Literature DB >> 29365053

Predicting progression from normal cognition to mild cognitive impairment for individuals at 5 years.

Marilyn Albert1, Yuxin Zhu2, Abhay Moghekar1, Susumu Mori3, Michael I Miller4, Anja Soldan1, Corinne Pettigrew1, Ola Selnes1, Shanshan Li5, Mei-Cheng Wang2.   

Abstract

Recent evidence indicates that measures from cerebrospinal fluid, MRI scans and cognitive testing obtained from cognitively normal individuals can be used to predict likelihood of progression to mild cognitive impairment several years later, for groups of individuals. However, it remains unclear whether these measures are useful for predicting likelihood of progression for an individual. The increasing focus on early intervention in clinical trials for Alzheimer's disease emphasizes the importance of improving the ability to identify which cognitively normal individuals are more likely to progress over time, thus allowing researchers to efficiently screen participants, as well as determine the efficacy of any treatment intervention. The goal of this study was to determine which measures, obtained when individuals were cognitively normal, predict on an individual basis, the onset of clinical symptoms associated with a diagnosis of mild cognitive impairment due to Alzheimer's disease. Cognitively normal participants (n = 224, mean baseline age = 57 years) were evaluated with a range of measures, including: cerebrospinal fluid amyloid-β and phosphorylated-tau, hippocampal and entorhinal cortex volume, cognitive tests scores and APOE genotype. They were then followed to determine which individuals developed mild cognitive impairment over time (mean follow-up = 11 years). The primary outcome was progression from normal cognition to the onset of clinical symptoms of mild cognitive impairment due to Alzheimer's disease at 5 years post-baseline. Time-dependent receiver operating characteristic analyses examined the sensitivity and specificity of individual measures, and combinations of measures, as predictors of the outcome. Six measures, in combination, were the most parsimonious predictors of transition to mild cognitive impairment 5 years after baseline (area under the curve = 0.85; sensitivity = 0.80, specificity = 0.75). The addition of variables from each domain significantly improved the accuracy of prediction. The incremental accuracy of prediction achieved by adding individual measures or sets of measures successively to one another was also examined, as might be done when enrolling individuals in a clinical trial. The results indicate that biomarkers obtained when individuals are cognitively normal can be used to predict which individuals are likely to develop clinical symptoms at 5 years post-baseline. As a number of the measures included in the study could also be used as subject selection criteria in a clinical trial, the findings also provide information about measures that would be useful for screening in a clinical trial aimed at individuals with preclinical Alzheimer's disease.

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Year:  2018        PMID: 29365053      PMCID: PMC5837651          DOI: 10.1093/brain/awx365

Source DB:  PubMed          Journal:  Brain        ISSN: 0006-8950            Impact factor:   13.501


  37 in total

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Authors:  Abhay Moghekar; Shanshan Li; Yi Lu; Ming Li; Mei-Cheng Wang; Marilyn Albert; Richard O'Brien
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7.  Quantitative and histologically validated measures of the entorhinal subfields in ex vivo MRI.

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8.  Deep Learning Prediction of Mild Cognitive Impairment using Electronic Health Records.

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Review 9.  Clinical diagnosis of Alzheimer's disease: recommendations of the International Working Group.

Authors:  Bruno Dubois; Nicolas Villain; Giovanni B Frisoni; Gil D Rabinovici; Marwan Sabbagh; Stefano Cappa; Alexandre Bejanin; Stéphanie Bombois; Stéphane Epelbaum; Marc Teichmann; Marie-Odile Habert; Agneta Nordberg; Kaj Blennow; Douglas Galasko; Yaakov Stern; Christopher C Rowe; Stephen Salloway; Lon S Schneider; Jeffrey L Cummings; Howard H Feldman
Journal:  Lancet Neurol       Date:  2021-04-29       Impact factor: 59.935

10.  Comparison of the predictive accuracy of multiple definitions of cognitive impairment for incident dementia: a 20-year follow-up of the Whitehall II cohort study.

Authors:  Marcos D Machado-Fragua; Aline Dugravot; Julien Dumurgier; Mika Kivimaki; Andrew Sommerlad; Benjamin Landré; Aurore Fayosse; Séverine Sabia; Archana Singh-Manoux
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