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Clinical Trial Summary

The proposed study is designed to evaluate the performance of the ALTOIDA™ System as a tool to assist physicians in diagnosing Alzheimer's Disease (AD) in real-world clinical settings. The design of this study is guided by two overriding factors: 1) to optimize the performance of the ALTOIDA™ Neuro Motor Index (NMI) prognosis classifiers, the subjects making up the training sets must be well characterized as to their clinical diagnosis, and 2) all ALTOIDA™ tests must be performed and reproduced in real-world clinical settings. Although there is already a large body of peer-reviewed scientific literature demonstrating that certain digital biomarker patterns are associated with certain neurologic conditions, the utilization of such tools for the evaluation of neurologic disorders is still considered an emerging science and therefore in the investigational stage. Although this protocol will report on brain patterns of certain neurologic conditions such as cognitive impairment and Alzheimer's disease, based on patterns published in peer-reviewed journals, such findings are not considered stand alone or diagnostic per se and should always be considered by the primary physician in conjunction with the patient's clinical condition. These data should only be used as additional information to add to the primary physician's diagnostic impression.


Clinical Trial Description

The goal of the study is to determine relationships among the clinical, cognitive, imaging, genetic, and biochemical biomarker characteristics of the stage of the AD spectrum that precedes MCI, the mildest symptomatic phase of AD, referred to here as MCI. The ADNI-GO model posits that AD begins with amyloid β (Aβ) deposition in the cortex, which leads to synaptic dysfunction, neurodegeneration, and cognitive/ functional decline. It may be possible to determine the future development of ALZ in a preclinical state in a cognitively normal but high risk individual at least 18-24 months before any symptoms develop of cognitive impairment. In addition a newly proposed research framework proposes to use biomarkers for amyloid, tau, and neurodegeneration (ATN) to classify MCI patients. Some of the leading-edge technologies under study are brain-imaging techniques, such as positron emission tomography (PET), including FDG-PET (which measures glucose metabolism in the brain); PET using a radioactive compound (F-AV-45) that measures brain beta-amyloid; and structural MRI. Brain scans are showing scientists how the brain's structure and function change as AD starts and progresses. Biomarkers in cerebrospinal fluid are revealing other changes that could identify which patients with MCI will develop Alzheimer's. Scientists are looking at levels of beta-amyloid and tau in cerebrospinal fluid. (Abnormal amounts of the amyloid and tau proteins in the brain are hallmarks of Alzheimer's disease.) The aim of the study is to evaluate the performance of the ALTOIDA™ System as as a tool to assist physicians in diagnosing Alzheimer's Disease (AD) in real-world clinical settings. The study will be : A. Multi-Center Study: primary goal of this study will be to evaluate the ALTOIDA™ Platform across multiple study locations. This will demonstrate an ability to perform tests, collect data, and generate classifications irrespective of variations in testing locations and personnel. 12 international study sites will be selected with the US based sites being a recognized NIH Center of Excellence for Alzheimer's disease or other nationally recognized Alzheimer's disease research center. Each site will evaluate up to 60 community dwellers evenly divided between MCI patients and age-matched controls (while the prevalence of AD is approximately 12% in the general population, the ratio of AD to normal among those who visit a clinic for memory or cognitive related issues is between 50-60%). Each site will follow the same testing protocols. Participants will be asked if they would like to participate in a protocol that monitors their prospective risk for developing ALZ short term, and whether certain of their prescribed medications may have a protective effect. Those who are accepting to be participants are then enrolled in the study. Enrollees will be tested for risk factors for having pre-clinical ALZ. Individuals identified as being at risk at baseline are followed at 6 month intervals for a 48 month period using psychometric testing and functional neuroimaging. Their maintenance of cognitive stability or cognitive decline is monitored while under the care of their PMD and while taking medications of interest. All test data will be uploaded to the online ALTOIDA™ database server. B. The overall impact of this study will be increased knowledge concerning the sequence and timing of events leading to MCI and from MCI to AD, development of better clinical and Neuro Motor Index prognosis methods for early detection and for monitoring the progression of these conditions, and facilitation of clinical trials of treatments to slow disease progression, ultimately contributing to the prevention of AD. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT02843529
Study type Interventional
Source Altoida
Contact
Status Completed
Phase N/A
Start date October 17, 2016
Completion date February 21, 2020

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