Using global statistical tests in long-term Parkinson's disease clinical trials.


Journal Article

Parkinson's disease (PD) impairments are multidimensional, making it difficult to choose a single primary outcome when evaluating treatments to stop or lessen the long-term decline in PD. We review commonly used multivariate statistical methods for assessing a treatment's global impact, and we highlight the novel Global Statistical Test (GST) methodology. We compare the GST to other multivariate approaches using data from two PD trials. In one trial where the treatment showed consistent improvement on all primary and secondary outcomes, the GST was more powerful than other methods in demonstrating significant improvement. In the trial where treatment induced both improvement and deterioration in key outcomes, the GST failed to demonstrate statistical evidence even though other techniques showed significant improvement. Based on the statistical properties of the GST and its relevance to overall treatment benefit, the GST appears particularly well suited for a disease like PD where disability and impairment reflect dysfunction of diverse brain systems and where both disease and treatment side effects impact quality of life. In future long term trials, use of GST for primary statistical analysis would allow the assessment of clinically relevant outcomes rather than the artificial selection of a single primary outcome.

Full Text

Cited Authors

  • Huang, P; Goetz, CG; Woolson, RF; Tilley, B; Kerr, D; Palesch, Y; Elm, J; Ravina, B; Bergmann, KJ; Kieburtz, K; Parkinson Study Group,

Published Date

  • September 2009

Published In

Volume / Issue

  • 24 / 12

Start / End Page

  • 1732 - 1739

PubMed ID

  • 19514076

Pubmed Central ID

  • 19514076

Electronic International Standard Serial Number (EISSN)

  • 1531-8257

International Standard Serial Number (ISSN)

  • 0885-3185

Digital Object Identifier (DOI)

  • 10.1002/mds.22645


  • eng