A major goal of the neuroscience community is to develop treatment strategies that will slow or forestall the progression of Parkinson's disease (PD). PD is one of the most common adult neurodegenerative disorders, affecting over 1 million people in North America and the European Union. As a first step, based on futility studies, the NINDS Exploratory Trials in Parkinson's disease (NET-PD) network identified creatine as a potential agent to slow clinical decline in PD. The NET-PD network is now conducting a large long term Phase III trial (LS-1) comparing creatine to placebo. During the renewal period the Statistical Coordination Center (SCC) proposes to complete the following specific aims in conjunction with the Clinical Coordination Center (CCC) and Clinical Sites in order to continue and complete LS1:
Aim1 Test the hypothesis that daily administration of creatine (10gm/day) is more effective than placebo in slowing clinical decline in PD between baseline and the 5 year follow-up visit against the background of dopaminergic therapy and best PD care. Given that PD is a multi-factorial disease that contributes to cognitive, motor, and behavioral disability, a gloal outcome measure of clinical decline analyzed by Global Statistical Test is utilized to provide sensitivity in detecting subtle overall changes in disease state;
Aim 2 Test a set of secondary hypotheses to provide insight into the primary results;
Aim 3 Continue as the SCC and (a) prepare interim reports for the CCC on performance of the Clinical Sites including retention, patient safety (blinded), and data quality;and (b) participate in the solution of problems with retention;
Aim 4 Continue to (a) minimize bias and protect blinding during the entire project, (b) adjudicate outcome measures relating to efficacy and safety (as needed), and (c) provide periodic reports and interim analyses to the Data and Safety Monitoring Board (DSMB);
Aim 5 In collaboration with the CCC and Clinical Sites (a) interpret and report results, and (b) document and archive the data in a publically available database.
Aim 6 Maintain an administrative structure that allows close collaboration with the CCC, the clinical centers, NINDS Scientific Program personnel, the DSMB, and the NIH Oversight Board.
The accumulated disability that PD causes is a major source of diminished quality of life and increased health care costs. Despite the advances in our understanding of the pathophysiology in PD, there are no current therapies that slow the inexorable clinical decline. The LS1 trial will help to determine if creatine can slow clinical decline and provide better information on the course of early PD than is currently available. Disclaimer: Please note that the following critiques were prepared by the reviewers prior to the Study Section meeting and are provided in an essentially unedited form. While there is opportunity for the reviewers to update or revise their written evaluation, based upon the group's discussion, there is no guarantee that individual critiques have been updated subsequent to the discussion at the meeting. Therefore, the critiques may not fully reflect the final opinions of th individual reviewers at the close of group discussion or the final majority opinion of the group. Thus the Resume and Summary of Discussion is the final word on what the reviewers actually considered critical at the meeting.
|Lin, Li-An; Luo, Sheng; Davis, Barry R (2018) Bayesian regression model for recurrent event data with event-varying covariate effects and event effect. J Appl Stat 45:1260-1276|
|Yang, Chengwu; Vrana, Kent E (2018) Rescuing Suboptimal Patient-Reported Outcome Instrument Data in Clinical Trials: A New Strategy. Healthcare (Basel) 6:|
|Zhu, Huirong; DeSantis, Stacia M; Luo, Sheng (2018) Joint modeling of longitudinal zero-inflated count and time-to-event data: A Bayesian perspective. Stat Methods Med Res 27:1258-1270|
|Luthra, Nijee S; Kim, Soeun; Zhang, Yunxi et al. (2018) Characterization of vitamin D supplementation and clinical outcomes in a large cohort of early Parkinson's disease. J Clin Mov Disord 5:7|
|Li, Kan; O'Brien, Richard; Lutz, Michael et al. (2018) A prognostic model of Alzheimer's disease relying on multiple longitudinal measures and time-to-event data. Alzheimers Dement 14:644-651|
|Chen, Geng; Luo, Sheng (2018) Bayesian Hierarchical Joint Modeling Using Skew-Normal/Independent Distributions. Commun Stat Simul Comput 47:1420-1438|
|Luo, Sheng; Liu, Yuanyuan; Teresi, Jeanne A et al. (2017) Differential item functioning in the Unified Dyskinesia Rating Scale (UDysRS). Mov Disord 32:1244-1249|
|Chou, Kelvin L; Elm, Jordan J; Wielinski, Catherine L et al. (2017) Factors associated with falling in early, treated Parkinson's disease: The NET-PD LS1 cohort. J Neurol Sci 377:137-143|
|Li, Kan; Furr-Stimming, Erin; Paulsen, Jane S et al. (2017) Dynamic Prediction of Motor Diagnosis in Huntington's Disease Using a Joint Modeling Approach. J Huntingtons Dis 6:127-137|
|Lin, Li-An; Luo, Sheng; Chen, Bingshu E et al. (2017) Bayesian analysis of multi-type recurrent events and dependent termination with nonparametric covariate functions. Stat Methods Med Res 26:2869-2884|
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