Clinical trial NCT04828122: Amyloid Prediction in Early Stage Alzheimer's Disease From Acoustic and Linguistic Patterns of Speech
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
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Alzheimer Disease
Preclinical Alzheimer's Disease
Prodromal Alzheimer's Disease
Alzheimer's Disease (Incl Subtypes)
Mild Cognitive Impairment
Keywords: 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
Lead sponsor: Novoic Limited
Sponsor class: INDUSTRY
First posted: 2021-04-01
Enrollment: 141
Sex: ALL
Minimum age (years): 50
Maximum age (years): 85
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: CROSS_SECTIONAL
Sampling method: NON_PROBABILITY_SAMPLE
Study population: All participants of the study are based in the UK.

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).


Eligibility 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.

Primary outcomes:
measure: 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.
timeFrame: baseline
Secondary outcomes:
measure: 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.
timeFrame: baseline
measure: 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.
timeFrame: baseline
measure: 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.
timeFrame: baseline
measure: 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.
timeFrame: baseline
measure: 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).
timeFrame: baseline
measure: 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.
timeFrame: baseline
Other outcomes:
Locations:
city: Birmingham
country: United Kingdom
facility: Re:Cognition Health
city: Guildford
country: United Kingdom
facility: Re:Cognition Health
city: London
country: United Kingdom
facility: Re:Cognition Health
city: Plymouth
country: United Kingdom
facility: Re:Cognition Health
Study officials:
affiliation: Novoic Limited
name: Emil Fristed, MSc
role: PRINCIPAL_INVESTIGATOR
References: