Amyloid Prediction in Early Stage Alzheimer's Disease Through Speech Phenotyping - PAST Extension

NCT ID: NCT04937959

Last Updated: 2022-04-07

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

40 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-01-22

Study Completion Date

2022-08-30

Brief Summary

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The primary objective of the study is to evaluate whether a set of algorithms analysing acoustic and linguistic patterns of speech can detect amyloid-specific cognitive impairment in early stage Alzheimer's disease, based on archival spoken or written language samples, as measured by the area under the curve (AUC) of the receiver operating characteristic curve of the binary classifier distinguishing between amyloid positive and amyloid negative arms. Secondary objectives include (1) evaluating how many years before diagnosis of Mild Cognitive Impairment (MCI) such algorithms work, as measured on binary classifier performance of the classifiers trained to classify MCI vs cognitively normal (CN) arms using archival material from the following time bins before MCI diagnosis: 0-5 years, 5-10 years, 10-15 years, 15-20 years, 20-25 years; (2) evaluating at what age such algorithms can detect later amyloid positivity, as measured on binary classifier performance of the classifiers trained to classify amyloid positive vs amyloid negative arms using archival material from the following age bins: younger than 50, 50-55, 55-60, 65-70, 70-75 years old.

Detailed Description

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Conditions

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Alzheimer Disease Alzheimer's Disease (Incl Subtypes) Preclinical Alzheimer's Disease Prodromal Alzheimer's Disease Mild Cognitive Impairment Normal Cognition

Study Design

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Observational Model Type

CASE_CONTROL

Study Time Perspective

RETROSPECTIVE

Study Groups

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Arm 1: MCI amyloid positive

* Meet the National Institute of Aging - Alzheimer's Association (NIA-AA) core clinical criteria (2011) for MCI due to Alzheimer's
* Positive amyloid PET or amyloid CSF status.
* MMSE 23-30 (inclusive)

No interventions assigned to this group

Arm 2: MCI amyloid negative

* Non-AD Mild Cognitive Impairment (MCI)
* Negative amyloid PET or amyloid CSF status.
* MMSE 23-30 (inclusive)

No interventions assigned to this group

Arm 3: CN amyloid positive

* Absence of a diagnosis of cognitive disorder and/or subjectively reported cognitive decline
* Positive amyloid PET or amyloid CSF status.
* MMSE 26-30 (inclusive)

No interventions assigned to this group

Arm 4: CN amyloid negative

* Absence of a diagnosis of cognitive disorder and/or subjectively reported cognitive decline
* Negative amyloid PET or amyloid CSF status.
* MMSE 26-30 (inclusive)

No interventions assigned to this group

Eligibility Criteria

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Inclusion Criteria

* Subjects are fully eligible for and have completed the AMYPRED-US (Amyloid Prediction in early stage Alzheimer's disease from acoustic and linguistic patterns of speech) study.

(See https://clinicaltrials.gov/ct2/show/NCT04928976)

* Subject has access to audio or written recordings created by them that are available for collection.
* Subject consents to take part in PAST extension study.

Exclusion Criteria

* Subject hasn't completed the full visit day in the AMYPRED-US study.
Minimum Eligible Age

50 Years

Maximum Eligible Age

85 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Novoic Limited

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Emil Fristed, MSc

Role: PRINCIPAL_INVESTIGATOR

Novoic Ltd

Locations

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Syrentis Clinical Research

Santa Ana, California, United States

Site Status RECRUITING

Countries

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United States

Central Contacts

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Head of Clinical Operations

Role: CONTACT

07849522891

Facility Contacts

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Director of Clinical Operations

Role: primary

714-542-3008

Other Identifiers

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NOV-0110-2

Identifier Type: -

Identifier Source: org_study_id

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