A point-based tool to predict conversion from mild cognitive impairment to probable Alzheimer's disease.
BACKGROUND
Our objective in this study was to develop a point-based tool to predict conversion from amnestic mild cognitive impairment (MCI) to probable Alzheimer's disease (AD).


METHODS
Subjects were participants in the first part of the Alzheimer's Disease Neuroimaging Initiative. Cox proportional hazards models were used to identify factors associated with development of AD, and a point score was created from predictors in the final model.


RESULTS
The final point score could range from 0 to 9 (mean 4.8) and included: the Functional Assessment Questionnaire (2‒3 points); magnetic resonance imaging (MRI) middle temporal cortical thinning (1 point); MRI hippocampal subcortical volume (1 point); Alzheimer's Disease Cognitive Scale-cognitive subscale (2‒3 points); and the Clock Test (1 point). Prognostic accuracy was good (Harrell's c = 0.78; 95% CI 0.75, 0.81); 3-year conversion rates were 6% (0‒3 points), 53% (4‒6 points), and 91% (7‒9 points).


CONCLUSIONS
A point-based risk score combining functional dependence, cerebral MRI measures, and neuropsychological test scores provided good accuracy for prediction of conversion from amnestic MCI to AD.
Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA; Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA; San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA. Electronic address: deborah.barnes@ucsf.edu.
Deborah E
DE
Barnes
San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA; Division of Geriatrics, University of California, San Francisco, San Francisco, CA, USA.
Irena S
IS
Cenzer
Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA; Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA; San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
Kristine
K
Yaffe
San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA; Division of Geriatrics, University of California, San Francisco, San Francisco, CA, USA; The Jewish Home of San Francisco, San Francisco, CA, USA.
Christine S
CS
Ritchie
San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
Sei J
SJ
Lee
D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000235:genetics / Q000503:physiopathology*; D053327:Apolipoprotein E4 / Q000235:genetics; D001921:Brain / Q000473:pathology; D060825:Cognitive Dysfunction / Q000150:complications* / Q000235:genetics; D018450:Disease Progression; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D009483:Neuropsychological Tests; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D011569:Psychiatric Status Rating Scales; D015203:Reproducibility of Results; D011795:Surveys and Questionnaires
D053327:Apolipoprotein E4
Aged; Alzheimer's disease; Disease progression; Human; Magnetic resonance imaging; Mild cognitive impairment; Neuropsychological tests; Prognostic modeling; Risk factors