Evaluation of a Computerized Complex Instrumental Activities of Daily Living Marker (NMI)

NCT02843529 | Completed Results DMC

• 1 other identifier: altoidaML01
• Study Type: interventional
• Target: 548
• Locations: 0 countries
• Sites: N/A

Brief 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. 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.

Conditions

Alzheimer Disease; Mild Cognitive Impairment; Memory Disorders; Cognitive Impairment; Dementia; Presymptomatic Disease

Keywords

biomarkers; CSF; EEG; MRI; Digital biomarkers

Outcome Measures

Primary Outcomes (1)

• 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.

  approximately 40 months follow up

Secondary Outcomes (29)

• Change From Baseline in Clinical Measure 1

  baseline, 6, 12, 24, 36 and 42 months of follow up

• Change From Baseline in Clinical Measure 2

  baseline, 6, 12, 24, 36 and approximately 40 months follow up

• Change From Baseline in Clinical Measure 3

  baseline, 6, 12, 24, 36 and approximately 40 months follow up

• Change From Baseline in Clinical Measure 4

  baseline, 6, 12, 24, 36 and approximately 40 months follow up

• Change From Baseline in Clinical Measure 5

  baseline, 6, 12, 24, 36 and approximately 40 months follow up

Study Arms (2)

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).

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).

Other: Altoida: neuropsychological, MRI, EEG and CSF biomarkers

Interventions

Altoida: neuropsychological, MRI, EEG and CSF biomarkers OTHER

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.

Preclinical AD (cognitively normal); Prodromal AD (MCI)

Eligibility Criteria

• Age: 55 Years - 90 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• 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
• 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

You may not qualify if:

• 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
• 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
• Use of investigational agents one month prior to entry and for the duration of the trial
• Exceptions to these guidelines may be considered on a case-by-case basis at the discretion of the protocol director

Sponsors & Collaborators

• Altoida: lead
• Greek Alzheimer's Association and Related Disorders: collaborator
• University of Roma La Sapienza: collaborator
• IRCCS Centro San Giovanni di Dio Fatebenefratelli: collaborator
• Neuromed IRCCS: collaborator
• Scripps Health: collaborator
• Global Brain Health Institute (GBHI): collaborator
• Takeda Pharmaceuticals International, Inc.: collaborator
• Research Center on Computational BioMarkers: collaborator
• Bioinformatics and Human Electrophysiology Laboratory: collaborator
• Fundacion Clinic per a la Recerca Biomédica: collaborator
• University of Dublin, Trinity College: collaborator
• University of Barcelona: collaborator
• EIT Health: collaborator
• Klinik Hirslanden, Zurich: collaborator
• The University of Texas at Dallas: collaborator

Related Publications (18)

• 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.

  PMID: 24656838 BACKGROUND

• Vallejo 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.

  PMID: 26736513 BACKGROUND

• Nef 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.

  PMID: 26007727 BACKGROUND

• Tarnanas 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.

  PMID: 25416111 BACKGROUND

• Tarnanas 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.

  PMID: 25954193 BACKGROUND

• Dimitriadis 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.

  PMID: 26539070 BACKGROUND

• Tarnanas 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.

  PMID: 25658491 BACKGROUND

• Xekardaki 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.

  PMID: 25291458 BACKGROUND

• Woodard 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.

  PMID: 20634590 BACKGROUND

• Rizk-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.

  PMID: 24040166 BACKGROUND

• Lazarczyk 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.

  PMID: 23098093 BACKGROUND

• Haller 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.

  PMID: 20847435 BACKGROUND

• Green 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.

  PMID: 25499536 BACKGROUND

• Christensen 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.

  PMID: 26810768 BACKGROUND

• Galluzzi 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.

  PMID: 26940242 BACKGROUND

• Cavedo E, Lista S, Khachaturian Z, Aisen P, Amouyel P, Herholz K, Jack CR Jr, Sperling R, Cummings J, Blennow K, O'Bryant S, Frisoni GB, Khachaturian A, Kivipelto M, Klunk W, Broich K, Andrieu S, de Schotten MT, Mangin JF, Lammertsma AA, Johnson K, Teipel S, Drzezga A, Bokde A, Colliot O, Bakardjian H, Zetterberg H, Dubois B, Vellas B, Schneider LS, Hampel H. The Road Ahead to Cure Alzheimer's Disease: Development of Biological Markers and Neuroimaging Methods for Prevention Trials Across all Stages and Target Populations. J Prev Alzheimers Dis. 2014 Dec;1(3):181-202. doi: 10.14283/jpad.2014.32.

  PMID: 26478889 BACKGROUND

• Tarnanas I, Tsolaki A, Wiederhold M, Wiederhold B, Tsolaki M. Five-year biomarker progression variability for Alzheimer's disease dementia prediction: Can a complex instrumental activities of daily living marker fill in the gaps? Alzheimers Dement (Amst). 2015 Nov 14;1(4):521-32. doi: 10.1016/j.dadm.2015.10.005. eCollection 2015 Dec.

  PMID: 27239530 BACKGROUND

• Buegler M, Harms R, Balasa M, Meier IB, Exarchos T, Rai L, Boyle R, Tort A, Kozori M, Lazarou E, Rampini M, Cavaliere C, Vlamos P, Tsolaki M, Babiloni C, Soricelli A, Frisoni G, Sanchez-Valle R, Whelan R, Merlo-Pich E, Tarnanas I. Digital biomarker-based individualized prognosis for people at risk of dementia. Alzheimers Dement (Amst). 2020 Aug 19;12(1):e12073. doi: 10.1002/dad2.12073. eCollection 2020.

  PMID: 32832589 RESULT

MeSH Terms

Conditions

Alzheimer Disease; Cognitive Dysfunction; Memory Disorders; Dementia; Asymptomatic Diseases

Interventions

Magnetic Resonance Spectroscopy

Condition Hierarchy (Ancestors)

Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Tauopathies; Neurodegenerative Diseases; Neurocognitive Disorders; Mental Disorders; Cognition Disorders; Neurobehavioral Manifestations; Neurologic Manifestations; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Disease Attributes; Pathologic Processes

Intervention Hierarchy (Ancestors)

Spectrum Analysis; Chemistry Techniques, Analytical; Investigative Techniques

Results Point of Contact

• Title: Ioannis Tarnanas
• Organization: Altoida Inc.

Ioannis@altoida.com

+18325975076

Study Officials

• Mark Wiederhold, PhD

  Scripps Clinic La Jolla Poole Building

  STUDY CHAIR

Publication Agreements

• PI is Sponsor Employee: Yes

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: PARTICIPANT, INVESTIGATOR
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Model Details: 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.

Study Record Dates

• First Submitted: May 18, 2016
• First Posted: July 26, 2016
• Study Start: October 17, 2016
• Primary Completion: February 18, 2020
• Study Completion: February 21, 2020
• Last Updated: August 23, 2024
• Results First Posted: December 16, 2020

Record last verified: 2024-07