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Arias JJ, Tyler AM, Beskow LM, Carillo MC, Dickinson S, Goldman J, Majumder MA, Mello MM, Snyder HM, Yokoyama JS. Data stewardship in FTLD research: Investigator and research participant views. Alzheimers Dement 2024; 20:2886-2893. [PMID: 38456576 PMCID: PMC11032535 DOI: 10.1002/alz.13719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 12/26/2023] [Accepted: 01/04/2024] [Indexed: 03/09/2024]
Abstract
INTRODUCTION Federal policies and guidelines have expanded the return of individual results to participants and expectations for data sharing between investigators and through repositories. Here, we report investigators' and study participants' views and experiences with data stewardship practices within frontotemporal lobal degeneration (FTLD) research, which reveal unique ethical challenges. METHODS Semi-structured interviews with (1) investigators conducting FTLD research that includes genetic data collection and/or analysis and (2) participants enrolled in a single site longitudinal FTLD study. RESULTS Analysis of the interviews identified three meta themes: perspectives on data sharing, experiences with enrollment and participation, and data management and security as mechanisms for participant protections. DISCUSSION This study identified a set of preliminary gaps and needs regarding data stewardship within FTLD research. The results offer initial insights on ethical challenges to data stewardship aimed at informing future guidelines and policies.
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Affiliation(s)
- Jalayne J. Arias
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
- Department of Health Policy & Behavioral SciencesSchool of Public HealthGeorgia State UniversityAtlantaGeorgiaUSA
| | - Ana M. Tyler
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Laura M. Beskow
- Center for Biomedical Ethics and SocietyVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Maria C. Carillo
- Division of Medical & Scientific RelationsAlzheimer's AssociationChicagoIllinoisUSA
| | - Susan Dickinson
- The Association for Frontotemporal DegenerationKing of PrussiaPennsylvaniaUSA
| | - Jill Goldman
- Neurological InstituteColumbia University Irving Medical CenterNew YorkNew YorkUSA
| | - Mary A. Majumder
- Center for Medical Ethics and Health PolicyBaylor College of MedicineHoustonTexasUSA
| | - Michelle M. Mello
- Stanford Law School and Department of MedicineStanford UniversityPalo AltoCaliforniaUSA
| | - Heather M. Snyder
- Division of Medical & Scientific RelationsAlzheimer's AssociationChicagoIllinoisUSA
| | - Jennifer S. Yokoyama
- Memory and Aging CenterDepartment of NeurologyWeill Institute for NeurosciencesUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
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Riviere M, Langbaum JB, Turner RS, Rinne JO, Sui Y, Cazorla P, Ricart J, Meneses K, Caputo A, Tariot PN, Reiman EM, Graf A. Effects of the active amyloid beta immunotherapy CAD106 on PET measurements of amyloid plaque deposition in cognitively unimpaired APOE ε4 homozygotes. Alzheimers Dement 2024; 20:1839-1850. [PMID: 38145469 PMCID: PMC10984441 DOI: 10.1002/alz.13532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 10/04/2023] [Accepted: 10/11/2023] [Indexed: 12/26/2023]
Abstract
INTRODUCTION Alzheimer's Prevention Initiative Generation Study 1 evaluated amyloid beta (Aβ) active immunotherapy (vaccine) CAD106 and BACE-1 inhibitor umibecestat in cognitively unimpaired 60- to 75-year-old participants at genetic risk for Alzheimer's disease (AD). The study was reduced in size and terminated early. Results from the CAD106 cohort are presented. METHODS Sixty-five apolipoprotein E ε4 homozygotes with/without amyloid deposition received intramuscular CAD106 450 μg (n = 42) or placebo (n = 23) at baseline; Weeks 1, 7, 13; and quarterly; 51 of them had follow-up Aβ positron emission tomography (PET) scans at 18 to 24 months. RESULTS CAD106 induced measurable serum Aβ immunoglobulin G titers in 41/42 participants, slower rates of Aβ plaque accumulation (mean [standard deviation] annualized change from baseline in amyloid PET Centiloid: -0.91[5.65] for CAD106 versus 8.36 [6.68] for placebo; P < 0.001), and three amyloid-related imaging abnormality cases (one symptomatic). DISCUSSION Despite early termination, these findings support the potential value of conducting larger prevention trials of Aβ active immunotherapies in individuals at risk for AD. HIGHLIGHTS This was the first amyloid-lowering prevention trial in persons at genetic risk of late-onset Alzheimer's disease (AD). Active immunotherapy targeting amyloid (CAD106) was tested in this prevention trial. CAD106 significantly slowed down amyloid plaque deposition in apolipoprotein E homozygotes. CAD106 was generally safe and well tolerated, with only three amyloid-related imaging abnormality cases (one symptomatic). Such an approach deserves further evaluation in larger AD prevention trials.
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Affiliation(s)
| | | | - R. Scott Turner
- Department of NeurologyGeorgetown University Medical CenterWashingtonDistrict of ColumbiaUSA
| | - Juha O. Rinne
- Turku PET CentreUniversity of Turku and Turku University HospitalTurkuFinland
- Department of NeurologyCRST – Clinical Research Services TurkuTurkuFinland
| | - Yihan Sui
- Clinical Development, NeuroscienceNovartis PharmaceuticalsEast HanoverNew JerseyUSA
| | - Pilar Cazorla
- Clinical Development, NeuroscienceNovartis PharmaceuticalsEast HanoverNew JerseyUSA
| | - Javier Ricart
- Clinical Development, NeuroscienceNovartis Farmaceutica SABarcelonaSpain
| | - Kathleen Meneses
- Clinical Development, NeuroscienceNovartis PharmaceuticalsEast HanoverNew JerseyUSA
| | - Angelika Caputo
- Clinical Development, NeuroscienceNovartis Pharma AGBaselSwitzerland
| | | | | | - Ana Graf
- Clinical Development, NeuroscienceNovartis Pharma AGBaselSwitzerland
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Reiman EM, Pruzin JJ, Rios-Romenets S, Brown C, Giraldo M, Acosta-Baena N, Tobon C, Hu N, Chen Y, Ghisays V, Enos J, Goradia DD, Lee W, Luo J, Malek-Ahmadi M, Protas H, Thomas RG, Chen K, Su Y, Boker C, Mastroeni D, Alvarez S, Quiroz YT, Langbaum JB, Sink KM, Lopera F, Tariot PN. A public resource of baseline data from the Alzheimer's Prevention Initiative Autosomal-Dominant Alzheimer's Disease Trial. Alzheimers Dement 2023; 19:1938-1946. [PMID: 36373344 PMCID: PMC10262848 DOI: 10.1002/alz.12843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 09/01/2022] [Accepted: 10/05/2022] [Indexed: 11/16/2022]
Abstract
INTRODUCTION The Alzheimer's Prevention Initiative Autosomal-Dominant Alzheimer's Disease (API ADAD) Trial evaluated the anti-oligomeric amyloid beta (Aβ) antibody therapy crenezumab in cognitively unimpaired members of the Colombian presenilin 1 (PSEN1) E280A kindred. We report availability, methods employed to protect confidentiality and anonymity of participants, and process for requesting and accessing baseline data. METHODS We developed mechanisms to share baseline data from the API ADAD Trial in consultation with experts and other groups sharing data from Alzheimer's disease (AD) prevention trials, balancing the need to protect anonymity and trial integrity with making data broadly available to accelerate progress in the field. We pressure-tested deliberate and inadvertent potential threats under specific assumptions, employed a system to suppress or mask both direct and indirect identifying variables, limited and firewalled data managers, and put forth specific principles requisite to receive data. RESULTS Baseline demographic, PSEN1 E280A and apolipoprotein E genotypes, florbetapir and fluorodeoxyglucose positron emission tomography, magnetic resonance imaging, clinical, and cognitive data can now be requested by interested researchers. DISCUSSION Baseline data are publicly available; treatment data and biological samples, including baseline and treatment-related blood-based biomarker data will become available in accordance with our original trial agreement and subsequently developed Collaboration for Alzheimer's Prevention principles. Sharing of these data will allow exploration of important questions including the differential effects of initiating an investigational AD prevention therapy both before as well as after measurable Aβ plaque deposition.
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Affiliation(s)
- Eric M. Reiman
- Banner Alzheimer’s Institute, Phoenix, AZ, USA
- University of Arizona College of Medicine, Phoenix, AZ, USA
| | - Jeremy J. Pruzin
- Banner Alzheimer’s Institute, Phoenix, AZ, USA
- University of Arizona College of Medicine, Phoenix, AZ, USA
| | | | - Chris Brown
- Banner Alzheimer’s Institute, Phoenix, AZ, USA
| | - Margarita Giraldo
- Grupo de Neurociencias de la Universidad de Antioquia, Medellin, Colombia
| | | | - Carlos Tobon
- Grupo de Neurociencias de la Universidad de Antioquia, Medellin, Colombia
| | - Nan Hu
- Genentech Inc., South San Francisco, CA, USA
| | | | | | | | | | - Wendy Lee
- Banner Alzheimer’s Institute, Phoenix, AZ, USA
| | - Ji Luo
- Banner Alzheimer’s Institute, Phoenix, AZ, USA
| | | | | | | | - Kewei Chen
- Banner Alzheimer’s Institute, Phoenix, AZ, USA
| | - Yi Su
- Banner Alzheimer’s Institute, Phoenix, AZ, USA
| | | | - Diego Mastroeni
- ASU-Banner Neurodegenerative Research Center, Biodesign Institute, Arizona State University, Tempe, AZ, USA
| | | | - Yakeel T. Quiroz
- Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Jessica B. Langbaum
- Banner Alzheimer’s Institute, Phoenix, AZ, USA
- University of Arizona College of Medicine, Phoenix, AZ, USA
| | | | - Francisco Lopera
- Grupo de Neurociencias de la Universidad de Antioquia, Medellin, Colombia
| | - Pierre N. Tariot
- Banner Alzheimer’s Institute, Phoenix, AZ, USA
- University of Arizona College of Medicine, Phoenix, AZ, USA
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Xu X, Lin L, Sun S, Wu S. A review of the application of three-dimensional convolutional neural networks for the diagnosis of Alzheimer's disease using neuroimaging. Rev Neurosci 2023:revneuro-2022-0122. [PMID: 36729918 DOI: 10.1515/revneuro-2022-0122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 01/02/2023] [Indexed: 02/03/2023]
Abstract
Alzheimer's disease (AD) is a degenerative disorder that leads to progressive, irreversible cognitive decline. To obtain an accurate and timely diagnosis and detect AD at an early stage, numerous approaches based on convolutional neural networks (CNNs) using neuroimaging data have been proposed. Because 3D CNNs can extract more spatial discrimination information than 2D CNNs, they have emerged as a promising research direction in the diagnosis of AD. The aim of this article is to present the current state of the art in the diagnosis of AD using 3D CNN models and neuroimaging modalities, focusing on the 3D CNN architectures and classification methods used, and to highlight potential future research topics. To give the reader a better overview of the content mentioned in this review, we briefly introduce the commonly used imaging datasets and the fundamentals of CNN architectures. Then we carefully analyzed the existing studies on AD diagnosis, which are divided into two levels according to their inputs: 3D subject-level CNNs and 3D patch-level CNNs, highlighting their contributions and significance in the field. In addition, this review discusses the key findings and challenges from the studies and highlights the lessons learned as a roadmap for future research. Finally, we summarize the paper by presenting some major findings, identifying open research challenges, and pointing out future research directions.
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Affiliation(s)
- Xinze Xu
- Intelligent Physiological Measurement and Clinical Translation, Beijing International Platform for Scientific and Technological Cooperation, Department of Biomedical Engineering, Faculty of Environment and Life Sciences, Beijing University of Technology, Beijing 100124, China
| | - Lan Lin
- Intelligent Physiological Measurement and Clinical Translation, Beijing International Platform for Scientific and Technological Cooperation, Department of Biomedical Engineering, Faculty of Environment and Life Sciences, Beijing University of Technology, Beijing 100124, China
| | - Shen Sun
- Intelligent Physiological Measurement and Clinical Translation, Beijing International Platform for Scientific and Technological Cooperation, Department of Biomedical Engineering, Faculty of Environment and Life Sciences, Beijing University of Technology, Beijing 100124, China
| | - Shuicai Wu
- Intelligent Physiological Measurement and Clinical Translation, Beijing International Platform for Scientific and Technological Cooperation, Department of Biomedical Engineering, Faculty of Environment and Life Sciences, Beijing University of Technology, Beijing 100124, China
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Gietl AF, Frisoni GB. Early termination of pivotal trials in Alzheimer's disease-Preserving optimal value for participants and science. Alzheimers Dement 2022; 18:1980-1987. [PMID: 35220681 PMCID: PMC9790521 DOI: 10.1002/alz.12605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 12/14/2021] [Accepted: 01/03/2022] [Indexed: 01/28/2023]
Abstract
Participants in Alzheimer's disease late-phase clinical trials are frequently confronted with a situation of early termination. We discuss measures to protect the perceived value of study participation and to maximize the scientific value under such circumstances. A communication strategy should ensure that trial participants maintain a positive relationship with the research team and have their informational needs optimally met. Measures to maximize the scientific value may include data/sample sharing, strategies for personalized medicine, as well as scientific follow-up. Critical for the success of such a concept are networks of excellence, extending models of existing initiatives like Global Alzheimer's Platform Foundation Network (GAP-Net). These networks could fundamentally strengthen the role of clinical investigators if they decide on their involvement in trials based upon their estimation of the scientific value and benefit for the participants, actively contribute to scientific analyses, and mediate optimal communication among the relevant trial stakeholders.
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Affiliation(s)
- Anton F. Gietl
- Institute for Regenerative Medicine, Center for Prevention and Dementia TherapyUniversity of ZurichSchlierenSwitzerland,University Hospital for Geriatric PsychiatrySwitzerland
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Turner EC, Gantman EC, Sampaio C, Sivakumaran S. Huntington's Disease Regulatory Science Consortium: Accelerating Medical Product Development. J Huntingtons Dis 2022; 11:97-104. [PMID: 35466945 DOI: 10.3233/jhd-220533] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Huntington's disease (HD) is a devastating neurodegenerative disorder that urgently needs disease-modifying therapeutics. To this end, collaboration to standardize clinical research practices in the field and drive progress in addressing drug development challenges is paramount. At a meeting in 2017 organized by CHDI Foundation and the Critical Path Institute, stakeholders across the pharmaceutical industry, academia, regulatory agencies, and patient advocacy groups discussed the need for and potential impact of a consortium dedicated to HD regulatory science. Consequently, the Huntington's Disease Regulatory Science Consortium (HD-RSC) was formed, a precompetitive consortium that is dedicated to building a regulatory strategy to expedite the approval of HD therapeutics.
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Keret O, Staffaroni AM, Ringman JM, Cobigo Y, Goh SM, Wolf A, Allen IE, Salloway S, Chhatwal J, Brickman AM, Reyes‐Dumeyer D, Bateman RJ, Benzinger TL, Morris JC, Ances BM, Joseph‐Mathurin N, Perrin RJ, Gordon BA, Levin J, Vöglein J, Jucker M, la Fougère C, Martins RN, Sohrabi HR, Taddei K, Villemagne VL, Schofield PR, Brooks WS, Fulham M, Masters CL, Ghetti B, Saykin AJ, Jack CR, Graff‐Radford NR, Weiner M, Cash DM, Allegri RF, Chrem P, Yi S, Miller BL, Rabinovici GD, Rosen HJ. Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12197. [PMID: 34258377 PMCID: PMC8256623 DOI: 10.1002/dad2.12197] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 04/13/2021] [Indexed: 01/18/2023]
Abstract
INTRODUCTION Asymptomatic and mildly symptomatic dominantly inherited Alzheimer's disease mutation carriers (DIAD-MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD-MC and could help predict risk for dementia during trial enrollment. METHODS We created a dementia risk score by entering standardized gray-matter volumes from 231 DIAD-MC into a logistic regression to classify participants with and without dementia. The score's predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD-MC followed longitudinally. RESULTS Our risk score separated asymptomatic versus demented DIAD-MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%-98.2%]) and improved prediction beyond established methods based on familial age of onset. DISCUSSION Individualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD-MC participants for prevention trials.
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Affiliation(s)
- Ophir Keret
- Global Brain Health InstituteUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Adam M. Staffaroni
- Department of Neurology, Memory and Aging CenterUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - John M. Ringman
- Alzheimer's Disease Research Center, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Yann Cobigo
- Department of Neurology, Memory and Aging CenterUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Sheng‐Yang M. Goh
- Department of Neurology, Memory and Aging CenterUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Amy Wolf
- Department of Neurology, Memory and Aging CenterUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Isabel Elaine Allen
- Global Brain Health InstituteUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of Epidemiology and BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Stephen Salloway
- Warren Alpert Medical SchoolBrown UniversityProvidenceRhode IslandUSA
| | - Jasmeer Chhatwal
- Massachusetts General Hospital, Harvard Medical School BostonBostonMassachusettsUSA
| | - Adam M. Brickman
- Taub Institute for Research on Alzheimer's Disease and the Aging BrainColumbia UniversityNew YorkNew YorkUSA
| | - Dolly Reyes‐Dumeyer
- Taub Institute for Research on Alzheimer's Disease and the Aging BrainColumbia UniversityNew YorkNew YorkUSA
| | - Randal J. Bateman
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Neuropathology, Department of Pathology & ImmunologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Biostatistics, Department of PsychiatryWashington University in St. Louis School of MedicineSt. LouisMissouriUSA
| | - Tammie L.S. Benzinger
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
| | - John C. Morris
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Neuropathology, Department of Pathology & ImmunologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Biostatistics, Department of PsychiatryWashington University in St. Louis School of MedicineSt. LouisMissouriUSA
| | - Beau M. Ances
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Neuropathology, Department of Pathology & ImmunologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Biostatistics, Department of PsychiatryWashington University in St. Louis School of MedicineSt. LouisMissouriUSA
| | - Nelly Joseph‐Mathurin
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Neuropathology, Department of Pathology & ImmunologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Biostatistics, Department of PsychiatryWashington University in St. Louis School of MedicineSt. LouisMissouriUSA
| | - Richard J. Perrin
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Neuropathology, Department of Pathology & ImmunologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Biostatistics, Department of PsychiatryWashington University in St. Louis School of MedicineSt. LouisMissouriUSA
| | - Brian A. Gordon
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Neuropathology, Department of Pathology & ImmunologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Biostatistics, Department of PsychiatryWashington University in St. Louis School of MedicineSt. LouisMissouriUSA
| | - Johannes Levin
- German Center for Neurodegenerative Diseases (DZNE)MunichGermany
- Department of NeurologyLudwig‐Maximilians‐Universität MünchenMunichGermany
| | - Jonathan Vöglein
- German Center for Neurodegenerative Diseases (DZNE)MunichGermany
- Department of NeurologyLudwig‐Maximilians‐Universität MünchenMunichGermany
| | - Mathias Jucker
- German Center for Neurodegenerative Diseases (DZNE)TübingenGermany
- Department of Neurodegenerative Diseases, Hertie Institute for Clinical Brain ResearchUniversity of TübingenTübingenGermany
| | - Christian la Fougère
- German Center for Neurodegenerative Diseases (DZNE)TübingenGermany
- Institute for Nuclear Medicine and Clinical Molecular ImagingEberhard Karls UniversityTübingenGermany
| | - Ralph N. Martins
- Department of Biomedical SciencesMacquarie UniversityNorth RydeNew South WalesAustralia
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health SciencesEdith Cowan UniversityJoondalupWestern AustraliaAustralia
- School of Psychiatry and Clinical NeurosciencesUniversity of Western AustraliaCrawleyWestern AustraliaAustralia
- Australian Alzheimer's Research FoundationNedlandsWestern AustraliaAustralia
- The Cooperative Research Centre for Mental HealthCarlton SouthVictoriaAustralia
| | - Hamid R. Sohrabi
- Department of Biomedical SciencesMacquarie UniversityNorth RydeNew South WalesAustralia
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health SciencesEdith Cowan UniversityJoondalupWestern AustraliaAustralia
- School of Psychiatry and Clinical NeurosciencesUniversity of Western AustraliaCrawleyWestern AustraliaAustralia
- Australian Alzheimer's Research FoundationNedlandsWestern AustraliaAustralia
- The Cooperative Research Centre for Mental HealthCarlton SouthVictoriaAustralia
| | - Kevin Taddei
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health SciencesEdith Cowan UniversityJoondalupWestern AustraliaAustralia
- Australian Alzheimer's Research FoundationNedlandsWestern AustraliaAustralia
| | - Victor L. Villemagne
- Department of Molecular Imaging and TherapyAustin HealthMelbourneVictoriaAustralia
| | - Peter R. Schofield
- Neuroscience Research Australia, RandwickSydneyNew South WalesAustralia
- School of Medical SciencesUNSW SydneySydneyNew South WalesAustralia
| | - William S. Brooks
- Neuroscience Research Australia, RandwickSydneyNew South WalesAustralia
- Prince of Wales Hospital Clinical SchoolUNSW SydneySydneyNew South WalesAustralia
| | - Michael Fulham
- Department of Molecular Imaging, Royal Prince Alfred Hospital, Sydney Medical SchoolUniversity of SydneyCamperdownNew South WalesAustralia
| | - Colin L. Masters
- The Florey InstituteUniversity of MelbourneParkvilleVictoriaAustralia
| | - Bernardino Ghetti
- Department of Pathology and Laboratory MedicineIndiana University School of MedicineIndianapolisIndianaUSA
| | - Andrew J. Saykin
- Department of NeurologyIndiana University School of MedicineIndianapolisIndianaUSA
- Department of RadiologyIndiana University School of MedicineIndianapolisIndianaUSA
| | | | | | - Michael Weiner
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of RadiologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
- Department of MedicineUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
- Department of PsychiatryUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
- Department of NeurologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - David M. Cash
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of NeurologyUniversity College LondonLondonUK
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
| | - Ricardo F. Allegri
- Department of Cognitive Neurology, Neuropsychiatry and NeuropsychologyInstituto de InvestigacionesNeurológicas FLENIBuenos AiresArgentina
| | - Patricio Chrem
- Department of Cognitive Neurology, Neuropsychiatry and NeuropsychologyInstituto de InvestigacionesNeurológicas FLENIBuenos AiresArgentina
| | - Su Yi
- Banner Alzheimer's InstitutePhoenixArizonaUSA
| | - Bruce L. Miller
- Global Brain Health InstituteUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of Neurology, Memory and Aging CenterUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Gil D. Rabinovici
- Global Brain Health InstituteUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Howard J. Rosen
- Global Brain Health InstituteUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of Neurology, Memory and Aging CenterUniversity of CaliforniaSan FranciscoCaliforniaUSA
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A trial of gantenerumab or solanezumab in dominantly inherited Alzheimer's disease. Nat Med 2021; 27:1187-1196. [PMID: 34155411 PMCID: PMC8988051 DOI: 10.1038/s41591-021-01369-8] [Citation(s) in RCA: 158] [Impact Index Per Article: 52.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 04/23/2021] [Indexed: 02/06/2023]
Abstract
Dominantly inherited Alzheimer's disease (DIAD) causes predictable biological changes decades before the onset of clinical symptoms, enabling testing of interventions in the asymptomatic and symptomatic stages to delay or slow disease progression. We conducted a randomized, placebo-controlled, multi-arm trial of gantenerumab or solanezumab in participants with DIAD across asymptomatic and symptomatic disease stages. Mutation carriers were assigned 3:1 to either drug or placebo and received treatment for 4-7 years. The primary outcome was a cognitive end point; secondary outcomes included clinical, cognitive, imaging and fluid biomarker measures. Fifty-two participants carrying a mutation were assigned to receive gantenerumab, 52 solanezumab and 40 placebo. Both drugs engaged their Aβ targets but neither demonstrated a beneficial effect on cognitive measures compared to controls. The solanezumab-treated group showed a greater cognitive decline on some measures and did not show benefits on downstream biomarkers. Gantenerumab significantly reduced amyloid plaques, cerebrospinal fluid total tau, and phospho-tau181 and attenuated increases of neurofilament light chain. Amyloid-related imaging abnormalities edema was observed in 19.2% (3 out of 11 were mildly symptomatic) of the gantenerumab group, 2.5% of the placebo group and 0% of the solanezumab group. Gantenerumab and solanezumab did not slow cognitive decline in symptomatic DIAD. The asymptomatic groups showed no cognitive decline; symptomatic participants had declined before reaching the target doses.
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Dekker MJHJ, Stolk P, Pasmooij AMG. The Use of Remote Monitoring Technologies: A Review of Recent Regulatory Scientific Advices, Qualification Opinions, and Qualification Advices Issued by the European Medicines Agency. Front Med (Lausanne) 2021; 8:619513. [PMID: 34277648 PMCID: PMC8281114 DOI: 10.3389/fmed.2021.619513] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 05/21/2021] [Indexed: 11/13/2022] Open
Abstract
Aims: Recently, the use of novel remote monitoring technologies (RMTs) in trials has gained much interest. To facilitate regulatory learning, we evaluated qualification opinions (QOs) and advices (QAs) and scientific advices (SAs) of the Committee for Medicinal Products for Human Use (CHMP) to gain insight in the types of devices that are intended to be used in clinical trials for supporting/submitting application for obtaining marketing authorization (registration trials) and the main recommendations of the CHMP. Methods: QOs, QAs, and SAs of the CHMP that assessed RMTs between 2013 and 2019 were eligible for our study. The following information was extracted from the documents: year of advice/opinion, device and endpoints used, type of endpoint (primary, secondary, exploratory, or safety), and main recommendations of the CHMP. Results: In total two QOs, four QAs, and 59 SAs were included in our study (total of SAs between 2013 and 2019 = 4,054). In the SAs, accelerometers to measure activity and/or sleep parameters (n = 31) were the most frequently used devices, followed by mobile applications (n = 6) and glucose monitoring devices (n = 6). Usually, these measures were proposed as secondary or exploratory endpoints (n = 32). The main recommendations of the CHMP were related to relevance of the (novel) outcome measure; validation; precision, accuracy, sensitivity, and specificity; compliance; sampling interval; and data handling and privacy. Conclusions: Although there was a trend toward an increased use over time, the use of RMTs in registration trials is still relatively rare. In the absence of formal European regulatory guidance on mHealth technologies, insight in the main recommendations of the CHMP may stimulate the use of novel RMTs in a regulatory context.
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10
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Value of Data Sharing to Advance Drug Development: A Regulatory Perspective. Ther Innov Regul Sci 2021; 55:850-852. [PMID: 33876396 DOI: 10.1007/s43441-021-00275-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 03/07/2021] [Indexed: 10/21/2022]
Abstract
New tools are needed to evaluate and predict the efficacy and safety of medical products. However, the development of such tools requires collaboration and effective data sharing. In this issue of Therapeutic Innovation & Regulatory Science, scientists from the Critical Path Institute (C-Path) discuss their experiences using patient-level data to facilitate innovation in drug development. We share our perspective on the issues discussed in the C-Path paper and offer suggestions on future efforts.
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11
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Coetzee T, Ball MP, Boutin M, Bronson A, Dexter DT, English RA, Furlong P, Goodman AD, Grossman C, Hernandez AF, Hinners JE, Hudson L, Kennedy A, Marchisotto MJ, Myers E, Nowell WB, Nosek BA, Sherer T, Shore C, Sim I, Smolensky L, Williams C, Wood J, Terry SF, Matrisian L. Data Sharing Goals for Nonprofit Funders of Clinical Trials. J Particip Med 2021; 13:e23011. [PMID: 33779573 PMCID: PMC8088851 DOI: 10.2196/23011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 12/10/2020] [Accepted: 12/12/2020] [Indexed: 01/25/2023] Open
Abstract
Sharing clinical trial data can provide value to research participants and communities by accelerating the development of new knowledge and therapies as investigators merge data sets to conduct new analyses, reproduce published findings to raise standards for original research, and learn from the work of others to generate new research questions. Nonprofit funders, including disease advocacy and patient-focused organizations, play a pivotal role in the promotion and implementation of data sharing policies. Funders are uniquely positioned to promote and support a culture of data sharing by serving as trusted liaisons between potential research participants and investigators who wish to access these participants’ networks for clinical trial recruitment. In short, nonprofit funders can drive policies and influence research culture. The purpose of this paper is to detail a set of aspirational goals and forward thinking, collaborative data sharing solutions for nonprofit funders to fold into existing funding policies. The goals of this paper convey the complexity of the opportunities and challenges facing nonprofit funders and the appropriate prioritization of data sharing within their organizations and may serve as a starting point for a data sharing toolkit for nonprofit funders of clinical trials to provide the clarity of mission and mechanisms to enforce the data sharing practices their communities already expect are happening.
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Affiliation(s)
- Timothy Coetzee
- National Multiple Sclerosis Society, Cherry Hill, NJ, United States
| | | | | | - Abby Bronson
- Edgewise Therapeutics, Boulder, CO, United States
| | | | - Rebecca A English
- National Academies of Sciences, Engineering, and Medicine, Washington, DC, United States
| | | | - Andrew D Goodman
- Department of Neurology, University of Rochester Medical Center, Rochester, NY, United States
| | | | | | | | - Lynn Hudson
- Critical Path Institute, Tucson, AZ, United States
| | - Annie Kennedy
- Parent Project Muscular Dystrophy, Bethesda, MD, United States
| | | | - Elizabeth Myers
- Doris Duke Charitable Foundation, New York, NY, United States
| | | | - Brian A Nosek
- Center for Open Science, Charlottesville, VA, United States
| | - Todd Sherer
- The Michael J Fox Foundation for Parkinson's Research, New York, NY, United States
| | - Carolyn Shore
- National Academies of Sciences, Engineering, and Medicine, Washington, DC, United States
| | - Ida Sim
- Department of Medicine, University of California San Francisco, San Francisco, CA, United States
| | - Luba Smolensky
- The Michael J Fox Foundation for Parkinson's Research, New York, NY, United States
| | | | | | | | - Lynn Matrisian
- Pancreatic Cancer Action Network, Washington, DC, United States
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12
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Bullich S, Roé-Vellvé N, Marquié M, Landau SM, Barthel H, Villemagne VL, Sanabria Á, Tartari JP, Sotolongo-Grau O, Doré V, Koglin N, Müller A, Perrotin A, Jovalekic A, De Santi S, Tárraga L, Stephens AW, Rowe CC, Sabri O, Seibyl JP, Boada M. Early detection of amyloid load using 18F-florbetaben PET. ALZHEIMERS RESEARCH & THERAPY 2021; 13:67. [PMID: 33773598 PMCID: PMC8005243 DOI: 10.1186/s13195-021-00807-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 03/10/2021] [Indexed: 03/26/2023]
Abstract
BACKGROUND A low amount and extent of Aβ deposition at early stages of Alzheimer's disease (AD) may limit the use of previously developed pathology-proven composite SUVR cutoffs. This study aims to characterize the population with earliest abnormal Aβ accumulation using 18F-florbetaben PET. Quantitative thresholds for the early (SUVRearly) and established (SUVRestab) Aβ deposition were developed, and the topography of early Aβ deposition was assessed. Subsequently, Aβ accumulation over time, progression from mild cognitive impairment (MCI) to AD dementia, and tau deposition were assessed in subjects with early and established Aβ deposition. METHODS The study population consisted of 686 subjects (n = 287 (cognitively normal healthy controls), n = 166 (subjects with subjective cognitive decline (SCD)), n = 129 (subjects with MCI), and n = 101 (subjects with AD dementia)). Three categories in the Aβ-deposition continuum were defined based on the developed SUVR cutoffs: Aβ-negative subjects, subjects with early Aβ deposition ("gray zone"), and subjects with established Aβ pathology. RESULTS SUVR using the whole cerebellum as the reference region and centiloid (CL) cutoffs for early and established amyloid pathology were 1.10 (13.5 CL) and 1.24 (35.7 CL), respectively. Cingulate cortices and precuneus, frontal, and inferior lateral temporal cortices were the regions showing the initial pathological tracer retention. Subjects in the "gray zone" or with established Aβ pathology accumulated more amyloid over time than Aβ-negative subjects. After a 4-year clinical follow-up, none of the Aβ-negative or the gray zone subjects progressed to AD dementia while 91% of the MCI subjects with established Aβ pathology progressed. Tau deposition was infrequent in those subjects without established Aβ pathology. CONCLUSIONS This study supports the utility of using two cutoffs for amyloid PET abnormality defining a "gray zone": a lower cutoff of 13.5 CL indicating emerging Aβ pathology and a higher cutoff of 35.7 CL where amyloid burden levels correspond to established neuropathology findings. These cutoffs define a subset of subjects characterized by pre-AD dementia levels of amyloid burden that precede other biomarkers such as tau deposition or clinical symptoms and accelerated amyloid accumulation. The determination of different amyloid loads, particularly low amyloid levels, is useful in determining who will eventually progress to dementia. Quantitation of amyloid provides a sensitive measure in these low-load cases and may help to identify a group of subjects most likely to benefit from intervention. TRIAL REGISTRATION Data used in this manuscript belong to clinical trials registered in ClinicalTrials.gov ( NCT00928304 , NCT00750282 , NCT01138111 , NCT02854033 ) and EudraCT (2014-000798-38).
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Affiliation(s)
- Santiago Bullich
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany.
| | - Núria Roé-Vellvé
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Marta Marquié
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley and Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Henryk Barthel
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | - Victor L Villemagne
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.,Departments of Medicine and Molecular Imaging, University of Melbourne, Austin Health, Melbourne, Victoria, Australia
| | - Ángela Sanabria
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Juan Pablo Tartari
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Oscar Sotolongo-Grau
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain
| | - Vincent Doré
- Departments of Medicine and Molecular Imaging, University of Melbourne, Austin Health, Melbourne, Victoria, Australia.,The Australian e-Health Research Centre, Health and Biosecurity, CSIRO, Melbourne, Victoria, Australia
| | - Norman Koglin
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Andre Müller
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Audrey Perrotin
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | | | | | - Lluís Tárraga
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Andrew W Stephens
- Life Molecular Imaging GmbH, Tegeler Str. 6-7, 13353, Berlin, Germany
| | - Christopher C Rowe
- Departments of Medicine and Molecular Imaging, University of Melbourne, Austin Health, Melbourne, Victoria, Australia
| | - Osama Sabri
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | | | - Mercè Boada
- Fundació ACE Institut Català de Neurociències Aplicades, Research Center and Memory Unit - Universitat Internacional de Catalunya (UIC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
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13
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McDade E, Bednar MM, Brashear HR, Miller DS, Maruff P, Randolph C, Ismail Z, Carrillo MC, Weber CJ, Bain LJ, Hake AM. The pathway to secondary prevention of Alzheimer's disease. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2020; 6:e12069. [PMID: 32885024 PMCID: PMC7453146 DOI: 10.1002/trc2.12069] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 07/09/2020] [Indexed: 11/11/2022]
Abstract
Alzheimer's disease (AD) is a continuum consisting of a preclinical stage that occurs decades before symptoms appear. As researchers make advances in investigating the continuum, the importance of developing drugs for secondary prevention is garnering increased discussion. For efficacious drug development for secondary prevention it is important to define what are the earliest biological stages of AD. The Alzheimer's Association Research Roundtable convened November 27 to 28, 2018 to focus on pre-clinical AD. This review will address the biological approach to defining pre-clinical AD, detection, identification of at-risk individuals, and lessons learned from trials such as A4 and TOMMORROW.
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Affiliation(s)
- Eric McDade
- Department of NeurologyWashington University School of MedicineSaint LouisMissouriUSA
| | - Martin M. Bednar
- Takeda Pharmaceuticals International Co.Americas, Inc.CambridgeMassachusettsUSA
| | | | | | | | - Christopher Randolph
- MedAvante‐ProPhaseHamiltonNew JerseyUSA
- Department of NeurologyLoyola University Medical CenterMaywoodIllinoisUSA
| | - Zahinoor Ismail
- Cumming School of MedicineThe University of CalgaryCalgaryCanada
| | | | | | - Lisa J. Bain
- Independent Science WriterElversonPennsylvaniaUSA
| | - Ann Marie Hake
- Eli Lilly and CompanyIndianapolisIndianaUSA
- Department of NeurologyIndiana University School of MedicineIndianapolisIndianaUSA
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14
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Kivipelto M, Mangialasche F, Snyder HM, Allegri R, Andrieu S, Arai H, Baker L, Belleville S, Brodaty H, Brucki SM, Calandri I, Caramelli P, Chen C, Chertkow H, Chew E, Choi SH, Chowdhary N, Crivelli L, Torre RDL, Du Y, Dua T, Espeland M, Feldman HH, Hartmanis M, Hartmann T, Heffernan M, Henry CJ, Hong CH, Håkansson K, Iwatsubo T, Jeong JH, Jimenez-Maggiora G, Koo EH, Launer LJ, Lehtisalo J, Lopera F, Martínez-Lage P, Martins R, Middleton L, Molinuevo JL, Montero-Odasso M, Moon SY, Morales-Pérez K, Nitrini R, Nygaard HB, Park YK, Peltonen M, Qiu C, Quiroz YT, Raman R, Rao N, Ravindranath V, Rosenberg A, Sakurai T, Salinas RM, Scheltens P, Sevlever G, Soininen H, Sosa AL, Suemoto CK, Tainta-Cuezva M, Velilla L, Wang Y, Whitmer R, Xu X, Bain LJ, Solomon A, Ngandu T, Carrillo MC. World-Wide FINGERS Network: A global approach to risk reduction and prevention of dementia. Alzheimers Dement 2020; 16:1078-1094. [PMID: 32627328 PMCID: PMC9527644 DOI: 10.1002/alz.12123] [Citation(s) in RCA: 237] [Impact Index Per Article: 59.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Revised: 03/11/2020] [Accepted: 04/30/2020] [Indexed: 12/14/2022]
Abstract
Reducing the risk of dementia can halt the worldwide increase of affected people. The multifactorial and heterogeneous nature of late-onset dementia, including Alzheimer’s disease (AD), indicates a potential impact of multidomain lifestyle interventions on risk reduction. The positive results of the landmark multidomain Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) support such an approach. The World-Wide FINGERS (WW-FINGERS), launched in 2017 and including over 25 countries, is the first global network of multidomain lifestyle intervention trials for dementia risk reduction and prevention. WW-FINGERS aims to adapt, test, and optimize the FINGER model to reduce risk across the spectrum of cognitive decline—from at-risk asymptomatic states to early symptomatic stages—in different geographical, cultural, and economic settings. WW-FINGERS aims to harmonize and adapt multidomain interventions across various countries and settings, to facilitate data sharing and analysis across studies, and to promote international joint initiatives to identify globally implementable and effective preventive strategies.
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Affiliation(s)
- Miia Kivipelto
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.,Theme Aging, Karolinska University Hospital, Stockholm, Sweden.,Stockholms Sjukhem, Research & Development Unit, Stockholm, Sweden.,The Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London, United Kingdom
| | - Francesca Mangialasche
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Aging Research Center, Center for Alzheimer Research, Department of Neurobiology Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Heather M Snyder
- Division of Medical and Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Ricardo Allegri
- Department of Cognitive Neurology, FLENI, Buenos Aires, Argentina
| | - Sandrine Andrieu
- INSERM, University of Toulouse UMR1027, Toulouse, France.,Department of Epidemiology and Public Health, Toulouse University Hospital, Toulouse, France
| | - Hidenori Arai
- National Center for Geriatrics and Gerontology, Obu, Japan
| | - Laura Baker
- Department of Internal Medicine - Geriatrics, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Sylvie Belleville
- Institute Universitaire de Geriatrie de Montreal, Universite de Montreal, Montreal, Canada
| | - Henry Brodaty
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW Sydney, Sydney, Australia
| | - Sonia M Brucki
- Department of Neurology, University of São Paulo Medical School, São Paulo, SP, Brazil
| | - Ismael Calandri
- Department of Cognitive Neurology, FLENI, Buenos Aires, Argentina
| | - Paulo Caramelli
- Department of Internal Medicine, Faculty of Medicine, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - Christopher Chen
- Memory Aging and Cognition Centre, National University of Singapore, Singapore, Singapore.,Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Howard Chertkow
- Division of Medicine/Neurology, University of Toronto, Toronto, Canada.,Division of Cognitive Neurology and Innovation, Baycrest Health Sciences and Rotman Research Institute, Toronto, Canada
| | - Effie Chew
- Division of Neurology, University Medicine Cluster, National University Hospital, Singapore, Singapore
| | - Seong H Choi
- Department of Neurology, Inha University School of Medicine, Incheon, Korea
| | - Neerja Chowdhary
- Brain Health Unit, Department of Mental Health and Substance Use, World Health Organization, Geneva, Switzerland
| | - Lucía Crivelli
- Department of Cognitive Neurology, FLENI, Buenos Aires, Argentina
| | - Rafael De La Torre
- Integrative Pharmacology and Systems Neurosciences Research Group, Neurosciences Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Yifeng Du
- Department of Neurology, Shandong Provincial Hospital affiliated to Shandong University, Jinan, Shandong, China
| | - Tarun Dua
- Brain Health Unit, Department of Mental Health and Substance Use, World Health Organization, Geneva, Switzerland
| | - Mark Espeland
- Department of Internal Medicine - Geriatrics, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.,Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Howard H Feldman
- Department of Neurosciences, Alzheimer Disease Cooperative Study, University of California, San Diego, California, La Jolla, USA.,Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Maris Hartmanis
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,FINGERS Brain Health Institute, Stockholm, Sweden
| | - Tobias Hartmann
- German Institute for Dementia Prevention (DIDP), Medical Faculty, and Department of Experimental Neurology, Saarland University, Homburg, Germany
| | - Megan Heffernan
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW Sydney, Sydney, Australia
| | - Christiani J Henry
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Chang H Hong
- Department of Psychiatry, Ajou University School of Medicine, Suwon, Korea
| | - Krister Håkansson
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Takeshi Iwatsubo
- Unit for Early and Exploratory Clinical Development, The University of Tokyo Hospital, Tokyo, Japan.,Department of Neuropathology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Jee H Jeong
- Department of Neurology, Ewha Womans University School of Medicine, Seoul, Korea
| | - Gustavo Jimenez-Maggiora
- Alzheimer's Therapeutic Research Institute, Keck School of Medicine, University of Southern California, California, San Diego, USA
| | - Edward H Koo
- Departments of Medicine and Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, Bethesda, Maryland, USA
| | - Jenni Lehtisalo
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland.,Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Francisco Lopera
- Neuroscience Group of Antioquia (GNA), Faculty of Medicine of the University of Antioquia, Medellín, Antioquia, Colombia
| | - Pablo Martínez-Lage
- Department of Neurology, Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
| | - Ralph Martins
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia.,Department of Biomedical Sciences, Macquarie University, North Ryde, New South Wales, Australia
| | - Lefkos Middleton
- The Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London, United Kingdom.,Neurology, Public Health Directorate, Imperial College Healthcare NHS Trust, London, UK
| | - José L Molinuevo
- BarcelonaBeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | - Manuel Montero-Odasso
- Department of Medicine and Biostatistics Western University, London, Ontario, Canada
| | - So Y Moon
- Department of Neurology, Ajou University School of Medicine, Suwon, Korea
| | - Kristal Morales-Pérez
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,FINGERS Brain Health Institute, Stockholm, Sweden
| | - Ricardo Nitrini
- Department of Neurology, University of São Paulo Medical School, São Paulo, SP, Brazil
| | - Haakon B Nygaard
- Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Yoo K Park
- Department of Medical nutrition, Graduate School of East-West Medical Science, Kyung Hee University, Suwon, Korea
| | - Markku Peltonen
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Chengxuan Qiu
- Aging Research Center, Center for Alzheimer Research, Department of Neurobiology Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.,Department of Neurology, Shandong Provincial Hospital affiliated to Shandong University, Jinan, Shandong, China
| | - Yakeel T Quiroz
- Neuroscience Group of Antioquia (GNA), Faculty of Medicine of the University of Antioquia, Medellín, Antioquia, Colombia.,Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Rema Raman
- Alzheimer's Therapeutic Research Institute, Keck School of Medicine, University of Southern California, California, San Diego, USA
| | - Naren Rao
- Department of psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
| | | | - Anna Rosenberg
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | | | - Rosa M Salinas
- Laboratory of Dementias, National Institute of Neurology and Neurosurgery, Mexico City, Mexico
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Gustavo Sevlever
- Department of Cognitive Neurology, FLENI, Buenos Aires, Argentina
| | - Hilkka Soininen
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Ana L Sosa
- Laboratory of Dementias, National Institute of Neurology and Neurosurgery, Mexico City, Mexico
| | - Claudia K Suemoto
- Division of Geriatrics, University of São Paulo Medical School, São Paulo, Brazil
| | - Mikel Tainta-Cuezva
- Department of Neurology, Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain.,Organización Sanitaria Integrada Goierri Alto Urola, Basque Country, Spain
| | - Lina Velilla
- Neuroscience Group of Antioquia (GNA), Faculty of Medicine of the University of Antioquia, Medellín, Antioquia, Colombia
| | - Yongxiang Wang
- Department of Neurology, Shandong Provincial Hospital affiliated to Shandong University, Jinan, Shandong, China
| | - Rachel Whitmer
- Division of Epidemiology, University of California, Davis, Davis, California, USA
| | - Xin Xu
- Memory Aging and Cognition Centre, National University of Singapore, Singapore, Singapore.,Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Lisa J Bain
- Independent Science Writer, Philadelphia, Pennsylvania, USA
| | - Alina Solomon
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Tiia Ngandu
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Maria C Carrillo
- Division of Medical and Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
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15
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Raman R. Statistical methods in handling placebo effect. INTERNATIONAL REVIEW OF NEUROBIOLOGY 2020; 153:103-120. [PMID: 32563284 DOI: 10.1016/bs.irn.2020.04.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
A critical issue facing the therapeutic area of neurological diseases is the large number of failed randomized clinical trials, especially when moving from promising Phase 2 trials to failed Phase 3 trials. A common cited reason for these failures is a high placebo response rate that thereby reduces the observed treatment effect. Explanations for this higher than anticipated placebo response include small sample sizes, inadequate study designs and/or analytic methods, baseline characteristics of the trial sample, possible investigator bias and a participant's own expectations and conditional learning. Several innovative study designs and new methodological approaches to statistical analyses have been proposed to handle placebo effects anticipated or observed in double blind, randomized clinical trials (RCT's). This chapter examines current study designs being used to reduce the observed placebo response and statistical analysis methods being employed for addressing this problem in neuroscience clinical trials.
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Affiliation(s)
- Rema Raman
- Alzheimer's Therapeutic Research Institute, University of Southern California, Los Angeles, CA, United States.
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16
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Mauricio R, Benn C, Davis J, Dawson G, Dawson LA, Evans A, Fox N, Gallacher J, Hutton M, Isaac J, Jones DN, Jones L, Lalli G, Libri V, Lovestone S, Moody C, Noble W, Perry H, Pickett J, Reynolds D, Ritchie C, Rohrer JD, Routledge C, Rowe J, Snyder H, Spires-Jones T, Swartz J, Truyen L, Whiting P. Tackling gaps in developing life-changing treatments for dementia. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2019; 5:241-253. [PMID: 31297438 PMCID: PMC6597931 DOI: 10.1016/j.trci.2019.05.001] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Since the G8 dementia summit in 2013, a number of initiatives have been established with the aim of facilitating the discovery of a disease-modifying treatment for dementia by 2025. This report is a summary of the findings and recommendations of a meeting titled "Tackling gaps in developing life-changing treatments for dementia", hosted by Alzheimer's Research UK in May 2018. The aim of the meeting was to identify, review, and highlight the areas in dementia research that are not currently being addressed by existing initiatives. It reflects the views of leading experts in the field of neurodegeneration research challenged with developing a strategic action plan to address these gaps and make recommendations on how to achieve the G8 dementia summit goals. The plan calls for significant advances in (1) translating newly identified genetic risk factors into a better understanding of the impacted biological processes; (2) enhanced understanding of selective neuronal resilience to inform novel drug targets; (3) facilitating robust and reproducible drug-target validation; (4) appropriate and evidence-based selection of appropriate subjects for proof-of-concept clinical trials; (5) improving approaches to assess drug-target engagement in humans; and (6) innovative approaches in conducting clinical trials if we are able to detect disease 10-15 years earlier than we currently do today.
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Affiliation(s)
| | | | - John Davis
- Alzheimer's Research UK Oxford Drug Discovery Institute, University of Oxford, Oxford, UK
| | - Gerry Dawson
- P1 Vital, Howbery Business Park, Wallingford, Oxfordshire, UK
| | - Lee A. Dawson
- Cerevance Ltd, Cambridge Science Park, Cambridge, UK
| | | | - Nick Fox
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - John Gallacher
- Department of Psychiatry, University of Oxford, Oxford, UK
| | | | - John Isaac
- Neuroscience External Innovation, Neuroscience Therapeutic Area, Johnson & Johnson Innovation, London, UK
| | - Declan N.C. Jones
- Neuroscience External Innovation, Neuroscience Therapeutic Area, Johnson & Johnson Innovation, London, UK
| | - Lesley Jones
- MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, Wales, UK
| | | | - Vincenzo Libri
- Institute of Neurology, University College London, London, UK
| | | | | | - Wendy Noble
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Hugh Perry
- Faculty of Natural and Environmental Sciences, University of Southampton, Southampton, UK
| | | | | | - Craig Ritchie
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Jonathan D. Rohrer
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | | | - James Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | | | - Tara Spires-Jones
- UK Dementia Research Institute, The University of Edinburgh, Edinburgh, UK
| | - Jina Swartz
- European Innovation Hub, Merck Sharp and Dohme, London, UK
| | - Luc Truyen
- Janssen Research & Development LLC, Titusville, NJ, USA
| | - Paul Whiting
- Dementia Research Institute, UCL, London, UK
- ARUK Drug Discovery Institute, Institute of Neurology, University College London, London, UK
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The Alzheimer's Prevention Initiative Generation Program: Study design of two randomized controlled trials for individuals at risk for clinical onset of Alzheimer's disease. ALZHEIMERS & DEMENTIA-TRANSLATIONAL RESEARCH & CLINICAL INTERVENTIONS 2019; 5:216-227. [PMID: 31211217 PMCID: PMC6562315 DOI: 10.1016/j.trci.2019.02.005] [Citation(s) in RCA: 61] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Introduction Alzheimer's disease (AD) pathology, including the accumulation of amyloid beta (Aβ) species and tau pathology, begins decades before the onset of cognitive impairment. This long preclinical period provides an opportunity for clinical trials designed to prevent or delay the onset of cognitive impairment due to AD. Under the umbrella of the Alzheimer's Prevention Initiative Generation Program, therapies targeting Aβ, including CNP520 (umibecestat), a β-site-amyloid precursor protein cleaving enzyme-1 (BACE-1) inhibitor, and CAD106, an active Aβ immunotherapy, are in clinical development in preclinical AD. Methods The Alzheimer's Prevention Initiative Generation Program comprises two pivotal (phase 2/3) studies that assess the efficacy and safety of umibecestat and CAD106 in cognitively unimpaired individuals with high risk for developing symptoms of AD based on their age (60-75 years), APOE4 genotype, and, for heterozygotes (APOE ε2/ε4 or ε3/ε4), elevated brain amyloid. Approximately, 3500 individuals will be enrolled in either Generation Study 1 (randomized to cohort 1 [CAD106 injection or placebo, 5:3] or cohort 2 [oral umibecestat 50 mg or placebo, 3:2]) or Generation Study 2 (randomized to oral umibecestat 50 mg and 15 mg, or placebo [2:1:2]). Participants receive treatment for at least 60 months and up to a maximum of 96 months. Primary outcomes include time to event, with event defined as diagnosis of mild cognitive impairment due to AD and/or dementia due to AD, and the Alzheimer's Prevention Initiative preclinical composite cognitive test battery. Secondary endpoints include the Clinical Dementia Rating Sum of Boxes, Repeatable Battery for the Assessment of Neuropsychological Status total score, Everyday Cognition Scale, biomarkers, and brain imaging. Discussion The Generation Program is designed to assess the efficacy, safety, and biomarker effects of the two treatments in individuals at high risk for AD. It may also provide a plausible test of the amyloid hypothesis and further accelerate the evaluation of AD prevention therapies.
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Salvadó G, Molinuevo JL, Brugulat-Serrat A, Falcon C, Grau-Rivera O, Suárez-Calvet M, Pavia J, Niñerola-Baizán A, Perissinotti A, Lomeña F, Minguillon C, Fauria K, Zetterberg H, Blennow K, Gispert JD. Centiloid cut-off values for optimal agreement between PET and CSF core AD biomarkers. Alzheimers Res Ther 2019; 11:27. [PMID: 30902090 PMCID: PMC6429814 DOI: 10.1186/s13195-019-0478-z] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Accepted: 02/27/2019] [Indexed: 01/22/2023]
Abstract
BACKGROUND The Centiloid scale has been developed to standardize measurements of amyloid PET imaging. Reference cut-off values of this continuous measurement enable the consistent operationalization of decision-making for multicentre research studies and clinical trials. In this study, we aimed at deriving reference Centiloid thresholds that maximize the agreement against core Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers in two large independent cohorts. METHODS A total of 516 participants of the ALFA+ Study (N = 205) and ADNI (N = 311) underwent amyloid PET imaging ([18F]flutemetamol and [18F]florbetapir, respectively) and core AD CSF biomarker determination using Elecsys® tests. Tracer uptake was quantified in Centiloid units (CL). Optimal Centiloid cut-offs were sought that maximize the agreement between PET and dichotomous determinations based on CSF levels of Aβ42, tTau, pTau, and their ratios, using pre-established reference cut-off values. To this end, a receiver operating characteristic analysis (ROC) was conducted, and Centiloid cut-offs were calculated as those that maximized the Youden's J Index or the overall percentage agreement recorded. RESULTS All Centiloid cut-offs fell within the range of 25-35, except for CSF Aβ42 that rendered an optimal cut-off value of 12 CL. As expected, the agreement of tau/Aβ42 ratios was higher than that of CSF Aβ42. Centiloid cut-off robustness was confirmed even when established in an independent cohort and against variations of CSF cut-offs. CONCLUSIONS A cut-off of 12 CL matches previously reported values derived against postmortem measures of AD neuropathology. Together with these previous findings, our results flag two relevant inflection points that would serve as boundary of different stages of amyloid pathology: one around 12 CL that marks the transition from the absence of pathology to subtle pathology and another one around 30 CL indicating the presence of established pathology. The derivation of robust and generalizable cut-offs for core AD biomarkers requires cohorts with adequate representation of intermediate levels. TRIAL REGISTRATION ALFA+ Study, NCT02485730 ALFA PET Sub-study, NCT02685969.
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Affiliation(s)
- Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Anna Brugulat-Serrat
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
| | - Carles Falcon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
- CIBER de Bioengeniería, Biomateriales y Nanomedicina, Madrid, Spain
| | - Oriol Grau-Rivera
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
| | - Javier Pavia
- CIBER de Bioengeniería, Biomateriales y Nanomedicina, Madrid, Spain
- Nuclear Medicine Department, Hospital Clínic, Barcelona, Spain
- Instititut d’Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
| | | | | | | | - Carolina Minguillon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- CIBER de Bioengeniería, Biomateriales y Nanomedicina, Madrid, Spain
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Tariot PN, Lopera F, Langbaum JB, Thomas RG, Hendrix S, Schneider LS, Rios-Romenets S, Giraldo M, Acosta N, Tobon C, Ramos C, Espinosa A, Cho W, Ward M, Clayton D, Friesenhahn M, Mackey H, Honigberg L, Sanabria Bohorquez S, Chen K, Walsh T, Langlois C, Reiman EM. The Alzheimer's Prevention Initiative Autosomal-Dominant Alzheimer's Disease Trial: A study of crenezumab versus placebo in preclinical PSEN1 E280A mutation carriers to evaluate efficacy and safety in the treatment of autosomal-dominant Alzheimer's disease, including a placebo-treated noncarrier cohort. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2018; 4:150-160. [PMID: 29955659 PMCID: PMC6021543 DOI: 10.1016/j.trci.2018.02.002] [Citation(s) in RCA: 79] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
INTRODUCTION Autosomal-dominant Alzheimer's disease (ADAD) represents a crucial population for identifying prevention strategies that might modify disease course for cognitively unimpaired individuals at high imminent risk for developing symptoms due to Alzheimer's disease (AD), that is, who have "preclinical" AD. Crenezumab is an antiamyloid monoclonal antibody that binds monomeric and aggregated forms of amyloid β, with highest affinity for oligomers; it is in development for early stages of sporadic AD and for ADAD. METHODS This is a prospective, randomized, double-blind, placebo-controlled phase 2 study of the efficacy of crenezumab versus placebo in asymptomatic PSEN1 E280A mutation carriers from family kindreds with ADAD in Colombia. Participants were randomized to receive either crenezumab or placebo for 260 weeks. The study was designed to enroll a planned total of 300 participants, including 200 preclinical mutation carriers (approximately 100 treatment, 100 placebo) and an additional control group of mutation noncarriers from the same family kindreds included to mask mutation carrier status (100 placebo only). The primary outcome is change in the Alzheimer's Prevention Initiative ADAD Composite Cognitive Test Score from baseline to week 260. Secondary outcomes include time to progression to mild cognitive impairment due to AD or dementia due to AD; changes in dementia severity, memory, and overall neurocognitive functioning; and changes in amyloid-positron emission tomography, fluorodeoxyglucose-positron emission tomography, magnetic resonance imaging volumes, and cerebrospinal fluid levels of β amyloid, tau, and p-tau. Safety and tolerability are assessed. RESULTS Two hundred fifty-two participants were enrolled between December 2013 and February 2017. DISCUSSION We describe the first large-scale, potentially label-enabling clinical trial of a preclinical treatment for ADAD. Results from this trial will inform on the efficacy of crenezumab for delaying onset of, slowing decline in, or preventing cognitive impairment in individuals with preclinical ADAD and will foster an improved understanding of AD biomarkers and their relationship to clinical outcomes.
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Affiliation(s)
| | - Francisco Lopera
- Grupo de Neurociencias, Universidad de Antioquia, SIU, Medellín, Colombia
| | | | - Ronald G. Thomas
- Department of Neurosciences, University of California San Diego School of Medicine, La Jolla, CA, USA
| | | | - Lon S. Schneider
- USC State of California Alzheimer's Disease Research and Clinical Center, Keck Medicine of USC, Los Angeles, CA, USA
| | | | - Margarita Giraldo
- Grupo de Neurociencias, Universidad de Antioquia, SIU, Medellín, Colombia
| | - Natalia Acosta
- Grupo de Neurociencias, Universidad de Antioquia, SIU, Medellín, Colombia
| | - Carlos Tobon
- Grupo de Neurociencias, Universidad de Antioquia, SIU, Medellín, Colombia
| | - Claudia Ramos
- Grupo de Neurociencias, Universidad de Antioquia, SIU, Medellín, Colombia
| | - Alejandro Espinosa
- Grupo de Neurociencias, Universidad de Antioquia, SIU, Medellín, Colombia
| | - William Cho
- Genentech, a Member of the Roche Group, South San Francisco, CA, USA
| | - Michael Ward
- Genentech, a Member of the Roche Group, South San Francisco, CA, USA
| | - David Clayton
- Genentech, a Member of the Roche Group, South San Francisco, CA, USA
| | | | - Howard Mackey
- Genentech, a Member of the Roche Group, South San Francisco, CA, USA
| | - Lee Honigberg
- Genentech, a Member of the Roche Group, South San Francisco, CA, USA
| | | | - Kewei Chen
- Banner Alzheimer's Institute, Phoenix, AZ, USA
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Arnerić SP, Kern VD, Stephenson DT. Regulatory-accepted drug development tools are needed to accelerate innovative CNS disease treatments. Biochem Pharmacol 2018; 151:291-306. [PMID: 29410157 DOI: 10.1016/j.bcp.2018.01.043] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2017] [Accepted: 01/26/2018] [Indexed: 02/07/2023]
Abstract
Central Nervous System (CNS) diseases represent one of the most challenging therapeutic areas for successful drug approvals. Developing quantitative biomarkers as Drug Development Tools (DDTs) can catalyze the path to innovative treatments, and improve the chances of drug approvals. Drug development and healthcare management requires sensitive, reliable, validated, and regulatory accepted biomarkers and endpoints. This review highlights the regulatory paths and considerations for developing DDTs required to advance biomarker and endpoint use in clinical development (e.g., consensus CDISC [Clinical Data Interchange Standards Consortium] data standards, precompetitive sharing of anonymized patient-level data, and continual alignment with regulators). Summarized is the current landscape of biomarkers in a range of CNS diseases including Alzheimer disease, Parkinson Disease, Amyotrophic Lateral Sclerosis, Autism Spectrum Disorders, Depression, Huntington's disease, Multiple Sclerosis and Traumatic Brain Injury. Advancing DDTs for these devastating diseases that are both validated and qualified will require an integrated, cross-consortium approach to accelerate the delivery of innovative CNS therapeutics.
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Affiliation(s)
- Stephen P Arnerić
- Critical Path for Alzheimer's Disease, Crititcal Path Institute, United States.
| | - Volker D Kern
- Critical Path for Alzheimer's Disease, Crititcal Path Institute, United States
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Neville J, Kopko S, Romero K, Corrigan B, Stafford B, LeRoy E, Broadbent S, Cisneroz M, Wilson E, Reiman E, Vanderstichele H, Arnerić SP, Stephenson D. Accelerating drug development for Alzheimer's disease through the use of data standards. ALZHEIMERS & DEMENTIA-TRANSLATIONAL RESEARCH & CLINICAL INTERVENTIONS 2017; 3:273-283. [PMID: 29067333 PMCID: PMC5651436 DOI: 10.1016/j.trci.2017.03.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Introduction The exceedingly high rate of failed trials in Alzheimer's disease (AD) calls for immediate attention to improve efficiencies and learning from past, ongoing, and future trials. Accurate, highly rigorous standardized data are at the core of meaningful scientific research. Data standards allow for proper integration of clinical data sets and represent the essential foundation for regulatory endorsement of drug development tools. Such tools increase the potential for success and accuracy of trial results. Methods The development of the Clinical Data Interchange Standards Consortium (CDISC) AD therapeutic area data standard was a comprehensive collaborative effort by CDISC and Coalition Against Major Diseases, a consortium of the Critical Path Institute. Clinical concepts for AD and mild cognitive impairment were defined and a data standards user guide was created from various sources of input, including data dictionaries used in AD clinical trials and observational studies. Results A comprehensive collection of AD-specific clinical data standards consisting of clinical outcome measures, leading candidate genes, and cerebrospinal fluid and imaging biomarkers was developed. The AD version 2.0 (V2.0) Therapeutic Area User Guide was developed by diverse experts working with data scientists across multiple consortia through a comprehensive review and revision process. The AD CDISC standard is a publicly available resource to facilitate widespread use and implementation. Discussion The AD CDISC V2.0 data standard serves as a platform to catalyze reproducible research, data integration, and efficiencies in clinical trials. It allows for the mapping and integration of available data and provides a foundation for future studies, data sharing, and long-term registries in AD. The availability of consensus data standards for AD has the potential to facilitate clinical trial initiation and increase sharing and aggregation of data across observational studies and among clinical trials, thereby improving our understanding of disease progression and treatment.
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Affiliation(s)
| | | | | | - Brian Corrigan
- Division of Pharmacometrics, Pfizer Global Research and Development, Groton, CT, USA
| | | | | | | | - Martin Cisneroz
- College of Medicine, The University of Arizona, Tucson, AZ, USA
| | | | - Eric Reiman
- Banner Medical institute, Arizona State University, Phoenix, AZ, USA
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