Format

Send to

Choose Destination
Alzheimers Res Ther. 2015 Nov 5;7(1):68. doi: 10.1186/s13195-015-0152-z.

Predicting Alzheimer's disease development: a comparison of cognitive criteria and associated neuroimaging biomarkers.

Author information

1
LC Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Rm A4 21, Toronto, Ontario, M4N 3 M5, Canada. brandy.callahan@sri.utoronto.ca.
2
Heart & Stroke Foundation Canadian Partnership in Stroke Recovery, Sunnybrook Health Sciences Centre, Toronto, Canada. brandy.callahan@sri.utoronto.ca.
3
Sunnybrook Health Sciences Centre, Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Canada. brandy.callahan@sri.utoronto.ca.
4
Université Laval, Faculté de médecine (Radiologie), Québec, Canada. brandy.callahan@sri.utoronto.ca.
5
Centre de recherche de l'Institut universitaire en santé mentale de Québec, Québec, Canada. brandy.callahan@sri.utoronto.ca.
6
LC Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Rm A4 21, Toronto, Ontario, M4N 3 M5, Canada. joelr@sri.utoronto.ca.
7
Heart & Stroke Foundation Canadian Partnership in Stroke Recovery, Sunnybrook Health Sciences Centre, Toronto, Canada. joelr@sri.utoronto.ca.
8
Sunnybrook Health Sciences Centre, Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Canada. joelr@sri.utoronto.ca.
9
LC Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Rm A4 21, Toronto, Ontario, M4N 3 M5, Canada. cberezuk@sri.utoronto.ca.
10
Heart & Stroke Foundation Canadian Partnership in Stroke Recovery, Sunnybrook Health Sciences Centre, Toronto, Canada. cberezuk@sri.utoronto.ca.
11
Sunnybrook Health Sciences Centre, Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Canada. cberezuk@sri.utoronto.ca.
12
Université Laval, Faculté de médecine (Radiologie), Québec, Canada. simon.duchesne@fmed.ulaval.ca.
13
Centre de recherche de l'Institut universitaire en santé mentale de Québec, Québec, Canada. simon.duchesne@fmed.ulaval.ca.
14
LC Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Rm A4 21, Toronto, Ontario, M4N 3 M5, Canada. sandra.black@sunnybrook.ca.
15
Heart & Stroke Foundation Canadian Partnership in Stroke Recovery, Sunnybrook Health Sciences Centre, Toronto, Canada. sandra.black@sunnybrook.ca.
16
Sunnybrook Health Sciences Centre, Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Canada. sandra.black@sunnybrook.ca.
17
Department of Medicine (Neurology), University of Toronto, Institute of Medical Science, Québec, Canada. sandra.black@sunnybrook.ca.

Abstract

INTRODUCTION:

The definition of "objective cognitive impairment" in current criteria for mild cognitive impairment (MCI) varies considerably between research groups and clinics. This study aims to compare different methods of defining memory impairment to improve prediction models for the development of Alzheimer's disease (AD) from baseline to 24 months.

METHODS:

The sensitivity and specificity of six methods of defining episodic memory impairment (< -1, -1.5 or -2 standard deviations [SD] on one or two memory tests) were compared in 494 non-demented seniors from the Alzheimer's Disease Neuroimaging Initiative using the area under the curve (AUC) for receiver operating characteristic analysis. The added value of non-memory measures (language and executive function) and biomarkers (hippocampal and white-matter hyperintensity volume, brain parenchymal fraction [BPF], and APOEε4 status) was investigated using logistic regression.

RESULTS:

Baseline scores < -1 SD on two memory tests predicted AD with 75.91 % accuracy (AUC = 0.80). Only APOE ε4 status further improved prediction (B = 1.10, SE = 0.45, p = .016). A < -1.5 SD cut-off on one test had 66.60 % accuracy (AUC = 0.77). Prediction was further improved using Trails B/A ratio (B = 0.27, SE = 0.13, p = .033), BPF (B = -15.97, SE = 7.58, p = .035), and APOEε4 status (B = 1.08, SE = 0.45, p = .017). A cut-off of < -2 SD on one memory test (AUC = 0.77, SE = 0.03, 95 % CI 0.72-0.82) had 76.52 % accuracy in predicting AD. Trails B/A ratio (B = 0.31, SE = 0.13, p = .017) and APOE ε4 status (B = 1.07, SE = 0.46, p = .019) improved predictive accuracy.

CONCLUSIONS:

Episodic memory impairment in MCI should be defined as scores < -1 SD below normative references on at least two measures. Clinicians or researchers who administer a single test should opt for a more stringent cut-off and collect and analyze whole-brain volume. When feasible, ascertaining APOE ε4 status can further improve prediction.

PMID:
26537709
PMCID:
PMC4634913
DOI:
10.1186/s13195-015-0152-z
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for BioMed Central Icon for PubMed Central
Loading ...
Support Center