Details

Autor(en) / Beteiligte

• McKay, Nicole S.
• Millar, Peter R.
• Nicosia, Jessica
• Aschenbrenner, Andrew J.
• Gordon, Brian A.
• Benzinger, Tammie L. S.
• Cruchaga, Carolos C.
• Schindler, Suzanne E.
• Morris, John C.
• Hassenstab, Jason
• Yeates, Keith Owen

Titel

Pick a PACC: Comparing Domain-Specific and General Cognitive Composites in Alzheimer Disease Research

Ist Teil von

• Neuropsychology, 2024-07, Vol.38 (5), p.443-464

Ort / Verlag

United States: American Psychological Association

Erscheinungsjahr

2024

Quelle

EBSCOhost APA PsycARTICLES

Beschreibungen/Notizen

• Objective: We aimed to illustrate how complex cognitive data can be used to create domain-specific and general cognitive composites relevant to Alzheimer disease research. Method: Using equipercentile equating, we combined data from the Charles F. and Joanne Knight Alzheimer Disease Research Center that spanned multiple iterations of the Uniform Data Set. Exploratory factor analyses revealed four domain-specific composites representing episodic memory, semantic memory, working memory, and attention/processing speed. The previously defined preclinical Alzheimer disease cognitive composite (PACC) and a novel alternative, the Knight-PACC, were also computed alongside a global composite comprising all available tests. These three composites allowed us to compare the usefulness of domain and general composites in the context of predicting common Alzheimer disease biomarkers. Results: General composites slightly outperformed domain-specific metrics in predicting imaging-derived amyloid, tau, and neurodegeneration burden. Power analyses revealed that the global, Knight-PACC, and attention and processing speed composites would require the smallest sample sizes to detect cognitive change in a clinical trial, while the Alzheimer Disease Cooperative Study-PACC required two to three times as many participants. Conclusions: Analyses of cognition with the Knight-PACC and our domain-specific composites offer researchers flexibility by providing validated outcome assessments that can equate across test versions to answer a wide range of questions regarding cognitive decline in normal aging and neurodegenerative disease. Key Points Question: What is the key question this article addresses? Can inconsistent cognitive data be used to create meaningful domain-specific and general cognitive composites relevant to Alzheimer disease research. Findings: What are the primary findings? Factor analyses reveal four underlying composites within Uniform Data Set cognitive data: episodic memory, semantic memory, working memory, and attention and processing speed. Importance: What are the key scientific and practical implications of the findings? The mini mental state examination may not be appropriate to be included within cognitive composites, which are being designed to detect cognitive decline in the context of clinical trials. Next Steps: What directions should be explored in future research? These domain-specific metrics could be used to complement research on general cognitive decline in Alzheimer disease, particularly in individuals presenting with atypical presentations of Alzheimer disease.