Journal article
Predicting Progression in Parkinson's Disease Using Baseline and 1-Year Change Measures
Journal of Parkinson's disease, Vol.9(4), pp.665-679
10/11/2019
DOI: 10.3233/JPD-181518
PMCID: PMC6839498
PMID: 31450510
Abstract
Background: 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.
Details
- Title: Subtitle
- Predicting Progression in Parkinson's Disease Using Baseline and 1-Year Change Measures
- Creators
- Lana M Chahine - University of PennsylvaniaAndrew SiderowfJanel Barnes - University of Iowa, BiostatisticsNicholas SeedorffChelsea Caspell-Garcia - University of IowaTanya SimuniChristopher S Coffey - University of Iowa, BiostatisticsDouglas GalaskoBrit MollenhauerVanessa ArnedoNichole DaegeleMark FrasierCaroline TannerKarl Kieburtz - University of RochesterKenneth MarekThe Parkinson’s Progression Markers Initiative
- Resource Type
- Journal article
- Publication Details
- Journal of Parkinson's disease, Vol.9(4), pp.665-679
- DOI
- 10.3233/JPD-181518
- PMID
- 31450510
- PMCID
- PMC6839498
- NLM abbreviation
- J Parkinsons Dis
- ISSN
- 1877-7171
- eISSN
- 1877-718X
- Language
- English
- Date published
- 10/11/2019
- Academic Unit
- Biostatistics
- Record Identifier
- 9984214948102771
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