Curcic Jelena, Vallejo Vanessa, Sorinas Jennifer, Sverdlov Oleksandr, Praestgaard Jens, Piksa Mateusz, Deurinck Mark, Erdemli Gul, Bügler Maximilian, Tarnanas Ioannis, Taptiklis Nick, Cormack Francesca, Anker Rebekka, Massé Fabien, Souillard-Mandar William, Intrator Nathan, Molcho Lior, Madero Erica, Bott Nicholas, Chambers Mieko, Tamory Josef, Shulz Matias, Fernandez Gerardo, Simpson William, Robin Jessica, Snædal Jón G, Cha Jang-Ho, Hannesdottir Kristin
Novartis Institutes for Biomedical Research, Basel, Switzerland.
Novartis Pharmaceuticals Corporation, East Hanover, NJ, United States.
JMIR Res Protoc. 2022 Aug 10;11(8):e35442. doi: 10.2196/35442.
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.
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.
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.
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.
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.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/35442.
迫切需要更敏感且负担更小的疗效终点，以提高阿尔茨海默病（AD）临床药物研发的有效性。尽管传统终点缺乏敏感性，但数字技术有望增强治疗信号的检测，并在疾病早期阶段捕捉认知异常。使用数字技术并结合多种测试方式，能够收集到关于认知和功能状态的更丰富信息，而这是通过传统纸笔测试无法确定的。
本研究旨在评估10种有前景的技术的心理测量特性、操作可行性以及患者接受度，这些技术将在未来的临床药物试验中用作测量认知的疗效终点。
阿尔茨海默病数字终点评估方法研究是一项探索性、横断面、非干预性研究，将评估10种数字技术根据认知障碍和痴呆严重程度将参与者准确分类为4个队列的能力。此外，本研究将评估每种测试数字技术的心理测量特性，包括评估天花板效应和地板效应的可接受范围、将数字结果测量与AD传统纸笔测试相关联的同时效度、比较测试和重测的信度，以及在轻度认知挑战模型中评估对变化敏感性的反应度。本研究纳入了50名符合条件的男性和女性参与者（年龄在60至80岁之间），其中13名（26%）为淀粉样蛋白阴性、认知健康的参与者（对照组）；12名（24%）为淀粉样蛋白阳性、认知健康的参与者（症状前组）；13名（26%）有轻度认知障碍（轻度痴呆前期）；12名（24%）患有轻度AD（轻度痴呆）。本研究包括4次门诊就诊。在初次就诊时，所有参与者完成了所有传统纸笔评估。在接下来的3次就诊中，参与者接受了一系列新颖的数字评估。
参与者招募和数据收集于2020年6月开始，持续至2021年6月。因此，数据收集发生在新冠疫情（严重急性呼吸综合征冠状病毒2病毒大流行）期间。已成功从所有数字技术收集数据，以评估统计和操作性能以及患者接受度。本文报告了所研究人群的基线人口统计学和特征以及疫情期间的研究进展。
本研究旨在生成可行性见解和验证数据，以帮助推进临床药物研发中的新型数字技术。本研究的经验教训将有助于指导未来评估新型数字技术的方法，并为早期AD的临床药物试验提供信息，旨在通过数字技术增强临床终点策略。
国际注册报告识别码（IRRID）：DERR1-10.2196/35442。
