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Description of the Method for Evaluating Digital Endpoints in Alzheimer Disease Study: Protocol for an Exploratory, Cross-sectional Study

Authors :
Jelena Curcic
Vanessa Vallejo
Jennifer Sorinas
Oleksandr Sverdlov
Jens Praestgaard
Mateusz Piksa
Mark Deurinck
Gul Erdemli
Maximilian Bügler
Ioannis Tarnanas
Nick Taptiklis
Francesca Cormack
Rebekka Anker
Fabien Massé
William Souillard-Mandar
Nathan Intrator
Lior Molcho
Erica Madero
Nicholas Bott
Mieko Chambers
Josef Tamory
Matias Shulz
Gerardo Fernandez
William Simpson
Jessica Robin
Jón G Snædal
Jang-Ho Cha
Kristin Hannesdottir
Source :
JMIR Research Protocols, Vol 11, Iss 8, p e35442 (2022)
Publication Year :
2022
Publisher :
JMIR Publications, 2022.

Abstract

BackgroundMore 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. ObjectiveThis 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. MethodsThe 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. ResultsParticipant 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. ConclusionsThis 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. International Registered Report Identifier (IRRID)DERR1-10.2196/35442

Details

Language :
English
ISSN :
19290748
Volume :
11
Issue :
8
Database :
Directory of Open Access Journals
Journal :
JMIR Research Protocols
Publication Type :
Academic Journal
Accession number :
edsdoj.3350c32a2b146b7b2079f8e8be5bd3b
Document Type :
article
Full Text :
https://doi.org/10.2196/35442