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

A Study to Evaluate the Ability of Speech- and Language-based Digital Biomarkers to Detect and Characterise Prodromal and Preclinical Alzheimer's Disease in a Clinical Setting - AMYPRED-US PAST Extension Study

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.

Study Overview

• Status: Recruiting
• Conditions: Alzheimer Disease; Mild Cognitive Impairment; Prodromal Alzheimer's Disease; Alzheimer's Disease (Incl Subtypes); Preclinical Alzheimer's Disease; Normal Cognition

• Study Type: Observational
• Enrollment (Anticipated): 40

Contacts and Locations

Study Locations

• United States
  • California
    • Santa Ana, California, United States, 92705
      • Recruiting
      • Syrentis Clinical Research

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 50 years to 85 years (ADULT, OLDER_ADULT)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

Participants will be identified from participants of the AMYPRED-US study.

Description

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.

Study Plan

How is the study designed?

Number of groups / cohorts

4

Cohorts and Interventions

Group / Cohort
Arm 2: MCI amyloid negative; Non-AD Mild Cognitive Impairment (MCI); Negative amyloid PET or amyloid CSF status.; MMSE 23-30 (inclusive)
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)
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)
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)

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The area under the curve (AUC) of the receiver operating characteristic (ROC) curve of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) arms.	Using archival spoken or written language samples as input.	Up to 85 years

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The sensitivity of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) arms using archival spoken or written language samples as input.		Up to 85 years
The specificity of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) arms using archival spoken or written language samples as input.		Up to 85 years
The Cohen's kappa of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) arms using archival spoken or written language samples as input.		Up to 85 years
The AUC of the binary classifiers distinguishing between MCI and cognitively normal (CN) arms.	Using archival spoken or written language samples as input in the following bins: 0-5 years, 5-10 years, 10-15 years, 15-20 years, 20-25 years before MCI diagnosis.	Up to 85 years
The sensitivity of the binary classifiers distinguishing between MCI and cognitively normal (CN) arms.	Using archival spoken or written language samples as input in the following bins: 0-5 years, 5-10 years, 10-15 years, 15-20 years, 20-25 years before MCI diagnosis.	Up to 85 years
The specificity of the binary classifiers distinguishing between MCI and cognitively normal (CN) arms.	Using archival spoken or written language samples as input in the following bins: 0-5 years, 5-10 years, 10-15 years, 15-20 years, 20-25 years before MCI diagnosis.	Up to 85 years
The Cohen's kappa of the binary classifiers distinguishing between MCI and cognitively normal (CN) arms.	Using archival spoken or written language samples as input in the following bins: 0-5 years, 5-10 years, 10-15 years, 15-20 years, 20-25 years before MCI diagnosis.	Up to 85 years
The AUC of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) arms.	Using archival spoken or written language samples as input in the following bins: younger than 50, 50-55, 55-60, 65-70, 70-75 years old.	Up to 85 years
The sensitivity of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) arms.	Using archival spoken or written language samples as input in the following bins: younger than 50, 50-55, 55-60, 65-70, 70-75 years old.	Up to 85 years
The specificity of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) arms.	Using archival spoken or written language samples as input in the following bins: younger than 50, 50-55, 55-60, 65-70, 70-75 years old.	Up to 85 years
The Cohen's kappa of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) arms.	Using archival spoken or written language samples as input in the following bins: younger than 50, 50-55, 55-60, 65-70, 70-75 years old.	Up to 85 years

Collaborators and Investigators

• Sponsor: Novoic Limited

Study record dates

Study Major Dates

• Study Start (ACTUAL): January 22, 2021
• Primary Completion (ANTICIPATED): August 30, 2022
• Study Completion (ANTICIPATED): August 30, 2022

Study Registration Dates

• First Submitted: June 17, 2021
• First Submitted That Met QC Criteria: June 23, 2021
• First Posted (ACTUAL): June 24, 2021

Study Record Updates

• Last Update Posted (ACTUAL): April 7, 2022
• Last Update Submitted That Met QC Criteria: April 6, 2022
• Last Verified: June 1, 2021

More Information

Terms related to this study

• Keywords: Language; Alzheimer's disease; Mild Cognitive Impairment; Artificial Intelligence; Speech; Machine Learning; Amyloid; Preclinical Alzheimer's disease; Prodromal Alzheimer's disease; Normal Cognition; Acoustic; Linguistic
• Additional Relevant MeSH Terms: Mental Disorders; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Neurocognitive Disorders; Neurodegenerative Diseases; Dementia; Tauopathies; Cognition Disorders; Alzheimer Disease; Cognitive Dysfunction
• Other Study ID Numbers: NOV-0110-2

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No