Predictive value of ATN biomarker profiles in estimating disease progression in Alzheimer's disease dementia.

ABSTRACT: We aimed to evaluate the value of ATN biomarker classification system (amyloid beta [A], pathologic tau [T], and neurodegeneration [N]) for predicting conversion from mild cognitive impairment (MCI) to dementia. In a sample of people with MCI (n = 415) we assessed predictive performance of ATN classification using empirical knowledge-based cut-offs for each component of ATN and compared it to two data-driven approaches, logistic regression and RUSBoost machine learning classifiers, which used continuous clinical or biomarker scores. In data-driven approaches, we identified ATN features that distinguish normals from individuals with dementia and used them to classify persons with MCI into dementia-like and normal groups. Both data-driven classification methods performed better than the empi

SUBMITTER: Ezzati A 

PROVIDER: S-EPMC8842842 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature