Amyloid Prediction in Early Stage Alzheimer's Disease From Acoustic and Linguistic Patterns of Speech (AMYPRED)

• ClinicalTrials.gov Identifier: NCT04828122
• Recruitment Status: Completed
• First Posted: April 1, 2021
• Last Update Posted: September 5, 2021
• Sponsor: Novoic Limited
• Information provided by (Responsible Party): Novoic Limited

Study Description

Brief Summary:

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, as measured by the 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. Secondary objectives include (1) evaluating whether similar algorithms can detect amyloid-specific cognitive impairment in the cognitively normal (CN) and MCI Arms respectively, as measured on binary classifier performance; (2) whether they can detect MCI, as measured on binary classifier performance (AUC, sensitivity, specificity, Cohen's kappa), and the agreement between the PACC5 composite and the corresponding regression model predicting it in all Arms pooled (Wilcoxon signed-rank test, CIA); (3) evaluating variables that can impact performance of such algorithms of covariates from the speaker (age, gender, education level) and environment (measures of acoustic quality).

Condition or disease
Alzheimer Disease; Preclinical Alzheimer's Disease; Prodromal Alzheimer's Disease; Alzheimer's Disease (Incl Subtypes); Mild Cognitive Impairment

Study Design

• Study Type: Observational [Patient Registry]
• Actual Enrollment: 141 participants
• Observational Model: Case-Control
• Time Perspective: Cross-Sectional
• Target Follow-Up Duration: 2 Weeks
• Official Title: 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
• Actual Study Start Date: November 19, 2020
• Actual Primary Completion Date: August 6, 2021
• Actual Study Completion Date: August 6, 2021

Groups and Cohorts

Group/Cohort
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 or Mild Alzheimer's Dementia; Positive amyloid PET or amyloid CSF status.; MMSE 23-30 (inclusive)
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)

Outcome Measures

Primary Outcome Measures :

1. 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 speech recordings as input. [ Time Frame: baseline ]

Secondary Outcome Measures :

1. The sensitivity, specificity and Cohen's kappa of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) Arms. [ Time Frame: baseline ]
2. The AUC, sensitivity, specificity and Cohen's kappa of the binary classifier distinguishing between amyloid positive cognitively normal (CN) (Arm 3) and amyloid negative cognitively normal (CN) (Arm 4) Arms. [ Time Frame: baseline ]
3. The AUC, sensitivity, specificity and Cohen's kappa of the binary classifier distinguishing between amyloid positive MCI (Arm 1) and amyloid negative MCI (Arm 2) Arms. [ Time Frame: baseline ]
4. The AUC, sensitivity, specificity and Cohen's kappa of the binary classifier distinguishing between the MCI (Arms 1 and 2) and the CN (Arms 3 and 4) Arms. [ Time Frame: baseline ]
5. The agreement between the PACC5 composite and the corresponding regression model predicting it in all four Arms, as measured by the coefficient of individual agreement (CIA). [ Time Frame: baseline ]
6. For each classifier/regressor in outcome 1-6, the correlation between the AUC/CIA and each age group, gender and speech-to-reverberation modulation energy ratio group, as measured by the Kendall rank correlation coefficient. [ Time Frame: baseline ]

Eligibility Criteria

• Ages Eligible for Study: 50 Years to 85 Years (Adult, Older Adult)
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: Yes
• Sampling Method: Non-Probability Sample

Study Population

All participants of the study are based in the UK.

Criteria

Inclusion Criteria:

• Amyloid status must be known, based on an amyloid PET scan or CSF amyloid test, no older than 30 months at the time of consent for Arm 2 and Arm 4 participants (amyloid negative Arms).
• Amyloid status must be known, based on an amyloid PET scan or CSF amyloid test, no older than 60 months at the time of consent for Arm 1 and Arm 3 (amyloid positive Arms).
• Subjects must be aged 50-85 (inclusive).
• Subjects must have MMSE scores of 23-30 (inclusive) based on a test not older than 1 month at the time of the visit.
• Date of diagnosis (if applicable) maximum of five years prior to consent.
• Subjects' first language must be English.
• Willing to participate in a study investigating speech and Alzheimer's disease.
• Availability of a person ('caregiver') who in the investigator's judgment has frequent and sufficient in-person contact with the participant, and is able to provide accurate information regarding the participant's cognitive and functional abilities. This is most likely met when living with a caregiver.
• Able to provide valid informed consent
• Able to use, or has a caregiver who is able to use a smartphone device.
• Has access to a smartphone device running an operation system of Android 7 or above; or iOS 11 or above.

If taking part in the study through virtual visits, the following inclusion criteria also applies:

• Able to use, or has a caregiver who is able to use a personal computer, notebook or tablet.
• Has access to a personal computing device of that is running an operating system of macOS X with macOS 10.9 or later, or Windows 7 or above, or Ubuntu 12.04 or higher; OR has access internet browser software Internet Explorer version 11 or above; or Microsoft Edge version 12 or above, or Firefox version 27 or above, or Google Chrome version 30 or above, or Safari version 7 or above; AND capable of audio and video recording; AND able to connect to the internet.

Exclusion Criteria:

• Clinically significant unstable psychiatric illness in 6 months.
• Diagnosis of Generalised Anxiety Disorder (GAD).
• Diagnosis of Major Depressive Disorder (MDD).
• History or presence of stroke within the past 2 years.
• Documented history of transient ischemic attack or unexplained loss of consciousness within the last 12 months.
• The participant is using drugs to treat symptoms related to AD, and the doses of these drugs were not stable for at least 8 weeks prior to consent.

Contacts and Locations

Locations

United Kingdom

Re:Cognition Health

Birmingham, United Kingdom, B16 8LT

Re:Cognition Health

Guildford, United Kingdom, GU2 7YD

Re:Cognition Health

London, United Kingdom, W1G 9JF

Re:Cognition Health

Plymouth, United Kingdom, PL68BT

Sponsors and Collaborators

Novoic Limited

Investigators

• Principal Investigator: Emil Fristed, MSc; Novoic Limited

More Information

• Responsible Party: Novoic Limited
• ClinicalTrials.gov Identifier: NCT04828122
• Other Study ID Numbers: NOV-0100
• First Posted: April 1, 2021
• Last Update Posted: September 5, 2021
• Last Verified: March 2021

Individual Participant Data (IPD) Sharing Statement:

• Plan to Share IPD: Undecided

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No

Keywords provided by Novoic Limited:

Alzheimer's disease; Preclinical Alzheimer's disease; Prodromal Alzheimer's disease; Mild Cognitive Impairment; Normal Cognition; Amyloid; Speech; Acoustic; Language; Linguistic; Machine Learning; Artificial Intelligence

Additional relevant MeSH terms:

Alzheimer Disease; Cognitive Dysfunction; Dementia; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Tauopathies; Neurodegenerative Diseases; Neurocognitive Disorders; Mental Disorders; Cognition Disorders