Mostrar el registro sencillo del ítem

dc.contributor.author
Curcic, Jelena  
dc.contributor.author
Vallejo, Vanessa  
dc.contributor.author
Sorinas, Jennifer  
dc.contributor.author
Sverdlov, Oleksandr  
dc.contributor.author
Praestgaard, Jens  
dc.contributor.author
Piksa, Mateusz  
dc.contributor.author
Deurinck, Mark  
dc.contributor.author
Erdemli, Gul  
dc.contributor.author
Bügler, Maximilian  
dc.contributor.author
Tarnanas, Ioannis  
dc.contributor.author
Taptiklis, Nick  
dc.contributor.author
Cormack, Francesca  
dc.contributor.author
Anker, Rebekka  
dc.contributor.author
Massé, Fabien  
dc.contributor.author
Mandar, William Souillard  
dc.contributor.author
Intrator, Nathan  
dc.contributor.author
Molcho, Lior  
dc.contributor.author
Madero, Erica  
dc.contributor.author
Bott, Nicholas  
dc.contributor.author
Chambers, Mieko  
dc.contributor.author
Tamory, Josef  
dc.contributor.author
Shulz, Matias  
dc.contributor.author
Fernández, Gerardo Abel  
dc.contributor.author
Simpson, William  
dc.contributor.author
Robin, Jessica  
dc.contributor.author
Snædal, Jón G.  
dc.contributor.author
Cha, Jang Ho  
dc.contributor.author
Hannesdottir, Kristin  
dc.date.available
2023-07-04T13:59:34Z  
dc.date.issued
2022-08  
dc.identifier.citation
Curcic, Jelena; Vallejo, Vanessa; Sorinas, Jennifer; Sverdlov, Oleksandr; Praestgaard, Jens; et al.; Description of the method for evaluating digital endpoints in alzheimer disease study: protocol for an exploratory, cross-sectional study; JMIR Publications Inc.; JMIR Research Protocols; 11; 8; 8-2022; 1-16  
dc.identifier.issn
1929-0748  
dc.identifier.uri
http://hdl.handle.net/11336/202238  
dc.description.abstract
Background: More sensitive and less burdensome efficacy end points are urgently needed to improve the effectiveness of clinical drug development for Alzheimer disease (AD). Although conventional end points lack sensitivity, digital technologies hold promise for amplifying the detection of treatment signals and capturing cognitive anomalies at earlier disease stages. Using digital technologies and combining several test modalities allow for the collection of richer information about cognitive and functional status, which is not ascertainable via conventional paper-and-pencil tests. Objective: This study aimed to assess the psychometric properties, operational feasibility, and patient acceptance of 10 promising technologies that are to be used as efficacy end points to measure cognition in future clinical drug trials. Methods: The Method for Evaluating Digital Endpoints in Alzheimer Disease study is an exploratory, cross-sectional, noninterventional study that will evaluate 10 digital technologies' ability to accurately classify participants into 4 cohorts according to the severity of cognitive impairment and dementia. Moreover, this study will assess the psychometric properties of each of the tested digital technologies, including the acceptable range to assess ceiling and floor effects, concurrent validity to correlate digital outcome measures to traditional paper-and-pencil tests in AD, reliability to compare test and retest, and responsiveness to evaluate the sensitivity to change in a mild cognitive challenge model. This study included 50 eligible male and female participants (aged between 60 and 80 years), of whom 13 (26%) were amyloid-negative, cognitively healthy participants (controls); 12 (24%) were amyloid-positive, cognitively healthy participants (presymptomatic); 13 (26%) had mild cognitive impairment (predementia); and 12 (24%) had mild AD (mild dementia). This study involved 4 in-clinic visits. During the initial visit, all participants completed all conventional paper-and-pencil assessments. During the following 3 visits, the participants underwent a series of novel digital assessments. Results: Participant recruitment and data collection began in June 2020 and continued until June 2021. Hence, the data collection occurred during the COVID-19 pandemic (SARS-CoV-2 virus pandemic). Data were successfully collected from all digital technologies to evaluate statistical and operational performance and patient acceptance. This paper reports the baseline demographics and characteristics of the population studied as well as the study's progress during the pandemic. Conclusions: This study was designed to generate feasibility insights and validation data to help advance novel digital technologies in clinical drug development. The learnings from this study will help guide future methods for assessing novel digital technologies and inform clinical drug trials in early AD, aiming to enhance clinical end point strategies with digital technologies.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
JMIR Publications Inc.  
dc.rights
info:eu-repo/semantics/restrictedAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
ALZHEIMER DISEASE  
dc.subject
BRAIN AMYLOID  
dc.subject
CLINICAL TRIAL DESIGN  
dc.subject
COGNITION  
dc.subject
DIGITAL ENDPOINTS  
dc.subject
METHODOLOGY STUDY  
dc.subject
MOBILE PHONE  
dc.subject.classification
Biotecnología relacionada con la Salud  
dc.subject.classification
Biotecnología de la Salud  
dc.subject.classification
CIENCIAS MÉDICAS Y DE LA SALUD  
dc.title
Description of the method for evaluating digital endpoints in alzheimer disease study: protocol for an exploratory, cross-sectional study  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2023-05-11T17:48:05Z  
dc.journal.volume
11  
dc.journal.number
8  
dc.journal.pagination
1-16  
dc.journal.pais
Canadá  
dc.description.fil
Fil: Curcic, Jelena. Novartis Institutes for Biomedical Research; Suiza  
dc.description.fil
Fil: Vallejo, Vanessa. Novartis Institutes for Biomedical Research; Suiza  
dc.description.fil
Fil: Sorinas, Jennifer. Novartis Institutes for Biomedical Research; Suiza  
dc.description.fil
Fil: Sverdlov, Oleksandr. Novartis Pharmaceuticals Corporation; Estados Unidos  
dc.description.fil
Fil: Praestgaard, Jens. Novartis Institutes for Biomedical Research; Suiza  
dc.description.fil
Fil: Piksa, Mateusz. Novartis Institutes for Biomedical Research; Suiza  
dc.description.fil
Fil: Deurinck, Mark. Novartis Institutes for Biomedical Research; Suiza  
dc.description.fil
Fil: Erdemli, Gul. Novartis Institutes for Biomedical Research; Estados Unidos  
dc.description.fil
Fil: Bügler, Maximilian. Altoida Inc; Estados Unidos  
dc.description.fil
Fil: Tarnanas, Ioannis. Altoida Inc; Estados Unidos  
dc.description.fil
Fil: Taptiklis, Nick. Cambridge Cognition Ltd; Reino Unido  
dc.description.fil
Fil: Cormack, Francesca. Cambridge Cognition Ltd; Reino Unido  
dc.description.fil
Fil: Anker, Rebekka. MindMaze SA; Suiza  
dc.description.fil
Fil: Massé, Fabien. MindMaze SA; Suiza  
dc.description.fil
Fil: Mandar, William Souillard. Massachusetts Institute of Technology; Estados Unidos  
dc.description.fil
Fil: Intrator, Nathan. Neurosteer Inc.; Estados Unidos  
dc.description.fil
Fil: Molcho, Lior. Neurosteer Inc.; Estados Unidos  
dc.description.fil
Fil: Madero, Erica. Neurotrack Technologies Inc; Estados Unidos  
dc.description.fil
Fil: Bott, Nicholas. University of Stanford; Estados Unidos  
dc.description.fil
Fil: Chambers, Mieko. Neurovision Imaging Inc; Estados Unidos  
dc.description.fil
Fil: Tamory, Josef. Neurovision Imaging Inc; Estados Unidos  
dc.description.fil
Fil: Shulz, Matias. ViewMind Inc; Estados Unidos  
dc.description.fil
Fil: Fernández, Gerardo Abel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; Argentina  
dc.description.fil
Fil: Simpson, William. Winterlight Labs; Canadá  
dc.description.fil
Fil: Robin, Jessica. Winterlight Labs; Canadá  
dc.description.fil
Fil: Snædal, Jón G.. Memory Clinic; Islandia  
dc.description.fil
Fil: Cha, Jang Ho. Novartis Institutes for Biomedical Research; Estados Unidos  
dc.description.fil
Fil: Hannesdottir, Kristin. Novartis Institutes for Biomedical Research; Estados Unidos  
dc.journal.title
JMIR Research Protocols  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.2196/35442  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.researchprotocols.org/2022/8/e35442