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

Michael Lawton*, Yoav Ben-Shlomo, Margaret T. May, Fahd Baig, Thomas R. Barber, Johannes C. Klein, Diane M.A. Swallow, Naveed Malek, Katherine A. Grosset, Nin Bajaj, Roger A. Barker, Nigel Williams, David J. Burn, Thomas Foltynie, Huw R. Morris, Nicholas W. Wood, Donald G. Grosset, Michele T.M. Hu

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

47 Citations (Scopus)
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Abstract

Objectives
To 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.

Methods
1601 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.

Results
We 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%.

Conclusions
We 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.
Original languageEnglish
Pages (from-to)1279-1287
Number of pages9
JournalJournal of Neurology, Neurosurgery, and Psychiatry
Volume89
Issue number12
Early online date25 Jul 2018
DOIs
Publication statusPublished - Dec 2018

Keywords

  • Parkinson's Disease
  • Cohort studies
  • cluster analysis
  • k-means
  • prognostic studies

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