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The PREVENTION Trial: Precision Recommendations to Optimize Neurocognition

Saint John's Cancer Institute · 2019
ClinicalTrials.gov · Datasets · License: Public Domain · 2019
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alzheimer-diseasecognitive-declinemild-cognitive-impairmentnapersonalprecision-medicine
The PREVENTION Trial is a 12-month, two-arm randomized clinical trial (RCT) in adults 50-80 years old experiencing cognitive decline. Our study clinicians will refer patients for enrollment based on three categories: 1) a diagnosis of mild AD according to criteria established by the National Institute of Neurological and Communicative Disorders and Stroke (AD and Related Disorders Association \[NINCDS-ADRDA\]), 2) those with mild cognitive impairment will be diagnosed according to the Petersen method, and 3) subjective memory impairment as assessed by neuropsychological assessments and self-report. Enrollment will require evidence of AD pathophysiological processes (as defined by a positive amyloid positron emission tomography (PET) scan). The first objective is to evaluate the efficacy of a coached, data-driven, multi-modal lifestyle intervention to treat cognitive decline. Subjects will be randomized into one of two groups: Group 1 (Active Control) or Group 2 (Intervention). Group 1 (Data-driven clinical recommendations (CR)) will serve as the active control group and will receive data-driven clinical recommendations by a study physician based on study assessments and clinical lab values. Group 2 (Data-driven multi-modal intervention with coaching (MMIC)) will receive the same clinical recommendations and also an intensive multi-modal intervention with health coaching, support and resources to carry out these recommendations. This includes health coaching sessions (with an RDN), dietary counseling sessions (with an RDN), and group cognitive and physical exercise classes (CogFit) with a certified personal trainer and a computer-based neurocognitive program at home. Both groups will be measured for treatment related changes in cognitive and functional abilities, quality of life, biological, and biochemical measures. The second objective is to analyze longitudinal multi-omic data, including metabolomics, proteomics, genetics, microbiome, behavior and cognition into
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