Dataset Information

A Comprehensive Visual Rating Scale for Predicting Progression from Mild Cognitive Impairment to Dementia in Patients with Alzheimer's Pathology or Suspected Non-Alzheimer's Pathology.

ABSTRACT:

Background and purpose

To identify biomarkers for prediction of the progression to dementia in mild cognitive impairment (MCI) patients, evaluation of brain structure changes has been validated by a comprehensive visual grading scale (CVRS) through magnetic resonance imaging (MRI). In this study, we specifically elucidated for the cognitive change of MCI patients classified based on AT(N) pathological status classification during the follow-up period of 3 years through the CVRS.

Methods

The 301 patients with initial MCI visited at least once for follow-up period. The data used in this study were obtained from the Alzheimer's disease (AD) Neuroimaging Initiative study. Brain atrophy was assessed by CVRS using MRI. AT(N) profiles were classified by cerebrospinal fluid abnormality. Based on the AT(N) assessment, all individuals in this study were divided into 3 groups (normal state biomarker, suspected non-Alzheimer's pathology [SNAP], or Alzheimer's continuum). The cox regression was used to analyze the hazard ratios of CVRS for progression to dementia.

Results

Sixty-three progressed and 238 remained stable to dementia and the CVRS (mean±standard deviation) had significant difference between progressive MCI and stable MCI (p<0.001). Univariate and multivariate cox regression results (p<0.001) showed the independence of initial CVRS as a predictor for the progression to dementia. Moreover, comparing the classified AT(N) pathology group, SNAP and AD, effectiveness of CVRS as a predictor was verified only in Alzheimer's continuum.

Conclusions

The initial CVRS score as a predictor of dementia progression was independently validated at the stage of Alzheimer's progression among AT(N) pathologically differentiated MCI.

SUBMITTER: Park SW

PROVIDER: S-EPMC7781734 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

A Comprehensive Visual Rating Scale for Predicting Progression from Mild Cognitive Impairment to Dementia in Patients with Alzheimer's Pathology or Suspected Non-Alzheimer's Pathology.

Park Sang Won SW Kim Seongheon S Park Jeonghoon J Jang Jae Won JW Kim SangYun S

Dementia and neurocognitive disorders 20201201 4

<h4>Background and purpose</h4>To identify biomarkers for prediction of the progression to dementia in mild cognitive impairment (MCI) patients, evaluation of brain structure changes has been validated by a comprehensive visual grading scale (CVRS) through magnetic resonance imaging (MRI). In this study, we specifically elucidated for the cognitive change of MCI patients classified based on AT(N) pathological status classification during the follow-up period of 3 years through the CVRS.<h4>Metho ...[more]

PMID: 33377666

Similar Datasets

Project description:BackgroundIndividuals with mild cognitive impairment (MCI) have a substantially increased risk of developing dementia due to Alzheimer's disease (AD). In this study, we developed a multivariate prognostic model for predicting MCI-to-dementia progression at the individual patient level.MethodsUsing baseline data from 259 MCI patients and a probabilistic, kernel-based pattern classification approach, we trained a classifier to distinguish between patients who progressed to AD-type dementia (n = 139) and those who did not (n = 120) during a three-year follow-up period. More than 750 variables across four data sources were considered as potential predictors of progression. These data sources included risk factors, cognitive and functional assessments, structural magnetic resonance imaging (MRI) data, and plasma proteomic data. Predictive utility was assessed using a rigorous cross-validation framework.ResultsCognitive and functional markers were most predictive of progression, while plasma proteomic markers had limited predictive utility. The best performing model incorporated a combination of cognitive/functional markers and morphometric MRI measures and predicted progression with 80% accuracy (83% sensitivity, 76% specificity, AUC = 0.87). Predictors of progression included scores on the Alzheimer's Disease Assessment Scale, Rey Auditory Verbal Learning Test, and Functional Activities Questionnaire, as well as volume/cortical thickness of three brain regions (left hippocampus, middle temporal gyrus, and inferior parietal cortex). Calibration analysis revealed that the model is capable of generating probabilistic predictions that reliably reflect the actual risk of progression. Finally, we found that the predictive accuracy of the model varied with patient demographic, genetic, and clinical characteristics and could be further improved by taking into account the confidence of the predictions.ConclusionsWe developed an accurate prognostic model for predicting MCI-to-dementia progression over a three-year period. The model utilizes widely available, cost-effective, non-invasive markers and can be used to improve patient selection in clinical trials and identify high-risk MCI patients for early treatment.

Dataset Information

A Comprehensive Visual Rating Scale for Predicting Progression from Mild Cognitive Impairment to Dementia in Patients with Alzheimer's Pathology or Suspected Non-Alzheimer's Pathology.

Background and purpose

Methods

Results

Conclusions

Publications

A Comprehensive Visual Rating Scale for Predicting Progression from Mild Cognitive Impairment to Dementia in Patients with Alzheimer's Pathology or Suspected Non-Alzheimer's Pathology.

Similar Datasets

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