4.5 Article

Amyloid-PET imaging offers small improvements in predictions of future cognitive trajectories

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NEUROIMAGE-CLINICAL
卷 31, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.nicl.2021.102713

关键词

Alzheimer's disease; amyloid-PET; Prediction; Cognitive change; Longitudinal studies

资金

  1. NIA [R01AG057869, P30 010129, R01 AG047827, R01 AG 031563, RF1 AG050782 RF1 AG052132, R00AG053410]

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This study investigated the added value of amyloid-PET measures in predicting future cognitive changes over and above sociodemographics and past cognitive measures. The results suggest that when repeated cognitive assessments are available, the additional utility of amyloid-PET in predicting future cognitive impairment may be limited.
Background: Amyloid beta (A beta) is thought to initiate a cascade of pathology culminating in Alzheimer's disease related cognitive decline. A beta accumulation in brain tissues may begin one to two decades prior to clinical diagnosis of Alzheimer's disease. Prior studies have demonstrated that A beta detected in vivo with positron emission tomography with amyloid ligands (amyloid-PET) predicts contemporaneously measured cognition and future cognitive trajectories. Prior studies have not evaluated the added value of A beta measures in predicting future cognition when repeated past cognitive measures are available. We evaluated the extent to which amyloid-PET improves prediction of future cognitive changes over and above predictions based only on sociodemographics and past cognitive measures. Methods: We used data from participants in the University of California Davis Alzheimer's Disease Research cohort who were cognitively normal at baseline, participated in amyloid-PET imaging, and completed at least three cognitive assessments prior to amyloid-PET imaging (N = 132 for memory andN = 135 for executive function). We used sociodemographic and cognitive measures taken prior to amyloid-PET imaging to predict cognitive trajectory after amyloid-PET imaging and assessed whether measures of amyloid burden improved predictions of subsequent cognitive change. Improvements in prediction were characterized as percent reduction in the mean squared error (MSE) in predicted cognition post amyloid-PET and increase in percent variance explained. Results: The base model using only sociodemographics and past cognitive performance explained the majority of variance in both predicted memory measures (55.6%) and executive function measures (74.5%) following amyloid-PET. Adding amyloid positivity to the model reduced the MSE for memory by 0.2%, 95% CI: (0%, 2.6%), p = 0.48 and for executive function by 3.4%, 95% CI: (0.6%, 10.2%), p = 0.002. This corresponded to an increase in the percent variance explained of 0.1%, 95% CI: (0%, 1.2%) for memory and 0.9%, 95% CI: (0.1%, 2.8%) for executive function. Similar results were obtained using a continuous measure of amyloid burden. Conclusion: In this cohort, the addition of amyloid burden slightly improved predictions of executive function compared to models based only on past cognitive assessments and sociodemographics. When repeated cognitive assessments are available, the additional utility of amyloid-PET in predicting future cognitive impairment may be limited.

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