Decentralized clinical trials for medications to reduce the risk of dementia: Consensus report and guidance.

Leanne Howard, Carla Abdelnour,Erin L Abner, Ricardo F Allegri,Hiroko H Dodge,Serge Gauthier,Camilla M Hoyos, Gregory A Jicha,Patrick G Kehoe, Catherine J Mummery, Adesola Ogunniyi,Nikolaos Scarmeas,Xiaoying Chen, Jodie R Titiner, Christopher R Weber, Clinical Trial Methodology Working review group members,Ruth Peters

Alzheimer's & dementia : the journal of the Alzheimer's Association(2024)

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摘要
INTRODUCTION:Recent growth in the functionality and use of technology has prompted an increased interest in the potential for remote or decentralized clinical trials in dementia. There are many potential benefits associated with decentralized medication trials, but we currently lack specific recommendations for their delivery in the dementia field. METHODS:A modified Delphi method engaged an expert panel to develop recommendations for the conduct of decentralized medication trials in dementia prevention. A working group of researchers and clinicians with expertise in dementia trials further refined the recommendations. RESULTS:Overall, the recommendations support the delivery of decentralized trials in dementia prevention provided adequate safety checks and balances are included. A total of 40 recommendations are presented, spanning aspects of decentralized clinical trials, including safety, dispensing, outcome assessment, and data collection. DISCUSSION:These recommendations provide an accessible, pragmatic guide for the design and conduct of remote medication trials for dementia prevention. HIGHLIGHTS:Clinical trials of medication have begun adopting decentralized approaches. Researchers in the field lack guidance on what would be appropriate circumstances and frameworks for what would be appropriate circumstances and frameworks for the use of decentralized trial methods in dementia prevention. The present report provides consensus-based expert recommendations for decentralized clinical trials for dementia prevention.
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