Commentary on Composite cognitive and functional measures for early stage Alzheimer's disease trials.
Commentary on Composite cognitive and functional measures for early stage Alzheimer's disease trials.
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DOI:
10.1002/dad2.12012
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发表时间:
2020
期刊:
影响因子:
--
通讯作者:
Papp KV
中科院分区:
文献类型:
--
作者:
Rentz DM;Papp KV
Demonstrating that disease-modifying treatments are effective and clinically meaningful across the Alzheimer disease (AD) continuum has led to the development of psychometric composites that attempt to capture a broad range of cognitive and functional changes characteristic of the AD trajectory. As Schneider and Goldberg (2019) point out, composite scales are not new to the clinical trial arena, but they are increasingly more attractive as treatment has moved into earlier preclinical stages of AD. Herein the authors provide a critical review of 12 such composites that were developed as primary outcome measures for AD clinical trials. They argue, however, that the development of these scales has been implemented without attention to basic psychometric principals, absence of alternate forms, and validation outside its use in the clinical trial (Schneider & Goldberg, 2019). They further argue that these composite measures may not fit the realities of the clinical phenotypes or neurobiology of AD. In this commentary, we address several criticisms of the authors from our perspective of deriving composites for secondary AD prevention trials (specifically, the Preclinical Alzheimer’s Cognitive Composite [PACC]). We will speak to (1) the value of cognitive composites in favor of a single cognitive test or domain score;(2) the psychometric validation of these composites prior to use in a clinical trial, and (3) considerations made in selecting PACC measures in the context of the clinical phenotype and neurobiology of AD. Most clinical trials for AD have been completed at symptomatic stages of disease. Our field’s recent shift toward secondary prevention has necessitated a corresponding evolution in cognitive outcomes that are able to capture more subtle cognitive change at the preclinical stage of AD. This need, combined with the available longitudinal and biomarker data from observational studies in older adults, has reenergized both neuropsychologists and statisticians to use both datadriven and theoretically driven approaches to develop and iterate on