Literature DB >> 23375562

Diagnostic accuracy of markers for prodromal Alzheimer's disease in independent clinical series.

Annapaola Prestia1, Anna Caroli, Karl Herholz, Eric Reiman, Kewei Chen, William J Jagust, Giovanni B Frisoni.   

Abstract

OBJECTIVE: To capitalize on data from different clinical series to compare sensitivity and specificity of individual biomarkers for predicting mild cognitive impairment (MCI) progression to Alzheimer's disease (AD).
METHODS: Medial temporal atrophy, cortical hypometabolism, and cerebrospinal fluid biomarkers were assessed in 18 patients with mild cognitive impairment (MCI) with prodromal AD (pAD; conversion time, 26 ± 12 months) and 18 stable MCI (sMCI) patients from the Translational Outpatient Memory Clinic cohort, as well as in 24 pAD patients (conversion time, 36 ± 12 months) and 33 sMCI patients from the Alzheimer's Disease Neuroimaging Initiative cohort. Medial temporal atrophy was measured by manual, semi-automated, and automated hippocampal volumetry; cortical hypometabolism was measured using several indices of AD-related hypometabolism pattern; and cerebrospinal fluid markers were amyloid β (Aβ)42 and total tau protein concentrations. For each biomarker, sensitivity for pAD, specificity for sMCI, and diagnostic accuracy were computed.
RESULTS: Sensitivity to predict MCI conversion to AD in the Alzheimer's Disease Neuroimaging Initiative and Translational Outpatient Memory Clinic cohorts was 79% and 94% based on Aβ42, 46% and 28% based on hippocampal volumes, 33% to 66% and 56% to 78% based on different hypometabolism indices, and 46% and 61% based on total tau levels, respectively. Specificity to exclude sMCI was 27% and 50% based on Aβ42, 76% and 94% based on hippocampal volumes, 58% to 67% and 55% to 83% based on different hypometabolism indices, and 61% and 83% based on total tau levels, respectively.
CONCLUSIONS: Current findings suggest that Aβ42 concentrations and hippocampal volumes may be used in combination to best identify pAD.
Copyright © 2013 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Alzheimer's disease; Diagnostic accuracy; Diagnostic test assessment; MCI; MRI; PET

Mesh:

Substances:

Year:  2013        PMID: 23375562      PMCID: PMC4058442          DOI: 10.1016/j.jalz.2012.09.016

Source DB:  PubMed          Journal:  Alzheimers Dement        ISSN: 1552-5260            Impact factor:   21.566


  39 in total

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  21 in total

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4.  Mild cognitive impairment with suspected nonamyloid pathology (SNAP): Prediction of progression.

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Review 5.  2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception.

Authors:  Michael W Weiner; Dallas P Veitch; Paul S Aisen; Laurel A Beckett; Nigel J Cairns; Jesse Cedarbaum; Robert C Green; Danielle Harvey; Clifford R Jack; William Jagust; Johan Luthman; John C Morris; Ronald C Petersen; Andrew J Saykin; Leslie Shaw; Li Shen; Adam Schwarz; Arthur W Toga; John Q Trojanowski
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Review 6.  Multimodality imaging of Alzheimer disease and other neurodegenerative dementias.

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7.  Prognostic value of Alzheimer's biomarkers in mild cognitive impairment: the effect of age at onset.

Authors:  Daniele Altomare; Clarissa Ferrari; Anna Caroli; Samantha Galluzzi; Annapaola Prestia; Wiesje M van der Flier; Rik Ossenkoppele; Bart Van Berckel; Frederik Barkhof; Charlotte E Teunissen; Anders Wall; Stephen F Carter; Michael Schöll; I L Han Choo; Timo Grimmer; Alberto Redolfi; Agneta Nordberg; Philip Scheltens; Alexander Drzezga; Giovanni B Frisoni
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8.  Structural covariance of the default network in healthy and pathological aging.

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10.  Reliability of a novel serious game using dual-task gait profiles to early characterize aMCI.

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