Can neurocognitive assessment be a lower-cost substitute for biomarkers in predicting progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD)? A narrative review
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Elsevier B.V.
Abstract
The challenge to find the best predictors of conversion from Mild Cognitive Impairment (MCI) to Alzheimer's disease (AD) has been ongoing at least for the last decade. Nonetheless, clinicians still lack, to date, a robust predictive tool for identifying individuals who will go through this conversion. In this narrative review, we reported the sensitivity and specificity of biomarkers and neurocognitive assessment in predicting the progression from MCI to AD. Given that biomarkers do not necessarily provide a better predictive accuracy as showcased by the numbers in this study, cognitive tests seem like a more cost-effective, less invasive, and easily accessible option. They also offer the added benefit of measuring functional cognitive impairment. However, it remains clear that efforts are still needed to come up with more accurate, sensitive, and specific predictors. © 2023 The Authors
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Alzheimer's disease, Biomarkers, Mild cognitive impairment, Neurocognitive assessment, Neuropsychological testing, Predictive accuracy, Amyloid beta protein[1-42], Biological marker, Fluorodeoxyglucose, Pittsburgh compound b, Tau protein, Alzheimer disease, Article, Attention network test, Boston diagnostic aphasia examination, Boston naming test, Buschke selective reminding test, Cognition assessment, Controlled oral word association test, Cost effectiveness analysis, Deep learning, Diagnostic accuracy, Diagnostic test accuracy study, Disease course, Ensemble multiple kernel learning, Episodic memory, Executive function, Human, In vivo study, Intermethod comparison, K nearest neighbor, Language, Low income country, Machine learning, Memory index score, Mini mental state examination, Montreal cognitive assessment, Neuropsychological assessment, Nuclear magnetic resonance imaging, Positron emission tomography, Prediction, Predictive value, Random forest, Sensitivity and specificity, Single photon emission computed tomography, Support vector machine, Wechsler adult intelligence scale, Wechsler memory scale