King's College London

Research portal

Predict cognitive decline with clinical markers in Parkinson’s disease (PRECODE-1)

Research output: Contribution to journalArticle

Heather Wilson, Gennaro Pagano, Tayyabah Yousaf, Sotirios Polychronis, Rosa De Micco, Beniamino Giordano, Flavia Niccolini, Marios Politis

Original languageEnglish
Pages (from-to)51-59
Number of pages9
JournalJournal of Neural Transmission
Volume127
Issue number1
DOIs
Publication statusPublished - 1 Jan 2020

King's Authors

Research Groups

  • King's College London

Abstract

Over the course of the disease, about 80% of Parkinson’s disease patients will develop cognitive impairment. However, predictive factors associated with cognitive decline are still under investigation. Here, we investigated which clinically available markers are predictive of cognitive impairment in a cohort of early drug-naïve Parkinson’s disease patients. 294 drug-naïve Parkinson’s disease patients, who were cognitively normal at baseline, were recruited from the Parkinson’s Progression Markers Initiative. At 36-month follow-up, patients were diagnosed with cognitive impairment according to two levels: Level 1 diagnosis was defined as MoCA < 26 and Level 2 diagnosis was defined as MoCA < 26, alongside an impaired score on at least two neuropsychological tests. Predictive variables with a validated cut-off were divided into normal or abnormal measures, whilst others were divided into normal or abnormal measures based on the decile with the highest power of prediction. At 3 years’ follow-up, 122/294 Parkinson’s disease (41.5%) patients had cognitive decline. We found that age at Parkinson’s disease onset, MDS-UPDRS Part-III, Hopkin’s Learning Verbal Test-Revised Recall, Semantic Fluency Test and Symbol Digit Modalities Test were all predictors of cognitive decline. Specifically, age at Parkinson’s disease onset, Semantic Fluency Test and symbol Digit Modalities Test were predictors of cognitive decline defined by Level 2. The combination of three abnormal tests, identified as the most significant predictors of cognitive decline, gave a 63.6–86.7% risk of developing cognitive impairment defined by Level 2 and Level 1 criteria, respectively, at 36-month follow-up. Our findings show that these clinically available measures encompass the ability to identify drug-naïve Parkinson’s disease patients with the highest risk of developing cognitive impairment at the earliest stages. Therefore, by implementing this in a clinical setting, we can better monitor and manage patients who are at risk of cognitive decline.

View graph of relations

© 2018 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454