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| Name | Class |
|---|---|
| Institute for Systems Biology | OTHER |
| St. Joseph's Healthcare Foundation | OTHER |
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The PREVENTION Trial is a 12-month, two-arm randomized clinical trial (RCT) in adults 50-80 years old experiencing cognitive decline. Our study clinicians will refer patients for enrollment based on three categories: 1) a diagnosis of mild AD according to criteria established by the National Institute of Neurological and Communicative Disorders and Stroke (AD and Related Disorders Association [NINCDS-ADRDA]), 2) those with mild cognitive impairment will be diagnosed according to the Petersen method, and 3) subjective memory impairment as assessed by neuropsychological assessments and self-report. Enrollment will require evidence of AD pathophysiological processes (as defined by a positive amyloid positron emission tomography (PET) scan).
The first objective is to evaluate the efficacy of a coached, data-driven, multi-modal lifestyle intervention to treat cognitive decline. Subjects will be randomized into one of two groups: Group 1 (Active Control) or Group 2 (Intervention). Group 1 (Data-driven clinical recommendations (CR)) will serve as the active control group and will receive data-driven clinical recommendations by a study physician based on study assessments and clinical lab values. Group 2 (Data-driven multi-modal intervention with coaching (MMIC)) will receive the same clinical recommendations and also an intensive multi-modal intervention with health coaching, support and resources to carry out these recommendations. This includes health coaching sessions (with an RDN), dietary counseling sessions (with an RDN), and group cognitive and physical exercise classes (CogFit) with a certified personal trainer and a computer-based neurocognitive program at home. Both groups will be measured for treatment related changes in cognitive and functional abilities, quality of life, biological, and biochemical measures.
The second objective is to analyze longitudinal multi-omic data, including metabolomics, proteomics, genetics, microbiome, behavior and cognition into personalized, dense, dynamic data (i.e. PD3) from individuals with cognitive decline and underlying Alzheimer's neuropathology. The goal analysis is to identify models of causation that can further advance knowledge and research in neurodegenerative disorders and healthy living.
Subject identification and recruitment - All participants will be recruited from the Pacific Brain Health Center in Santa Monica, which is a high-volume memory-care and dementia outpatient clinic within a large physician medical group affiliated with Providence Saint John's Health Center. 60 participants will be randomized into the RCT, with 30 in each treatment arm.
Procedures for Obtaining Informed Consent - All participants will receive the Experimental Research Subject's Bill of Rights prior to signing the informed consent form (ICF), authorization of use and disclosure of protected health information (PHI), and authorization of medical record release for the subject's treating physician, will be obtained from each participants prior to enrolling in the study. A copy of all signed ICF's will be given to the participants, and the investigator will retain the original.
A Functional Assessment Staging Test (FAST) will be done before participants are consented to determine whether they or a legally appointed representative (LAR) can consent to participate in the study. In this study, participants with FAST stages 2-4 will be recruited (see Inclusion Criteria).
Considerations for consenting: FAST Stages 2-3 Participants - FAST stages 2-3 participants are usually capable of making medical and legal decisions, and will be consented directly, unless there is a caregiver, legally appointed representative, or other reason to think that an informed consent cannot be given by the participants without approval by a reliable informant acting on their behalf.
Considerations for consenting: FAST Stage 4 (mild dementia) Participants - FAST stage 4 participants will be consented by having them give oral or written assent, indicating their preference with regard to study participation. In addition, the caregiver or legally appointed representative of a demented participants will be consented to assure full understanding of study procedures and willingness on behalf of the participants to participate in the study.
The consenting approach for patients with cognitive impairment has been evaluated by the Department of Psychiatry and Behavioral Sciences at Johns Hopkins, and found to adequately ensure informed consent. They concluded that ADRD participants should not be excluded from study participation if they cannot directly consent themselves, so long as their caregivers can consent, and the participants can assent, either verbally or in writing, their preference to participate in the study.
The caregiver or legally appointed representative will be required to accompany participants to participate in the required procedures. A copy of the appropriate document (e.g., the power of attorney for healthcare) will be obtained and filed with the original ICF.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Group 1 - Data-driven clinical recommendations (CR) | Active Comparator | Data-driven clinical recommendations (CR) |
|
| Group 2 - Data-driven coached multi-modal intervention (MMIC) | Experimental | Data-driven coached multi-modal intervention (MMIC) |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Data-Driven Clinical Recommendations | Behavioral | Data-driven clinical recommendations. Participants will receive routine care with data-driven, personalized, multi-modal clinical recommendations by a study physician based on study assessments and clinical lab values and be monitored and re-assessed for a period of 12 months. |
| Measure | Description | Time Frame |
|---|---|---|
| NIH ToolBox Cognition Function Battery - Cognitive Function Composite Score | To test the hypothesis that high contact coaching is better than no coaching for people in the early stages and at risk for cognitive decline. We plan to test that after one year of coached data-driven personalized interventions, participants in the coaching (CDDCR) (Group 2) will have less cognitive decline than the non-coaching (DDCR) arm (Group 1) as measured by the NIH ToolBox Cognition Function Battery (NIHTB-CB). The Cognitive Function Composite Score will be our primary outcome measure for cognitive function. The NIHTB-CB contains seven computer-based instruments assessing five cognitive sub-domains: Language, Executive Function, Episodic Memory, Processing Speed, and Working Memory. The Composite Score is calculated using all seven subsets of the NIHTB-CB. Participants will be assessed at baseline and one year. | 1 year |
| RAVLT (Rey's Auditory Verbal Learning Test) score | To test the hypothesis that high contact coaching is better than no coaching for people in the early stages and at risk for cognitive decline. We plan to test that after one year of coached data-driven personalized interventions, participants in the coaching (CDDCR) (Group 2) will have less cognitive decline than the non-coaching (DDCR) arm (Group 1) as measured by the he Rey Auditory Verbal Learning Test (RAVLT). The RAVLT is a test derived for assessing verbal learning and memory. The RAVLT will be used to evaluate the changes in memory function of participants in the two different arms. Participants will be assessed at baseline and one year. Changes in RAVLT learn and recall scores will be used to assess changes in cognitive function. | 1 year |
| Hippocampal Volume | To test the hypothesis that high contact coaching is better than no coaching for people in the early stages and at risk for cognitive decline. We plan to test that after one year of coached data-driven personalized interventions, participants in the coaching (CDDCR) (Group 2) will have less hippocampal volume decline than the non-coaching (DDCR) arm (Group 1) as measured by the structural magnetic resonance imaging (MRI). Participants will be assessed at baseline and one year. |
| Measure | Description | Time Frame |
|---|---|---|
| Blood Urine Nitrogen | To test the hypothesis that high contact coaching is better than no coaching for people in the early stages and at risk for cognitive decline. We plan to test that after one year of coached data-driven personalized interventions, participants in the coaching (CDDCR) (Group 2) will have lower blood urea levels (BUN) than the non-coaching (DDCR) arm (Group 1) as measured by the plasma BUN. Participants will be assessed at baseline and one year. |
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Inclusion Criteria
Exclusion Criteria
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Pacific Brain Health Center | Santa Monica | California | 90404 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 21775213 | Background | Barnes DE, Yaffe K. The projected effect of risk factor reduction on Alzheimer's disease prevalence. Lancet Neurol. 2011 Sep;10(9):819-28. doi: 10.1016/S1474-4422(11)70072-2. Epub 2011 Jul 19. | |
| 20094021 | Background | Black BS, Rabins PV, Sugarman J, Karlawish JH. Seeking assent and respecting dissent in dementia research. Am J Geriatr Psychiatry. 2010 Jan;18(1):77-85. doi: 10.1097/JGP.0b013e3181bd1de2. |
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| ID | Term |
|---|---|
| D000544 | Alzheimer Disease |
| D060825 | Cognitive Dysfunction |
| ID | Term |
|---|---|
| D003704 | Dementia |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
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Participants will be assigned with a participant identification number (ID), so that data will not be identified by any names or personally identifiable information. This ID will be used throughout this study.
|
| Coached Data-Driven Clinical Recommendations | Behavioral | Data-driven multi-modal lifestyle intervention with coaching. Participants will receive coached routine care with data-driven, personalized, multimodal recommendations. MMIC participants will receive an intensive multi-modal intervention with health coaching, support and resources to carry out these recommendations. This additional intervention services include: 13 personal, data-driven brain health coaching sessions (with an RDN), 7 personal dietary counseling sessions (with an RDN), 33 group-based cognitive and physical exercise classes (CogFit) with a certified personal trainer and a computer-based neurocognitive program at home and be monitored and re-assessed for a period of 12 months. |
|
| 1 year |
| 1 year |
| 9502356 | Background | Friedenreich CM, Courneya KS, Bryant HE. The lifetime total physical activity questionnaire: development and reliability. Med Sci Sports Exerc. 1998 Feb;30(2):266-74. doi: 10.1097/00005768-199802000-00015. |
| 16925881 | Background | Hagstromer M, Oja P, Sjostrom M. The International Physical Activity Questionnaire (IPAQ): a study of concurrent and construct validity. Public Health Nutr. 2006 Sep;9(6):755-62. doi: 10.1079/phn2005898. |
| 28744111 | Background | Park YH, Moon SH, Ha JY, Lee MH. The long-term effects of the health coaching self-management program for nursing-home residents. Clin Interv Aging. 2017 Jul 11;12:1079-1088. doi: 10.2147/CIA.S137821. eCollection 2017. |
| 18302232 | Background | Jack CR Jr, Bernstein MA, Fox NC, Thompson P, Alexander G, Harvey D, Borowski B, Britson PJ, L Whitwell J, Ward C, Dale AM, Felmlee JP, Gunter JL, Hill DL, Killiany R, Schuff N, Fox-Bosetti S, Lin C, Studholme C, DeCarli CS, Krueger G, Ward HA, Metzger GJ, Scott KT, Mallozzi R, Blezek D, Levy J, Debbins JP, Fleisher AS, Albert M, Green R, Bartzokis G, Glover G, Mugler J, Weiner MW. The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI methods. J Magn Reson Imaging. 2008 Apr;27(4):685-91. doi: 10.1002/jmri.21049. |
| 7069156 | Background | Pfeffer RI, Kurosaki TT, Harrah CH Jr, Chance JM, Filos S. Measurement of functional activities in older adults in the community. J Gerontol. 1982 May;37(3):323-9. doi: 10.1093/geronj/37.3.323. |
| 28714965 | Background | Price ND, Magis AT, Earls JC, Glusman G, Levy R, Lausted C, McDonald DT, Kusebauch U, Moss CL, Zhou Y, Qin S, Moritz RL, Brogaard K, Omenn GS, Lovejoy JC, Hood L. A wellness study of 108 individuals using personal, dense, dynamic data clouds. Nat Biotechnol. 2017 Aug;35(8):747-756. doi: 10.1038/nbt.3870. Epub 2017 Jul 17. |
| 26633093 | Background | Thom DH, Hessler D, Willard-Grace R, DeVore D, Prado C, Bodenheimer T, Chen EH. Health coaching by medical assistants improves patients' chronic care experience. Am J Manag Care. 2015 Oct;21(10):685-91. |
| 25755034 | Background | Willard-Grace R, Chen EH, Hessler D, DeVore D, Prado C, Bodenheimer T, Thom DH. Health coaching by medical assistants to improve control of diabetes, hypertension, and hyperlipidemia in low-income patients: a randomized controlled trial. Ann Fam Med. 2015 Mar;13(2):130-8. doi: 10.1370/afm.1768. |
| 25030513 | Background | Norton S, Matthews FE, Barnes DE, Yaffe K, Brayne C. Potential for primary prevention of Alzheimer's disease: an analysis of population-based data. Lancet Neurol. 2014 Aug;13(8):788-94. doi: 10.1016/S1474-4422(14)70136-X. |
| 29016550 | Background | Slavich GM, Shields GS. Assessing Lifetime Stress Exposure Using the Stress and Adversity Inventory for Adults (Adult STRAIN): An Overview and Initial Validation. Psychosom Med. 2018 Jan;80(1):17-27. doi: 10.1097/PSY.0000000000000534. |
| 10391658 | Background | Washburn RA, McAuley E, Katula J, Mihalko SL, Boileau RA. The physical activity scale for the elderly (PASE): evidence for validity. J Clin Epidemiol. 1999 Jul;52(7):643-51. doi: 10.1016/s0895-4356(99)00049-9. |
| 20693631 | Background | Hansmannel F, Sillaire A, Kamboh MI, Lendon C, Pasquier F, Hannequin D, Laumet G, Mounier A, Ayral AM, DeKosky ST, Hauw JJ, Berr C, Mann D, Amouyel P, Campion D, Lambert JC. Is the urea cycle involved in Alzheimer's disease? J Alzheimers Dis. 2010;21(3):1013-21. doi: 10.3233/JAD-2010-100630. |
| 6610841 | Background | McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease. Neurology. 1984 Jul;34(7):939-44. doi: 10.1212/wnl.34.7.939. |
| 10190820 | Background | Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E. Mild cognitive impairment: clinical characterization and outcome. Arch Neurol. 1999 Mar;56(3):303-8. doi: 10.1001/archneur.56.3.303. |
| D024801 |
| Tauopathies |
| D019636 | Neurodegenerative Diseases |
| D019965 | Neurocognitive Disorders |
| D001523 | Mental Disorders |
| D003072 | Cognition Disorders |