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Trial details imported from ClinicalTrials.gov
For full trial details, please see the original record at
https://clinicaltrials.gov/ct2/show/NCT05194787
Registration number
NCT05194787
Ethics application status
Date submitted
29/12/2021
Date registered
18/01/2022
Date last updated
30/10/2023
Titles & IDs
Public title
TAS Test: Online Motor-cognitive Tests for Early Detection of Alzheimer's Disease
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Scientific title
TAS Test: Determining the Feasibility and Validity of Online Motor-cognitive Testing for Early Detection of Alzheimer's Disease
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Secondary ID [1]
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H0021660
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Universal Trial Number (UTN)
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Trial acronym
TASTest
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Linked study record
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Health condition
Health condition(s) or problem(s) studied:
Alzheimer Disease
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Dementia
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Age-related Cognitive Decline
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Condition category
Condition code
Neurological
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Alzheimer's disease
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Neurological
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Dementias
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Mental Health
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Other mental health disorders
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Intervention/exposure
Study type
Observational
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Patient registry
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Target follow-up duration
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Target follow-up type
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Description of intervention(s) / exposure
Diagnosis / Prognosis - Cognitive test scores, clinical diagnosis and blood biomarkers
Diagnosis / Prognosis: Cognitive test scores, clinical diagnosis and blood biomarkers
Clinical diagnosis of Alzheimer's disease, mild cognitive impairment or normal ageing.
Cognitive test score on CANTAB Blood biomarker (p-tau 181) level
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Intervention code [1]
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Diagnosis / Prognosis
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Comparator / control treatment
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Control group
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Outcomes
Primary outcome [1]
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Develop and validate the optimal TAS Test protocol to detect pre-AD (p-tau 181 positivity)
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Assessment method [1]
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Receiver Operating Characteristic (ROC) curves will be plotted against the positive p-tau181 cut-off to assess the sensitivity/specificity of TAS Test models to identify the pre-AD stage.
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Timepoint [1]
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3 years
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Primary outcome [2]
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Prospectively validate TAS Test to predict risks of cognitive decline
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Assessment method [2]
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Assess the sensitivity and specificity of TAS Test to predict cognitive trajectories (CANTAB scores) "stable" and "declining" using ROC curve analysis.
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Timepoint [2]
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5 years
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Primary outcome [3]
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Prospectively validate TAS Test to predict risks of AD diagnosis
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Assessment method [3]
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Multinomial logistic regression will estimate the (covariate adjusted) log-odds of being in each diagnostic category (AD, MCI and normal) at 5 years as predicted by baseline TAS Test results.
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Timepoint [3]
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5 years
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Eligibility
Key inclusion criteria
> 50years old
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Minimum age
50
Years
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Maximum age
No limit
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Sex
Both males and females
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Can healthy volunteers participate?
Yes
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Key exclusion criteria
established diagnosis of dementia
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Study design
Purpose
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Duration
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Selection
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Timing
Prospective
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Statistical methods / analysis
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Recruitment
Recruitment status
Recruiting
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Data analysis
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Reason for early stopping/withdrawal
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Other reasons
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Date of first participant enrolment
Anticipated
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Actual
5/03/2021
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Date of last participant enrolment
Anticipated
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Actual
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Date of last data collection
Anticipated
1/12/2030
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Actual
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Sample size
Target
3000
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Accrual to date
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Final
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Recruitment in Australia
Recruitment state(s)
TAS
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Recruitment hospital [1]
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University of Tasmania - Hobart
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Recruitment postcode(s) [1]
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7001 - Hobart
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Funding & Sponsors
Primary sponsor type
Other
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Name
University of Tasmania
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Address
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Country
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Other collaborator category [1]
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Other
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Name [1]
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National Health and Medical Research Council, Australia
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Address [1]
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Country [1]
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Other collaborator category [2]
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Other
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Name [2]
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University of Sydney
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Address [2]
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Other collaborator category [3]
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Other
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Name [3]
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University of Leeds
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Address [3]
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Country [3]
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Ethics approval
Ethics application status
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Summary
Brief summary
Global dementia prevalence is rising. Alzheimer's disease (AD), the most common cause, has
devastating effects on people's quality of life. AD has a preclinical (pre-AD) period of
10-20 years when brain pathology silently progresses before any cognitive symptoms appear.
Current tests for pre-AD are invasive, costly and unsuitable for screening at population
level. Similar to screening for pre-diabetes and carcinoma in situ, it is important to detect
AD at the preclinical stage in order to offer early interventions before the pathology
progresses to the irrerversible degenerative stage. In the study, research will develop a new
scalable test (TAS Test) by combining two innovative ideas: hand-movement tests to detect
pre-AD >10 years before cognitive symptoms begin; and computer vision so people can
"self-test" online using home computers. This unique approach builds on recent discoveries
that hand-movement patterns change in pre-AD. The research team will use exquisitely precise
computer vision methods to automatically analyse movement data from thousands of
participants, and combine this with machine learning of overall motor-cognitive performance.
The project team has access to 3 well-phenotyped cohorts, >10,000 existing participants and a
cutting-edge assay for a blood AD biomarker, ptau181. The research team will develop a TAS
Test algorithm to classify hand-movement and cognitive test data for pre-AD risk (p-taua181
levels) and determine TAS Test's precision to prospectively predict 5-year risks of cognitive
decline and AD.
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Trial website
https://clinicaltrials.gov/ct2/show/NCT05194787
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Trial related presentations / publications
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Public notes
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Contacts
Principal investigator
Name
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Prof Vickers, PhD DSc
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Address
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University of Tasmania
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Phone
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Fax
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Email
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Contact person for public queries
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A/Prof Alty, MD FRACP
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Address
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Phone
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+61 (0)3 36226 4273
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Fax
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Email
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[email protected]
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Contact person for scientific queries
Summary Results
For IPD and results data, please see
https://clinicaltrials.gov/ct2/show/NCT05194787
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