Digital Screening for Dementia

Overseen By Katrina Coppedge, BA

Age: 65+

Sex: Any

Trial Phase: Academic

Sponsor: Indiana University

Must not be taking: Cholinesterase inhibitors, Memantine

Disqualifiers: Prior ADRD, Bipolar, Schizophrenia, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Approved in 1 Jurisdiction This treatment is already approved in other countries

Compensation: Varies

Number of Visits: 1

3150 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to find better methods for early dementia detection in primary care settings. It tests a Passive Digital Marker (PDM) that uses electronic health records to identify signs of dementia up to three years before symptoms appear. The trial includes three groups: one using PDM alone, another using PDM with a questionnaire, and a usual care group for comparison. Participants must be 65 or older, have had a recent doctor visit, and not have a dementia diagnosis. As an unphased trial, it offers participants the opportunity to contribute to groundbreaking research that could revolutionize early dementia detection.

Do I need to stop my current medications to join the trial?

The trial information does not specify whether you need to stop taking your current medications.

What prior data suggests that the Passive Digital Marker and Quick Dementia Rating Scale are safe for use in primary care?

Research has shown that the Passive Digital Marker (PDM) is a computer tool using advanced technology to predict Alzheimer's and related dementias. It examines electronic health records to identify signs of these conditions up to three years before they appear.

Although few studies have focused on the safety of PDM, it is generally considered safe because it only analyzes existing health data without involving physical procedures. No reports of negative effects have emerged from its use. The PDM processes data to help doctors spot potential issues earlier, posing little risk to participants since it doesn't involve medication or medical procedures. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about this trial because it explores innovative ways to detect Alzheimer's Disease and Related Dementias (ADRD) early using technology. The Passive Digital Marker (PDM) leverages a machine learning algorithm to analyze Electronic Health Record data and predict ADRD up to three years before symptoms appear. This method stands out from the traditional approach of relying solely on cognitive tests or clinical evaluations. Additionally, combining PDM with the Quick Dementia Rating Scale (QDRS) as a patient-reported outcome tool aims to enhance early diagnosis. Overall, these tools could potentially transform routine primary care visits into proactive opportunities for early dementia detection, offering hope for improved long-term outcomes.

What evidence suggests that this trial's treatments could be effective for dementia?

Research shows that the Passive Digital Marker (PDM), a tool under study in this trial, is a promising method for predicting Alzheimer's and other dementias. Studies have found that this technology can detect signs of these conditions one to three years before symptoms appear, using information from electronic health records. In this trial, some participants will have their data analyzed with the PDM alone, while others will also complete the Quick Dementia Rating Scale (QDRS), a patient-filled questionnaire. This combined approach could help doctors identify dementia earlier and begin treatments sooner. ^{1 3 4 6 7}

Who Is on the Research Team?

Malaz Boustani, MD, MPH

Principal Investigator

Indiana University

Are You a Good Fit for This Trial?

This trial is for caregivers of individuals with Alzheimer's Disease or dementia. It aims to test if using a Passive Digital Marker (PDM) and the Quick Dementia Rating System (QDRS), either alone or combined, can help primary care practices diagnose dementia more frequently within a year.

Inclusion Criteria

I am 65 years old or older.

Ability to provide informed consent

I can communicate in English or Spanish.

Exclusion Criteria

I have been diagnosed with Alzheimer's or mild cognitive impairment.

Has serious mental illness such as bipolar or schizophrenia as determined by ICD-10 code

Permanent resident of a nursing facility

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Annual Wellness Visit (AWV)

Participants undergo the Annual Wellness Visit, which includes the Passive Digital Marker (PDM) and Quick Dementia Rating Scale (QDRS) assessments for some arms

1 day

1 visit (in-person)

Follow-up

Participants are monitored for new ADRD diagnoses and related services over a 12-month period

12 months

What Are the Treatments Tested in This Trial?

Interventions

• Passive Digital Marker

Trial Overview The study is testing the effectiveness of a Passive Digital Marker tool and the QDRS in detecting Alzheimer's Disease and related dementias. The goal is to see if these methods increase diagnosis rates when used by primary care doctors.

How Is the Trial Designed?

Group I: Passive Digital Marker (PDM) Experimental Treatment 1 Intervention

Passive Digital Marker (PDM): Electronic Health Record Data from those clinics randomized to PDM will be run through the PDM, a machine learning algorithm which can predict ADRD one year and three years prior to its onset.

Group II: Passive Digital Marker (PDM) + Quick Dementia Rating Scale (QDRS) Active Control 1 Intervention

Patients in the primary care clinics randomized to PDM+QDRS will have Electronic Health Record Data of their patients run through the PDM, a machine learning algorithm which can predict ADRD one year and three years prior to its onset. In addition, patients from these clinics will have their patients complete the QDRS, a validated patient reported outcome (PRO) tool. This combined approach will assess the value of early detection of ADRD and if the annual well visit can overcome the barriers related to early detection of ADRD.

Group III: Annual Well Visit or any other visit to Primary Care Doctor Active Control 1 Intervention

Annual Well Visit or any other visit to Primary Care Doctor: This is the usual care arm. Electronic Health Record Data for patients from the clinics randomized to usual care will be collected for comparison with the other 2 arms. Patients from these primary care clinics must have had a visit to their doctor either as an annual well visit (AWV) or any other type of visit. These clinics will not have to do anything for the study but run their business as usual without altering anything.

Passive Digital Marker is already approved in United States for the following indications:

Approved in United States as PDM for:

• Alzheimer's disease and related dementias (ADRD) detection

Who Is Running the Clinical Trial?

Indiana University

Lead Sponsor

Trials

1,063

Recruited

1,182,000+

National Institute on Aging (NIA)

Collaborator

Trials

1,841

Recruited

28,150,000+

Published Research Related to This Trial

Digital biomarkers, which are collected through devices like wearables and sensors, offer a promising way to assess cognitive decline in real-life settings, but there is currently no consensus on standards or the most effective types of biomarkers.

A review of 26 studies involving 12 to 279 participants over periods of 3 days to 3.6 years found that while embedded passive sensors show the most promise for home-based evaluations, many technologies are not yet ready for practical use in everyday life.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Current State of Digital Biomarker Technologies for Real-Life, Home-Based Monitoring of Cognitive Function for Mild Cognitive Impairment to Mild Alzheimer Disease and Implications for Clinical Care: Systematic Review. Piau, A., Wild, K., Mattek, N., et al.[2020]

Digital technologies are being explored to create more sensitive and objective assessments for neurodegenerative diseases like Alzheimer's, Parkinson's, and Huntington's, which could improve clinical trial outcomes.

Projects like RADAR-AD and IDEA-FAST aim to establish reliable digital endpoints that can better track symptoms and quality of life, addressing the limitations of traditional assessment methods in early disease stages.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Digital endpoints in clinical trials of Alzheimer's disease and other neurodegenerative diseases: challenges and opportunities. Brem, AK., Kuruppu, S., de Boer, C., et al.[2023]

This study evaluated 10 digital technologies for measuring cognitive impairment in Alzheimer disease, involving 50 participants across different cognitive stages, to improve the sensitivity of clinical drug development endpoints.

The research aimed to validate these digital tools against traditional assessments, providing insights into their feasibility and potential to enhance the detection of cognitive changes in early Alzheimer's disease.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Description of the Method for Evaluating Digital Endpoints in Alzheimer Disease Study: Protocol for an Exploratory, Cross-sectional Study. Curcic, J., Vallejo, V., Sorinas, J., et al.[2022]

The Cognitive Assessment for Dementia, iPad version (CADi), has been shown to effectively differentiate between dementia patients and healthy elderly individuals, indicating its potential as a reliable screening tool.

The CADi demonstrated good reliability and validity, with acceptable Cronbach's alpha values and significant test-retest reliability over a one-year period, making it suitable for mass screening in Japanese populations.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Validation of a new mass screening tool for cognitive impairment: Cognitive Assessment for Dementia, iPad version. Onoda, K., Hamano, T., Nabika, Y., et al.[2022]

A computer-generated version of the Clinical Dementia Rating (CDR) was developed and tested using data from 138 evaluations, showing excellent internal consistency and interrater reliability, making it a reliable tool for assessing cognitive impairment in Alzheimer's disease.

The software-based CDR demonstrated strong discriminative ability between demented and nondemented individuals, with an area under the curve of 0.95, indicating it is an effective alternative to traditional paper-based methods for clinical and research settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The "portable" CDR: translating the clinical dementia rating interview into a PDA format. Galvin, JE., Meuser, TM., Coats, MA., et al.[2021]

The revised criteria for Alzheimer's disease (AD) dementia aim to be flexible for both general healthcare providers and specialized researchers, maintaining the framework of probable AD dementia from the 1984 guidelines while incorporating new clinical insights.

Biomarker evidence has been integrated into the diagnostic criteria for AD dementia, which is expected to improve the accuracy and specificity of diagnoses in research settings, although further validation of these biomarker-based diagnoses is still needed.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. McKhann, GM., Knopman, DS., Chertkow, H., et al.[2023]

A systematic review of 19 studies found that electronic health record (EHR)-based passive digital markers (PDMs) can potentially enhance the early detection of Alzheimer's disease and related dementias, with performance metrics (AUC) ranging from 0.67 to 0.97.

Despite the promise of these PDMs, the studies showed significant variability in quality and methodology, with only seven using valid diagnostic methods, indicating a need for further refinement and standardization in their development.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Passive digital markers for Alzheimer's disease and other related dementias: A systematic evidence review. Taylor, B., Barboi, C., Boustani, M.[2023]

The Electronic Clinical Dementia Rating (eCDR) shows strong concordance with the traditional Clinical Dementia Rating (CDR), with over 90% agreement on many assessment items, indicating its potential as a reliable tool for screening cognitive impairment in older adults.

In a study of 288 participants, the eCDR demonstrated a good association with in-clinic assessments, achieving an area under the curve of 0.79 for global scores, suggesting it could effectively facilitate remote dementia screening and assessment.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Evaluation of the Electronic Clinical Dementia Rating for Dementia Screening. Nosheny, RL., Yen, D., Howell, T., et al.[2023]

Citations

1. pubmed.ncbi.nlm.nih.gov pubmed.ncbi.nlm.nih.gov/37249252/

Passive digital markers for Alzheimer's disease and other ... We conducted a systematic evidence review to identify studies that describe the development, performance, and validity of EHR-based PDMs for ADRD.

2. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC9552361/

Digital detection of dementia (D3) - PubMed Central - NIH We have developed a Passive Digital Marker (PDM), based on machine learning algorithms applied to EHR data, and paired it with a patient-reported outcome (the ...

3. agsjournals.onlinelibrary.wiley.com agsjournals.onlinelibrary.wiley.com/doi/abs/10.1111/jgs.18426

Passive digital markers for Alzheimer's disease and other ... We conducted a systematic evidence review to identify studies that describe the development, performance, and validity of EHR-based PDMs for ...

4. clinicaltrials.gov clinicaltrials.gov/study/NCT05231954

Digital Detection of Dementia (D Cubed) Studies: D2 Passive Digital Marker (PDM) - is a Machine Learning (ML) algorithm which can predict ADRD one year and three years prior to its onset by using routine care ...

5. ovid.com ovid.com/journals/jamger/pdf/10.1111/jgs.18426~passive-digital-markers-for-alzheimers-disease-and-other

Passive Digital Markers for Alzheimer's Disease and Other ... Abstract. Background: The timely detection of Alzheimer's disease and other related dementias (ADRD) is suboptimal. Digital data already ...

6. clinicaltrials.gov clinicaltrials.gov/study/NCT06224205

Digital Detection of Dementia (D Cubed) Studies: D3 Passive Digital Marker (PDM) - is a Machine Learning (ML) algorithm which can predict ADRD one year and three years prior to its onset by using routine care ...

7. clinicalresearchnewsonline.com clinicalresearchnewsonline.com/news/2023/02/22/pragmatic-trials-testing-passive-digital-marker-for-detecting-dementia

Pragmatic Trials Testing 'Passive Digital Marker' For ... Application of the PDM will now be tested in the real world in a pair of pragmatic randomized controlled trials, the first of which is already ...