Developing and validating Parkinson’s disease subtypes and their motor and cognitive progression

ObjectivesTo use a data-driven approach to determine the existence and natural history of subtypes of Parkinson’s disease (PD) using two large independent cohorts of patients newly diagnosed with this condition.Methods1601 and 944 patients with idiopathic PD, from Tracking Parkinson’s and Discovery...

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Bibliographic Details
Published in:Journal of neurology, neurosurgery and psychiatry Vol. 89; no. 12; pp. 1279 - 1287
Main Authors: Lawton, Michael, Ben-Shlomo, Yoav, May, Margaret T, Baig, Fahd, Barber, Thomas R, Klein, Johannes C, Swallow, Diane M A, Malek, Naveed, Grosset, Katherine A, Bajaj, Nin, Barker, Roger A, Williams, Nigel, Burn, David J, Foltynie, Thomas, Morris, Huw R, Wood, Nicholas W, Grosset, Donald G, Hu, Michele T M
Format: Journal Article
Language:English
Published: England BMJ Publishing Group LTD 01.12.2018
BMJ Publishing Group
Series:Research paper
Subjects:
Aged
Biomarkers
Clinical trials
Cluster analysis
Disease Progression
Female
Humans
Levodopa - therapeutic use
Male
Movement Disorders
Neuropsychological Tests
Parkinson Disease - classification
Parkinson Disease - drug therapy
Parkinson's disease
Patients
Prospective Studies
Psychiatric Status Rating Scales
Questionnaires
Severity of Illness Index
Variables
Well being
United Kingdom > UK
ISSN:0022-3050, 1468-330X, 1468-330X
Online Access:Get full text
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Summary:ObjectivesTo use a data-driven approach to determine the existence and natural history of subtypes of Parkinson’s disease (PD) using two large independent cohorts of patients newly diagnosed with this condition.Methods1601 and 944 patients with idiopathic PD, from Tracking Parkinson’s and Discovery cohorts, respectively, were evaluated in motor, cognitive and non-motor domains at the baseline assessment. Patients were recently diagnosed at entry (within 3.5 years of diagnosis) and were followed up every 18 months. We used a factor analysis followed by a k-means cluster analysis, while prognosis was measured using random slope and intercept models.ResultsWe identified four clusters: (1)  fast motor progression with symmetrical motor disease, poor olfaction, cognition and postural hypotension; (2) mild motor and non-motor disease with intermediate motor progression; (3) severe motor disease, poor psychological well-being and  poor sleep with an intermediate motor progression; (4) slow motor progression with tremor-dominant, unilateral disease. Clusters were moderately to substantially stable across the two cohorts (kappa 0.58). Cluster 1 had the fastest motor progression in Tracking Parkinson’s at 3.2 (95% CI 2.8 to 3.6) UPDRS III points per year while cluster 4 had the slowest at 0.6 (0.1–1.1). In Tracking Parkinson’s, cluster 2 had the largest response to levodopa 36.3% and cluster 4 the lowest 28.8%.ConclusionsWe have found four novel clusters that replicated well across two independent early PD cohorts and were associated with levodopa response and motor progression rates. This has potential implications for better understanding disease pathophysiology and the relevance of patient stratification in future clinical trials.
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DGG and MTMH are joint senior authors.
ISSN:0022-3050
1468-330X
1468-330X
DOI:10.1136/jnnp-2018-318337