Predicting Progression in Parkinson's Disease Using Baseline and 1-Year Change Measures

Lana M. Chahine*, Andrew Siderowf, Janel Barnes, Nicholas Seedorff, Chelsea Caspell-Garcia, Tanya Simuni, Christopher S. Coffey, Douglas Galasko, Brit Mollenhauer, Vanessa Arnedo, Nichole Daegele, Mark Frasier, Caroline Tanner, Karl Kieburtz, Kenneth Marek

*Corresponding author for this work

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Improved prediction of Parkinson's disease (PD) progression is needed to support clinical decision-making and to accelerate research trials. Objectives: To examine whether baseline measures and their 1-year change predict longer-term progression in early PD. Methods: Parkinson's Progression Markers Initiative study data were used. Participants had disease duration ≤2 years, abnormal dopamine transporter (DAT) imaging, and were untreated with PD medications. Baseline and 1-year change in clinical, cerebrospinal fluid (CSF), and imaging measures were evaluated as candidate predictors of longer-term (up to 5 years) change in Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) score and DAT specific binding ratios (SBR) using linear mixed-effects models. Results: Among 413 PD participants, median follow-up was 5 years. Change in MDS-UPDRS from year-2 to last follow-up was associated with disease duration (β=0.351; 95% CI=0.146, 0.555), male gender (β=3.090; 95% CI=0.310, 5.869), and baseline (β=-0.199; 95% CI=-0.315, -0.082) and 1-year change (β=0.540; 95% CI=0.423, 0.658) in MDS-UPDRS; predictors in the model accounted for 17.6% of the variance in outcome. Predictors of percent change in mean SBR from year-2 to last follow-up included baseline rapid eye movement sleep behavior disorder score (β=-0.6229; 95% CI=-1.2910, 0.0452), baseline (β=7.232; 95% CI=2.268, 12.195) and 1-year change (β=45.918; 95% CI=35.994,55.843) in mean striatum SBR, and 1-year change in autonomic symptom score (β=-0.325;95% CI=-0.695, 0.045); predictors in the model accounted for 44.1% of the variance. Conclusions: Baseline clinical, CSF, and imaging measures in early PD predicted change in MDS-UPDRS and dopamine-transporter binding, but the predictive value of the models was low. Adding the short-term change of possible predictors improved the predictive value, especially for modeling change in dopamine-transporter binding.

Original languageEnglish (US)
Pages (from-to)665-679
Number of pages15
JournalJournal of Parkinson's disease
Volume9
Issue number4
DOIs
StatePublished - 2019

Keywords

  • Parkinson's disease
  • biomarkers
  • disease progression
  • surrogate endpoint

ASJC Scopus subject areas

  • Clinical Neurology
  • Cellular and Molecular Neuroscience

Fingerprint Dive into the research topics of 'Predicting Progression in Parkinson's Disease Using Baseline and 1-Year Change Measures'. Together they form a unique fingerprint.

  • Cite this

    Chahine, L. M., Siderowf, A., Barnes, J., Seedorff, N., Caspell-Garcia, C., Simuni, T., Coffey, C. S., Galasko, D., Mollenhauer, B., Arnedo, V., Daegele, N., Frasier, M., Tanner, C., Kieburtz, K., & Marek, K. (2019). Predicting Progression in Parkinson's Disease Using Baseline and 1-Year Change Measures. Journal of Parkinson's disease, 9(4), 665-679. https://doi.org/10.3233/JPD-181518