Alzheimer DiseasePAST-USNCT04937959
Amyloid Prediction in Early Stage Alzheimer's Disease Through Speech Phenotyping - PAST Extension
An observational study of Alzheimer Disease and Alzheimer's Disease (Incl Subtypes), run by Novoic Limited at 1 site in United States.
Trial 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, based on archival spoken or written language samples, as measured by the area under the curve (AUC) of… Read more about this study
- Who is it for?
- Ages 50 to 85 yearsHealthy volunteers can take part
- Conditions the study is for
- Alzheimer Disease, Alzheimer's Disease (Incl Subtypes), Preclinical Alzheimer's Disease
- How many people
- 40 participants
- Where
- 1 siteUnited States
- Study dates
- 22 Jan 2021to 30 Aug 2022
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 50 to 85 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Participants will be identified from participants of the AMYPRED-US study.
Who may be able to join
- 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.
Who cannot join
- Subject hasn't completed the full visit day in the AMYPRED-US study.
Trial locations and contacts
1 site in 1 country.
United States1 site, 1 recruiting
- Recruiting
Syrentis Clinical Research
Santa Ana, California, 92705
Director of Clinical Operations, 714-542-3008, info@syrentis.com
About this study
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 - 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.
- Conditions
- Alzheimer Disease, Alzheimer's Disease (Incl Subtypes), Preclinical Alzheimer's Disease, Prodromal Alzheimer's Disease, Mild Cognitive Impairment, Normal Cognition
- 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
- Medical subject headings
- Alzheimer Disease, Cognitive Dysfunction, Speech, Language
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| 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) | |
| 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) |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: Up to 85 years
Secondary outcomes (11)
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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: Up to 85 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Jun 2021
- Study start22 Jan 2021
- Primary completion30 Aug 2022 (estimated)
- Study completion30 Aug 2022 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Alzheimer DiseaseStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Retrospective
- Enrolment
- 40 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Novoic Limited
- Sponsor type
- Industry (pharma, biotech, devices)
- Responsible party
- Sponsor
- Investigators
- Emil Fristed, MSc, Principal investigator, Novoic Ltd
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04937959
- Sponsor's protocol ID
- NOV-0110-2
- Acronym
- PAST-US
- Status last verified
- Jun 2021
- First submitted
- 17 Jun 2021
- Last updated
- 7 Apr 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 7 Apr 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- 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 - AMYPRED-US PAST Extension Study
- ClinicalTrials.gov ID
- NCT04937959
- Acronym / sponsor ID
- PAST-US / NOV-0110-2
- Conditions
- Alzheimer Disease, Alzheimer's Disease (Incl Subtypes), Preclinical Alzheimer's Disease, Prodromal Alzheimer's Disease, Mild Cognitive Impairment, Normal Cognition
- Keywords
- Alzheimer's disease, Preclinical Alzheimer's disease, Prodromal Alzheimer's disease, Mild Cognitive Impairment, Normal Cognition, Amyloid, Speech, Acoustic
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 40 participants (estimated)
- Lead sponsor
- Novoic LimitedIndustry (pharma, biotech, devices)
- Study start
- 22 Jan 2021 (actual)
- Primary completion
- 30 Aug 2022 (estimated)
- Study completion
- 30 Aug 2022 (estimated)
- First posted
- 24 Jun 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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 design
- Observational model
- Case-control
- Time perspective
- Retrospective
- Number of arms
- 4
| Arm | Type | Receives |
|---|---|---|
| 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) |
| 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) |
Who may qualify
- Ages
- 50 to 85 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Participants will be identified from participants of the AMYPRED-US study.
Key inclusion criteria (4 listed)
- 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.
Key exclusion criteria (1 listed)
- Subject hasn't completed the full visit day in the AMYPRED-US study.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
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.
Time frame: Up to 85 years
Using archival spoken or written language samples as input.
11 secondary outcomes
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.
Time frame: 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.
Time frame: 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.
Time frame: Up to 85 years
The AUC of the binary classifiers distinguishing between MCI and cognitively normal (CN) arms.
Time frame: Up to 85 years
The sensitivity of the binary classifiers distinguishing between MCI and cognitively normal (CN) arms.
Time frame: Up to 85 years
The specificity of the binary classifiers distinguishing between MCI and cognitively normal (CN) arms.
Time frame: Up to 85 years
The Cohen's kappa of the binary classifiers distinguishing between MCI and cognitively normal (CN) arms.
Time frame: 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.
Time frame: 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.
Time frame: 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.
Time frame: 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.
Time frame: Up to 85 years
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 7 Apr 2022.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Emil Fristed, MSc principal investigator
Novoic Ltd
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Alzheimer Disease and Alzheimer's Disease (Incl Subtypes), run by Novoic Limited at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 7 Apr 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Head of Clinical Operations (07849522891, s2@novoic.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome 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. (time frame: Up to 85 years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 7 Apr 2022.