
- 99451124202621
- Output Type
- Journal article
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