Alzheimer DiseaseAltoidaMLNCT02843529
Evaluation of a Computerized Complex Instrumental Activities of Daily Living Marker (NMI)
A study testing Altoida: neuropsychological, MRI, EEG and CSF biomarkers in people with Alzheimer Disease and Mild Cognitive Impairment, run by Altoida.
Trial summary
The proposed study is designed to evaluate the performance of the ALTOIDA™ System as a tool to assist physicians in diagnosing Alzheimer's Disease (AD) in real-world clinical settings. Read more about this study
- Who is it for?
- Ages 55 to 90 yearsHealthy volunteers can take part
- Conditions the study is for
- Alzheimer Disease, Mild Cognitive Impairment, Memory Disorders
- What is being tested?
- Altoida: neuropsychological, MRI, EEG and CSF biomarkers
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 548 participants
- Where
- No sites listed yet
- Study dates
- 17 Oct 2016to 21 Feb 2020
- Phase
- Interventional
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
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 55 to 90 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Between 55 and 90 years of age
- Study partner to accompany patient to all clinic visits for the duration of the protocol
- Memory complaint by patient and/or study partner
- Abnormal memory function score on Wechsler Memory Scale (adjusted for education)
- Mini-Mental State Exam score between 24 and 30 (inclusive)
- Clinical Dementia Rating = 0.5; Memory Box score at least 0.5
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- General cognition and functional performance sufficiently preserved such that a diagnosis of Alzheimer's disease cannot be made by the site physician at the time of the screening visit
- Stability of the following permitted medications for 4 weeks (unless stated otherwise):
- Antidepressants lacking significant anticholinergic side effects
- Estrogen replacement therapy
- Gingko biloba is permissible, but discouraged
- Washout from psychoactive medication (e.g., excluded antidepressants, neuroleptics, chronic anxiolytics or sedative hypnotics, etc.) for at least 4 weeks prior to screening
- Cholinesterase inhibitors and memantine if stable for 12 weeks prior to screening
- Geriatric Depression Scale less than 6
- Visual and auditory acuity adequate for neuropsychological testing
- Good general health with no diseases expected to interfere with the study
- Not pregnant, lactating, or of childbearing potential (i.e. women must be two years post-menopausal or surgically sterile)
- Hachinski less than or equal to 4
- Six grade education or has a good work history (sufficient to exclude mental retardation)
- Fluent in English or Spanish
- Agrees to at least one lumbar puncture for the collection of CSF
- Willing and able to complete all baseline assessments
- Willing to undergo repeated MRIs and at least two PET scans and willing to provide DNA and plasma samples as specified
- Willing and able to participate in a longitudinal imaging study
Who cannot join
- Any significant neurologic disease other than suspected incipient Alzheimer's disease, such as Parkinson's disease, multi-infarct dementia, Huntington's disease, normal pressure hydrocephalus, brain tumor, progressive supranuclear palsy, seizure disorder, subdural hematoma, multiple sclerosis, or history of significant head trauma followed by persistent neurologic defaults or known structural brain abnormalities
- Screening/baseline MRI scans with evidence of infection, infarction, or other focal lesions; multiple lacunes or lacunes in a critical memory structure
- Presence of pacemakers, aneurysm clips, artificial heart valves, ear implants, metal fragments or foreign objects in the eyes, skin or body
- Major depression, bipolar disorder as described in DSM-IV within the past 1 year
- Psychotic features, agitation or behavioral problems within the last 3 months which could lead to difficulty complying with the protocol
- History of schizophrenia
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- History of alcohol or substance abuse or dependence within the past 2 years
- Any significant systemic illness or unstable medical condition which could lead to difficulty complying with the protocol
- Clinically significant abnormalities in B12, or TFTs that might interfere with the study
- Residence in skilled nursing facility
- Current use of specific psychoactive medications (e.g.,certain antidepressants, neuroleptics, chronic anxiolytics or sedative hypnotics, etc.); current use of warfarin (exclusionary for lumbar puncture)
- Use of investigational agents one month prior to entry and for the duration of the trial
- Exclusion for amyloid imaging with 18F -AV-45: Current or recent participation in any procedures involving radioactive agents such that the total radiation dose exposure to the participant in any given year would exceed the limits of annual and total dose commitment set forth in the US Code of Federal Regulations (CFR) Title 21 Section 361.1
- Exceptions to these guidelines may be considered on a case-by-case basis at the discretion of the protocol director
About this study
Official title: Evaluation of a Computerized Complex Instrumental Activities of Daily Living Marker (NMI) as a Pre-Clinical or Pro-Dromal Alzheimers Diagnosis (Prognosis) for Optimum Outcomes
The proposed study is designed to evaluate the performance of the ALTOIDA™ System as a tool to assist physicians in diagnosing Alzheimer's Disease (AD) in real-world clinical settings. The design of this study is guided by two overriding factors: 1) to optimize the performance of the ALTOIDA™ Neuro Motor Index (NMI) prognosis classifiers, the subjects making up the training sets must be well characterized as to their clinical diagnosis, and 2) all ALTOIDA™ tests must be performed and reproduced in real-world clinical settings.
Although there is already a large body of peer-reviewed scientific literature demonstrating that certain digital biomarker patterns are associated with certain neurologic conditions, the utilization of such tools for the evaluation of neurologic disorders is still considered an emerging science and therefore in the investigational stage. Although this protocol will report on brain patterns of certain neurologic conditions such as cognitive impairment and Alzheimer's disease, based on patterns published in peer-reviewed journals, such findings are not considered stand alone or diagnostic per se and should always be considered by the primary physician in conjunction with the patient's clinical condition. These data should only be used as additional information to add to the primary physician's diagnostic impression.
Read the detailed description
The goal of the study is to determine relationships among the clinical, cognitive, imaging, genetic, and biochemical biomarker characteristics of the stage of the AD spectrum that precedes MCI, the mildest symptomatic phase of AD, referred to here as MCI. The ADNI-GO model posits that AD begins with amyloid β (Aβ) deposition in the cortex, which leads to synaptic dysfunction, neurodegeneration, and cognitive/ functional decline.
It may be possible to determine the future development of ALZ in a preclinical state in a cognitively normal but high risk individual at least 18-24 months before any symptoms develop of cognitive impairment. In addition a newly proposed research framework proposes to use biomarkers for amyloid, tau, and neurodegeneration (ATN) to classify MCI patients.
Some of the leading-edge technologies under study are brain-imaging techniques, such as positron emission tomography (PET), including FDG-PET (which measures glucose metabolism in the brain); PET using a radioactive compound (F-AV-45) that measures brain beta-amyloid; and structural MRI. Brain scans are showing scientists how the brain's structure and function change as AD starts and progresses. Biomarkers in cerebrospinal fluid are revealing other changes that could identify which patients with MCI will develop Alzheimer's. Scientists are looking at levels of beta-amyloid and tau in cerebrospinal fluid. (Abnormal amounts of the amyloid and tau proteins in the brain are hallmarks of Alzheimer's disease.)
The aim of the study is to evaluate the performance of the ALTOIDA™ System as as a tool to assist physicians in diagnosing Alzheimer's Disease (AD) in real-world clinical settings.
The study will be :
- Multi-Center Study: primary goal of this study will be to evaluate the ALTOIDA™ Platform across multiple study locations. This will demonstrate an ability to perform tests, collect data, and generate classifications irrespective of variations in testing locations and personnel.
12 international study sites will be selected with the US based sites being a recognized NIH Center of Excellence for Alzheimer's disease or other nationally recognized Alzheimer's disease research center. Each site will evaluate up to 60 community dwellers evenly divided between MCI patients and age-matched controls (while the prevalence of AD is approximately 12% in the general population, the ratio of AD to normal among those who visit a clinic for memory or cognitive related issues is between 50-60%).
Each site will follow the same testing protocols. Participants will be asked if they would like to participate in a protocol that monitors their prospective risk for developing ALZ short term, and whether certain of their prescribed medications may have a protective effect. Those who are accepting to be participants are then enrolled in the study.
Enrollees will be tested for risk factors for having pre-clinical ALZ. Individuals identified as being at risk at baseline are followed at 6 month intervals for a 48 month period using psychometric testing and functional neuroimaging. Their maintenance of cognitive stability or cognitive decline is monitored while under the care of their PMD and while taking medications of interest.
All test data will be uploaded to the online ALTOIDA™ database server.
- The overall impact of this study will be increased knowledge concerning the sequence and timing of events leading to MCI and from MCI to AD, development of better clinical and Neuro Motor Index prognosis methods for early detection and for monitoring the progression of these conditions, and facilitation of clinical trials of treatments to slow disease progression, ultimately contributing to the prevention of AD.
- Conditions
- Alzheimer Disease, Mild Cognitive Impairment, Memory Disorders, Cognitive Impairment, Dementia, Presymptomatic Disease
- Being tested
- Altoida: neuropsychological, MRI, EEG and CSF biomarkers
- Keywords
- biomarkers, CSF, EEG, MRI, Digital biomarkers
- Medical subject headings
- Alzheimer Disease, Cognitive Dysfunction, Memory Disorders, Dementia, Asymptomatic Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Altoida: neuropsychological, MRI, EEG and CSF biomarkersOther
Data collection at baseline: clinical (neurological, activity of the daily life, instrumental activity of the daily life, depression scale), standard neuropsychological exam, ALTOIDA and neurophysiology (EEG/ERPs) in both Prodromal and Preclinical AD subjects. In both Prodromal and Preclinical AD subjects, APOE genotyping. The local clinical Unit should document the positivity at the baseline session of at least one of the biomarkers of AD mentioned above.
Data collection at 6, 12, 24 and 36 months of follow up: clinical (neurological, activity of the daily life, instrumental activity of the daily life, depression scale), standard neuropsychological exam, ALTOIDA and neurophysiology (EEG/ERPs) in both Prodromal and Preclinical AD subjects.
| Study group | Role | What they receive |
|---|---|---|
| Prodromal AD (MCI) | Experimental | Altoida: neuropsychological, MRI, EEG and CSF biomarkers
MCI participants will undergo at baseline and every 6 months a neurological examination and a neuropsychological assessment. Alzheimer disease biomarkers' measurements will be performed at inclusion and at the end of the study (or the conversion). Receives: Other: Altoida: neuropsychological, MRI, EEG and CSF biomarkers |
| Preclinical AD (cognitively normal) | Experimental | Altoida: neuropsychological, MRI, EEG and CSF biomarkers
Cognitively normal participants at risk will undergo at baseline and every 6 months a neurological examination and a neuropsychological assessment. Alzheimer disease biomarkers' measurements will be performed at inclusion and at the end of the study (or the conversion). Receives: Other: Altoida: neuropsychological, MRI, EEG and CSF biomarkers |
What is being measured
The primary outcome is the main question the study is designed to answer.
Change in Diagnostic Area Under the Receiver Operating Characteristic Curve (ROC-AUC)
The machine learning models capturing voice data, hands micromovements \& micro-errors, posture changes, eye tracking, visuospatial navigation micro-errors and spatio-temporal gait parameters developed for the Altoida system will be tested in this prospective cohort. Sensitivity, specificity and accuracy of the model will be tested in differential diagnosis between the study groups as well as the accuracy of prediction cognitive decline as measured by neuropsychological test battery in the MCI group.
Measured: approximately 40 months follow up
Secondary outcomes (29)
Change From Baseline in Clinical Measure 1
Clinical Dementia Rating (CDR), including CDR sum of boxes (CDR-SB) and clinician's diagnostic assessment
Measured: baseline, 6, 12, 24, 36 and 42 months of follow up
Change From Baseline in Clinical Measure 2
Geriatric Depression Scale (GDS)
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Clinical Measure 3
Functional Assessment Questionnaire (FAQ)
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Clinical Measure 4
Mini Mental Status Exam (MMSE)
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Clinical Measure 5
Neuropsychiatric Inventory Questionnaire (NPI-Q)
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Clinical Measure 6
Activities of the daily life (ADL)
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Clinical Measure 7
Instrumental activities of the daily life (iADL)
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
ADAS Cog
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
-Rey-Osterrieth Complex Figure Test (Copy)
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Trail Making Test
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Digit Span Forward
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Category Fluency (Animals \& Vegetables)
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Digit Span Backward
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Rey Osterrieth Complex Figure Test (30 minute delay)
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Wechsler Memory Scale - Revised (WMS-R) Digit Span
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Wechsler Memory Scale Logical Memory
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Wechsler Memory Scale Paragraph Memory (Immediate \& Delayed Recall)
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Wechsler Adult Intelligence Scale - Revised (WAIS-R) Digit-Symbol Substitution Test
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Rey Auditory Verbal Learning Test (RAVLT)
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Secondary Resting State EEG Endpoints
EEG endpoints (occipital, parietal, and temporal sources of delta and low-frequency alpha rhythms) according to the PharmaCog WP5 European ADNI. These markers are expected to be related to disease status at baseline assessment and disease progression at follow-ups. Exploratory probability level of p < 0.05.
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Secondary Resting State Auditory Oddball ERP Endpoints
ERP endpoints (latency of scalp parietal P3b peak and activity of the cingulate and temporal-parietal sources of P3b peak according to PharmaCog WP5 European ADNI). These markers are expected to be related to disease status at baseline assessment and disease progression at follow-ups. Exploratory probability level of p < 0.05.
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Total Abeta 1-42 (Aβ42) Amyloid Deposition
Currently available evidence strongly supports the position that the initiating event in Alzheimer's disease (AD) is related to abnormal processing of beta-amyloid (Abeta) peptide, ultimately leading to formation of Abeta plaques in the brain. Baseline amount of CSF Abeta(42) will be investigated.
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change of Brain Amyloid Deposition
Biomarkers of brain beta-amyloidosis are reductions in CSF Abeta(42) and increased amyloid PET tracer retention. The change in amyloid deposition as measured by Abeta 1-42 (Aβ42) and its relation to the genetic, clinical, neuropsychological, EEG and ERP endpoints measurement will be assessed.
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change of CSF Biomarkers Tau and ptau181 Values
The change in CSF biomarkers tau and ptau181 values and its relation to the genetic, clinical, neuropsychological, EEG and ERP endpoints measurement will be assessed.
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
MRI (Optional)
Relationship between MRI measures (brain volume, hippocampus atrophy, vascular lesions) and biomarkers.
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Changes in Driving Breaking Force
Changes in driving behavior, such as breaking force observed continuesly through in-car sensors or dongles.
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Changes in Driving Acceleration Velocity
Changes in driving behavior, such as acceleration velocity observed continuesly through in-car sensors or dongles.
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Changes in Driving Direction
Changes in driving behavior, such as sudden changes of direction observed continuesly through in-car sensors or dongles.
Measured: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Changes in Driving Violations
Changes in driving behavior, such as speed limit violations observed continuesly through in-car sensors or dongles.
Measured: Continuous measurement for approximately 12 months follow up
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Jul 2016 (estimated)
- Study start17 Oct 2016
- Primary completion18 Feb 2020
- Study completion21 Feb 2020
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Publications (18)Papers the sponsor has linked to this study.
- 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- Adults at high risk of developing ALZ within 18-40 months (MCI) or cognitively normal for their age sex matching group. Risk factors include parents with a history of ALZ, and/or positive APOE4 alleles.
- Masking
- Double blind
- Who is masked
- Participant, Investigator
- Enrolment
- 548 participants (actual)
Sponsor and investigators
- Lead sponsor
- Altoida
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- Greek Alzheimer's Association and Related Disorders, University of Roma La Sapienza, IRCCS Centro San Giovanni di Dio Fatebenefratelli, Neuromed IRCCS, Scripps Health, Global Brain Health Institute (GBHI), Takeda Pharmaceuticals International, Inc., Research Center on Computational BioMarkers, Bioinformatics and Human Electrophysiology Laboratory, Fundacion Clinic per a la Recerca Biomédica, University of Dublin, Trinity College, University of Barcelona, EIT Health, Klinik Hirslanden, Zurich, The University of Texas at Dallas
- Responsible party
- Sponsor
- Investigators
- Mark Wiederhold, PhD, Study chair, Scripps Clinic La Jolla Poole Building
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT02843529
- Sponsor's protocol ID
- altoidaML01
- Acronym
- AltoidaML
- Status last verified
- Jul 2024
- First submitted
- 18 May 2016
- Last updated
- 23 Aug 2024
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- Yes
- Individual data sharing
- Undecided: neuromotor data sharing
Publications
Tarnanas I, Tsolaki M, Nef T, M Muri R, Mosimann UP. Can a novel computerized cognitive screening test provide additional information for early detection of Alzheimer's disease? Alzheimers Dement. 2014 Nov;10(6):790-8. doi: 10.1016/j.jalz.2014.01.002. Epub 2014 Mar 18.
PubMed 24656838Vallejo V, Mitache AV, Tarnanas I, Muri R, Mosimann UP, Nef T. Combining qualitative and quantitative methods to analyze serious games outcomes: A pilot study for a new cognitive screening tool. Annu Int Conf IEEE Eng Med Biol Soc. 2015 Aug;2015:1327-30. doi: 10.1109/EMBC.2015.7318613.
PubMed 26736513Nef T, Urwyler P, Buchler M, Tarnanas I, Stucki R, Cazzoli D, Muri R, Mosimann U. Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data. Sensors (Basel). 2015 May 21;15(5):11725-40. doi: 10.3390/s150511725.
PubMed 26007727Tarnanas I, Laskaris N, Tsolaki M, Muri R, Nef T, Mosimann UP. On the comparison of a novel serious game and electroencephalography biomarkers for early dementia screening. Adv Exp Med Biol. 2015;821:63-77. doi: 10.1007/978-3-319-08939-3_11.
PubMed 25416111Tarnanas I, Papagiannopoulos S, Kazis D, Wiederhold M, Widerhold B, Tsolaki M. Reliability of a novel serious game using dual-task gait profiles to early characterize aMCI. Front Aging Neurosci. 2015 Apr 22;7:50. doi: 10.3389/fnagi.2015.00050. eCollection 2015.
PubMed 25954193Dimitriadis SI, Laskaris NA, Bitzidou MP, Tarnanas I, Tsolaki MN. A novel biomarker of amnestic MCI based on dynamic cross-frequency coupling patterns during cognitive brain responses. Front Neurosci. 2015 Oct 20;9:350. doi: 10.3389/fnins.2015.00350. eCollection 2015.
PubMed 26539070Tarnanas I, Schlee W, Tsolaki M, Muri R, Mosimann U, Nef T. Ecological validity of virtual reality daily living activities screening for early dementia: longitudinal study. JMIR Serious Games. 2013 Aug 6;1(1):e1. doi: 10.2196/games.2778.
PubMed 25658491Xekardaki A, Rodriguez C, Montandon ML, Toma S, Tombeur E, Herrmann FR, Zekry D, Lovblad KO, Barkhof F, Giannakopoulos P, Haller S. Arterial spin labeling may contribute to the prediction of cognitive deterioration in healthy elderly individuals. Radiology. 2015 Feb;274(2):490-9. doi: 10.1148/radiol.14140680. Epub 2014 Oct 7.
PubMed 25291458Woodard JL, Seidenberg M, Nielson KA, Smith JC, Antuono P, Durgerian S, Guidotti L, Zhang Q, Butts A, Hantke N, Lancaster M, Rao SM. Prediction of cognitive decline in healthy older adults using fMRI. J Alzheimers Dis. 2010;21(3):871-85. doi: 10.3233/JAD-2010-091693.
PubMed 20634590Rizk-Jackson A, Insel P, Petersen R, Aisen P, Jack C, Weiner M. Early indications of future cognitive decline: stable versus declining controls. PLoS One. 2013 Sep 9;8(9):e74062. doi: 10.1371/journal.pone.0074062. eCollection 2013.
PubMed 24040166Lazarczyk MJ, Hof PR, Bouras C, Giannakopoulos P. Preclinical Alzheimer disease: identification of cases at risk among cognitively intact older individuals. BMC Med. 2012 Oct 25;10:127. doi: 10.1186/1741-7015-10-127.
PubMed 23098093Haller S, Nguyen D, Rodriguez C, Emch J, Gold G, Bartsch A, Lovblad KO, Giannakopoulos P. Individual prediction of cognitive decline in mild cognitive impairment using support vector machine-based analysis of diffusion tensor imaging data. J Alzheimers Dis. 2010;22(1):315-27. doi: 10.3233/JAD-2010-100840.
PubMed 20847435Green RC, Christensen KD, Cupples LA, Relkin NR, Whitehouse PJ, Royal CD, Obisesan TO, Cook-Deegan R, Linnenbringer E, Butson MB, Fasaye GA, Levinson E, Roberts JS; REVEAL Study Group. A randomized noninferiority trial of condensed protocols for genetic risk disclosure of Alzheimer's disease. Alzheimers Dement. 2015 Oct;11(10):1222-30. doi: 10.1016/j.jalz.2014.10.014. Epub 2014 Dec 9.
PubMed 25499536Christensen KD, Roberts JS, Whitehouse PJ, Royal CD, Obisesan TO, Cupples LA, Vernarelli JA, Bhatt DL, Linnenbringer E, Butson MB, Fasaye GA, Uhlmann WR, Hiraki S, Wang N, Cook-Deegan R, Green RC; REVEAL Study Group*. Disclosing Pleiotropic Effects During Genetic Risk Assessment for Alzheimer Disease: A Randomized Trial. Ann Intern Med. 2016 Feb 2;164(3):155-63. doi: 10.7326/M15-0187. Epub 2016 Jan 26.
PubMed 26810768Galluzzi S, Marizzoni M, Babiloni C, Albani D, Antelmi L, Bagnoli C, Bartres-Faz D, Cordone S, Didic M, Farotti L, Fiedler U, Forloni G, Girtler N, Hensch T, Jovicich J, Leeuwis A, Marra C, Molinuevo JL, Nobili F, Pariente J, Parnetti L, Payoux P, Del Percio C, Ranjeva JP, Rolandi E, Rossini PM, Schonknecht P, Soricelli A, Tsolaki M, Visser PJ, Wiltfang J, Richardson JC, Bordet R, Blin O, Frisoni GB; PharmaCog Consortium. Clinical and biomarker profiling of prodromal Alzheimer's disease in workpackage 5 of the Innovative Medicines Initiative PharmaCog project: a 'European ADNI study'. J Intern Med. 2016 Jun;279(6):576-91. doi: 10.1111/joim.12482. Epub 2016 Mar 4.
PubMed 26940242
Study at a glance
From the registry record, last updated by the sponsor on 23 Aug 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation of a Computerized Complex Instrumental Activities of Daily Living Marker (NMI) as a Pre-Clinical or Pro-Dromal Alzheimers Diagnosis (Prognosis) for Optimum Outcomes
- ClinicalTrials.gov ID
- NCT02843529
- Acronym / sponsor ID
- AltoidaML / altoidaML01
- Conditions
- Alzheimer Disease, Mild Cognitive Impairment, Memory Disorders, Cognitive Impairment, Dementia, Presymptomatic Disease
- Keywords
- biomarkers, CSF, EEG, MRI, Digital biomarkers
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 548 participants (actual)
- Lead sponsor
- AltoidaIndustry (pharma, biotech, devices)
- Collaborators
- Greek Alzheimer's Association and Related Disorders, University of Roma La Sapienza, IRCCS Centro San Giovanni di Dio Fatebenefratelli, Neuromed IRCCS, Scripps Health, Global Brain Health Institute (GBHI), Takeda Pharmaceuticals International, Inc., Research Center on Computational BioMarkers, Bioinformatics and Human Electrophysiology Laboratory, Fundacion Clinic per a la Recerca Biomédica, University of Dublin, Trinity College, University of Barcelona, EIT Health, Klinik Hirslanden, Zurich, The University of Texas at Dallas
- Study start
- 17 Oct 2016 (actual)
- Primary completion
- 18 Feb 2020 (actual)
- Study completion
- 21 Feb 2020 (actual)
- First posted
- 26 Jul 2016 (estimated)
- Results
- Posted 16 Dec 2020
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The proposed study is designed to evaluate the performance of the ALTOIDA™ System as a tool to assist physicians in diagnosing Alzheimer's Disease (AD) in real-world clinical settings. The design of this study is guided by two overriding factors: 1) to optimize the performance of the ALTOIDA™ Neuro Motor Index (NMI) prognosis classifiers, the subjects making up the training sets must be well characterized as to their clinical diagnosis, and 2) all ALTOIDA™ tests must be performed and reproduced in real-world clinical settings.
Although there is already a large body of peer-reviewed scientific literature demonstrating that certain digital biomarker patterns are associated with certain neurologic conditions, the utilization of such tools for the evaluation of neurologic disorders is still considered an emerging science and therefore in the investigational stage. Although this protocol will report on brain patterns of certain neurologic conditions such as cognitive impairment and Alzheimer's disease, based on patterns published in peer-reviewed journals, such findings are not considered stand alone or diagnostic per se and should always be considered by the primary physician in conjunction with the patient's clinical condition. These data should only be used as additional information to add to the primary physician's diagnostic impression.
Detailed description
The goal of the study is to determine relationships among the clinical, cognitive, imaging, genetic, and biochemical biomarker characteristics of the stage of the AD spectrum that precedes MCI, the mildest symptomatic phase of AD, referred to here as MCI. The ADNI-GO model posits that AD begins with amyloid β (Aβ) deposition in the cortex, which leads to synaptic dysfunction, neurodegeneration, and cognitive/ functional decline.
It may be possible to determine the future development of ALZ in a preclinical state in a cognitively normal but high risk individual at least 18-24 months before any symptoms develop of cognitive impairment. In addition a newly proposed research framework proposes to use biomarkers for amyloid, tau, and neurodegeneration (ATN) to classify MCI patients.
Some of the leading-edge technologies under study are brain-imaging techniques, such as positron emission tomography (PET), including FDG-PET (which measures glucose metabolism in the brain); PET using a radioactive compound (F-AV-45) that measures brain beta-amyloid; and structural MRI. Brain scans are showing scientists how the brain's structure and function change as AD starts and progresses. Biomarkers in cerebrospinal fluid are revealing other changes that could identify which patients with MCI will develop Alzheimer's. Scientists are looking at levels of beta-amyloid and tau in cerebrospinal fluid. (Abnormal amounts of the amyloid and tau proteins in the brain are hallmarks of Alzheimer's disease.)
The aim of the study is to evaluate the performance of the ALTOIDA™ System as as a tool to assist physicians in diagnosing Alzheimer's Disease (AD) in real-world clinical settings.
The study will be :
- Multi-Center Study: primary goal of this study will be to evaluate the ALTOIDA™ Platform across multiple study locations. This will demonstrate an ability to perform tests, collect data, and generate classifications irrespective of variations in testing locations and personnel.
12 international study sites will be selected with the US based sites being a recognized NIH Center of Excellence for Alzheimer's disease or other nationally recognized Alzheimer's disease research center. Each site will evaluate up to 60 community dwellers evenly divided between MCI patients and age-matched controls (while the prevalence of AD is approximately 12% in the general population, the ratio of AD to normal among those who visit a clinic for memory or cognitive related issues is between 50-60%).
Each site will follow the same testing protocols. Participants will be asked if they would like to participate in a protocol that monitors their prospective risk for developing ALZ short term, and whether certain of their prescribed medications may have a protective effect. Those who are accepting to be participants are then enrolled in the study.
Enrollees will be tested for risk factors for having pre-clinical ALZ. Individuals identified as being at risk at baseline are followed at 6 month intervals for a 48 month period using psychometric testing and functional neuroimaging. Their maintenance of cognitive stability or cognitive decline is monitored while under the care of their PMD and while taking medications of interest.
All test data will be uploaded to the online ALTOIDA™ database server.
- The overall impact of this study will be increased knowledge concerning the sequence and timing of events leading to MCI and from MCI to AD, development of better clinical and Neuro Motor Index prognosis methods for early detection and for monitoring the progression of these conditions, and facilitation of clinical trials of treatments to slow disease progression, ultimately contributing to the prevention of AD.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (participant, investigator)
- Number of arms
- 2
- Model description
- Adults at high risk of developing ALZ within 18-40 months (MCI) or cognitively normal for their age sex matching group. Risk factors include parents with a history of ALZ, and/or positive APOE4 alleles.
| Arm | Type | Receives |
|---|---|---|
| Prodromal AD (MCI) | Experimental | Other: Altoida: neuropsychological, MRI, EEG and CSF biomarkersAltoida: neuropsychological, MRI, EEG and CSF biomarkers MCI participants will undergo at baseline and every 6 months a neurological examination and a neuropsychological assessment. Alzheimer disease biomarkers' measurements will be performed at inclusion and at the end of the study (or the conversion). |
| Preclinical AD (cognitively normal) | Experimental | Other: Altoida: neuropsychological, MRI, EEG and CSF biomarkersAltoida: neuropsychological, MRI, EEG and CSF biomarkers Cognitively normal participants at risk will undergo at baseline and every 6 months a neurological examination and a neuropsychological assessment. Alzheimer disease biomarkers' measurements will be performed at inclusion and at the end of the study (or the conversion). |
Who may qualify
- Ages
- 55 to 90 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (24 listed)
- Between 55 and 90 years of age
- Study partner to accompany patient to all clinic visits for the duration of the protocol
- Memory complaint by patient and/or study partner
- Abnormal memory function score on Wechsler Memory Scale (adjusted for education)
- Mini-Mental State Exam score between 24 and 30 (inclusive)
Key exclusion criteria (14 listed)
- Any significant neurologic disease other than suspected incipient Alzheimer's disease, such as Parkinson's disease, multi-infarct dementia, Huntington's disease, normal pressure hydrocephalus, brain tumor, progressive supranuclear palsy, seizure disorder, subdural hematoma, multiple sclerosis, or history of significant head trauma followed by persistent neurologic defaults or known structural brain abnormalities
- Screening/baseline MRI scans with evidence of infection, infarction, or other focal lesions; multiple lacunes or lacunes in a critical memory structure
- Presence of pacemakers, aneurysm clips, artificial heart valves, ear implants, metal fragments or foreign objects in the eyes, skin or body
- Major depression, bipolar disorder as described in DSM-IV within the past 1 year
- Psychotic features, agitation or behavioral problems within the last 3 months which could lead to difficulty complying with the protocol
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Altoida: neuropsychological, MRI, EEG and CSF biomarkersData collection at baseline: clinical (neurological, activity of the daily life, instrumental activity of the daily life, depression scale), standard neuropsychological exam, ALTOIDA and neurophysiology (EEG/ERPs) in both Prodromal and Preclinical AD subjects. In both Prodromal and Preclinical AD subjects, APOE genotyping. The local clinical Unit should document the positivity at the baseline session of at least one of the biomarkers of AD mentioned above. Data collection at 6, 12, 24 and 36 months of follow up: clinical (neurological, activity of the daily life, instrumental activity of the daily life, depression scale), standard neuropsychological exam, ALTOIDA and neurophysiology (EEG/ERPs) in both Prodromal and Preclinical AD subjects. | Other | Preclinical AD (cognitively normal), Prodromal AD (MCI) |
Primary outcome
Change in Diagnostic Area Under the Receiver Operating Characteristic Curve (ROC-AUC)
Time frame: approximately 40 months follow up
The machine learning models capturing voice data, hands micromovements \& micro-errors, posture changes, eye tracking, visuospatial navigation micro-errors and spatio-temporal gait parameters developed for the Altoida system will be tested in this prospective cohort. Sensitivity, specificity and accuracy of the model will be tested in differential diagnosis between the study groups as well as the accuracy of prediction cognitive decline as measured by neuropsychological test battery in the MCI group.
29 secondary outcomes
Change From Baseline in Clinical Measure 1
Time frame: baseline, 6, 12, 24, 36 and 42 months of follow up
Change From Baseline in Clinical Measure 2
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Clinical Measure 3
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Clinical Measure 4
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Clinical Measure 5
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Clinical Measure 6
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Clinical Measure 7
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change From Baseline in Cognitive Measure
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Secondary Resting State EEG Endpoints
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Secondary Resting State Auditory Oddball ERP Endpoints
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Total Abeta 1-42 (Aβ42) Amyloid Deposition
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change of Brain Amyloid Deposition
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Change of CSF Biomarkers Tau and ptau181 Values
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
MRI (Optional)
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Changes in Driving Breaking Force
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Changes in Driving Acceleration Velocity
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Changes in Driving Direction
Time frame: baseline, 6, 12, 24, 36 and approximately 40 months follow up
Changes in Driving Violations
Time frame: Continuous measurement for approximately 12 months follow up
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 23 Aug 2024.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Background: PubMed 24656838Tarnanas I, Tsolaki M, Nef T, M Muri R, Mosimann UP. Can a novel computerized cognitive screening test provide additional information for early detection of Alzheimer's disease? Alzheimers Dement. 2014 Nov;10(6):790-8. doi: 10.1016/j.jalz.2014.01.002. Epub 2014 Mar 18.
- Background: PubMed 26736513Vallejo V, Mitache AV, Tarnanas I, Muri R, Mosimann UP, Nef T. Combining qualitative and quantitative methods to analyze serious games outcomes: A pilot study for a new cognitive screening tool. Annu Int Conf IEEE Eng Med Biol Soc. 2015 Aug;2015:1327-30. doi: 10.1109/EMBC.2015.7318613.
- Background: PubMed 26007727Nef T, Urwyler P, Buchler M, Tarnanas I, Stucki R, Cazzoli D, Muri R, Mosimann U. Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data. Sensors (Basel). 2015 May 21;15(5):11725-40. doi: 10.3390/s150511725.
- Background: PubMed 25416111Tarnanas I, Laskaris N, Tsolaki M, Muri R, Nef T, Mosimann UP. On the comparison of a novel serious game and electroencephalography biomarkers for early dementia screening. Adv Exp Med Biol. 2015;821:63-77. doi: 10.1007/978-3-319-08939-3_11.
- Background: PubMed 25954193Tarnanas I, Papagiannopoulos S, Kazis D, Wiederhold M, Widerhold B, Tsolaki M. Reliability of a novel serious game using dual-task gait profiles to early characterize aMCI. Front Aging Neurosci. 2015 Apr 22;7:50. doi: 10.3389/fnagi.2015.00050. eCollection 2015.
- Background: PubMed 26539070Dimitriadis SI, Laskaris NA, Bitzidou MP, Tarnanas I, Tsolaki MN. A novel biomarker of amnestic MCI based on dynamic cross-frequency coupling patterns during cognitive brain responses. Front Neurosci. 2015 Oct 20;9:350. doi: 10.3389/fnins.2015.00350. eCollection 2015.
- Background: PubMed 25658491Tarnanas I, Schlee W, Tsolaki M, Muri R, Mosimann U, Nef T. Ecological validity of virtual reality daily living activities screening for early dementia: longitudinal study. JMIR Serious Games. 2013 Aug 6;1(1):e1. doi: 10.2196/games.2778.
- Background: PubMed 25291458Xekardaki A, Rodriguez C, Montandon ML, Toma S, Tombeur E, Herrmann FR, Zekry D, Lovblad KO, Barkhof F, Giannakopoulos P, Haller S. Arterial spin labeling may contribute to the prediction of cognitive deterioration in healthy elderly individuals. Radiology. 2015 Feb;274(2):490-9. doi: 10.1148/radiol.14140680. Epub 2014 Oct 7.
- Background: PubMed 20634590Woodard JL, Seidenberg M, Nielson KA, Smith JC, Antuono P, Durgerian S, Guidotti L, Zhang Q, Butts A, Hantke N, Lancaster M, Rao SM. Prediction of cognitive decline in healthy older adults using fMRI. J Alzheimers Dis. 2010;21(3):871-85. doi: 10.3233/JAD-2010-091693.
- Background: PubMed 24040166Rizk-Jackson A, Insel P, Petersen R, Aisen P, Jack C, Weiner M. Early indications of future cognitive decline: stable versus declining controls. PLoS One. 2013 Sep 9;8(9):e74062. doi: 10.1371/journal.pone.0074062. eCollection 2013.
- Background: PubMed 23098093Lazarczyk MJ, Hof PR, Bouras C, Giannakopoulos P. Preclinical Alzheimer disease: identification of cases at risk among cognitively intact older individuals. BMC Med. 2012 Oct 25;10:127. doi: 10.1186/1741-7015-10-127.
- Background: PubMed 20847435Haller S, Nguyen D, Rodriguez C, Emch J, Gold G, Bartsch A, Lovblad KO, Giannakopoulos P. Individual prediction of cognitive decline in mild cognitive impairment using support vector machine-based analysis of diffusion tensor imaging data. J Alzheimers Dis. 2010;22(1):315-27. doi: 10.3233/JAD-2010-100840.
- Individual participant dataSharing planned: Undecided. neuromotor data sharing
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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.
Mark Wiederhold, PhD study chair
Scripps Clinic La Jolla Poole Building
Questions about this trial
What is this clinical trial studying?
A study testing Altoida: neuropsychological, MRI, EEG and CSF biomarkers in people with Alzheimer Disease and Mild Cognitive Impairment, run by Altoida.
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 24 inclusion and 14 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: finished, as of the sponsor's last update on 23 Aug 2024. Status can change between updates, so confirm with the study contact before making plans.
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?
Yes. Results are posted in the registry (first posted 16 Dec 2020). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change in Diagnostic Area Under the Receiver Operating Characteristic Curve (ROC-AUC) (time frame: approximately 40 months follow up). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT02843529, which also lists 18 linked publications.
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 23 Aug 2024.