Study to Identify Clinical, Imaging and Biologic Markers of Parkinson Disease Progression (PPMI)
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|ClinicalTrials.gov Identifier: NCT01141023|
Recruitment Status : Recruiting
First Posted : June 10, 2010
Last Update Posted : August 8, 2017
This is a observational, multi-center study to assess progression of clinical features, imaging and biologic biomarkers in Parkinson disease (PD) patients compared to healthy controls (HC) and in PD patient subtypes.
The primary objective of this study is to identify clinical, imaging and biologic markers of PD progression for use in clinical trials of disease-modifying therapies.
|Condition or disease||Intervention/treatment||Phase|
|Parkinson Disease||Drug: Datscan and AV-133||Phase 2|
PPMI will be a five-year natural history study (a minimum of 3-year involvement for each subject) of de novo idiopathic PD patients and healthy controls. This study will also include a SWEDD (subjects without evidence of dopaminergic deficit)and Prodromal populations.
All subjects will be comprehensively assessed at baseline and every three to six months thereafter. Subjects will undergo clinical (motor, neuropsychiatric and cognitive) and imaging assessments and will donate blood, urine, and cerebral spinal fluid (CSF). A blood sample for DNA will be collected. Data will be collected by each site under uniformly established protocols and data will be analyzed and stored at designated core facilities.
|Study Type :||Interventional (Clinical Trial)|
|Estimated Enrollment :||680 participants|
|Intervention Model:||Single Group Assignment|
|Masking:||None (Open Label)|
|Official Title:||The Parkinson's Progression Markers Initiative (PPMI)|
|Study Start Date :||June 2010|
|Estimated Primary Completion Date :||September 2018|
|Estimated Study Completion Date :||December 2018|
|Experimental: Datscan and AV-133||
Drug: Datscan and AV-133
- The mean rates of change and the variability around the mean of clinical, imaging and biomic outcomes in early PD patients, and the comparison of these rates between PD patient subsets and between PD, SWEDD, Prodromal and healthy subjects. [ Time Frame: Study intervals from 3 months - 36 months ]Specific examples of outcomes include MDS-UPDRS, dopamine transporter striatal uptake, vesicular monoamine transporter type-2 uptake, and serum and CSF alpha-synuclein. PD patient subsets maybe defined by baseline assessments, progression milestones and/or rate of clinical,imaging, or biomic change.
- Comparison between the rates of change in the mean of clinical, imaging and biomic outcomes in early PD patients and between PD and healthy subjects [ Time Frame: Study Intervals from 3 months to 36 months ]
- Prevalence of measures of clinical, imaging and biomic outcomes in early PD patients and healthy subjects. [ Time Frame: from baseline to 36 months. ]
- To establish the predictive value of early clinical non-motor features, baseline imaging and biomic outcomes for future course of disease. [ Time Frame: No time frame needed. ]
- Exploratory analysis of comparison between the rates of change in the mean of clinical, imaging and biomic outcomes in prodromal PD with baseline DaTSCAN binding showing minimal to moderate DAT deficit and early PD patients and healthy subjects. [ Time Frame: Study intervals from 3 months to 36 months ]
- Exploratory analysis of prevalence of measures of clinical, imaging and biomic outcomes in prodromal PD compared to early PD patients and healthy subjects [ Time Frame: Study intervals from baseline to 36 months ]
- To examine the proportion of Prodromal subjects with one or more risk characteristics. [ Time Frame: No Time Frame needed ]To examine the proportion of Prodromal subjects with one or more risk characteristics [hyposmia (<10th percentile by age and gender), RBD, or LRRK2 mutation, and baseline DaTSCAN binding showing minimal to moderate DAT deficit] who phenoconvert within two years. To correlate the baseline DaTSCAN binding with risk of phenoconversion.
- To conduct exploratory analyses to examine whether the progression of clinical, imaging, and biospecimen biomarkers will predict those subjects likely to phenoconvert. [ Time Frame: No Time frame needed ]For example, dopamine transfer loss during the prodromal period either independently or in combination with other biomarkers may provide a quantitative outcome associated with prodromal disease progression to phenoconversion.
- To examine the proportion of SWEDD subjects that have a change in their clinical management at 24 months (SWEDD Clinical Diagnosis and Management Questionnaire). [ Time Frame: No Time Frame Needed ]
- To conduct exploratory analyses in SWEDD subjects to examine the prevalence of measures of clinical, imaging, and biomic outcomes from baseline to 24 months. [ Time Frame: Interval 3 months to 24 months ]Examine the mean rates of change and the variability among these outcomes from 3 months to 24 months, and to examine the correlations between the rates of change in these outcomes from 3 months to 24 months.
- To conduct exploratory analyses to determine whether the measures and change over time in clinical, imaging, and biomic outcomes are similar among the SWEDD, Prodromal, and PD subjects. [ Time Frame: No Time Frame Needed ]
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT01141023
Show 24 Study Locations
|Study Chair:||Kenneth L Marek, MD||Institute for Neurodegenerative Disorders|
|Study Director:||John Q. Trojanowski, MD, PhD||University of Pennsylvania|
|Study Director:||Arthur W. Toga, PhD||University of California, Los Angeles|
|Study Director:||Tatiana Froud, PhD||Indiana University|
|Study Director:||Karl Kieburtz, MD||Clinical Trials Coordination Center|
|Study Director:||Andrew Singleton, PhD||Laboratory of Neurogenetics; National Institute on Aging NIH|
|Study Director:||John P Seibyl, MD||Institute for Neurodegenerative Disorders|
|Study Director:||Christopher Coffey, PhD||Clinical Trials Statistical and Data Management Center, University of Iowa|