Methods to improve the detection of mild cognitive impairment

We examined whether the performance of the National Institute of Aging's Consortium to Establish a Registry for Alzheimer's Disease's 10-word list (CWL), part of the consortium's neuropsychological battery, can be improved for detecting Alzheimer's disease and related disorders early. We focused on mild cognitive impairment (MCI) and mild dementia because these stages often go undetected, and their detection is important for treatment. Using standardized diagnostic criteria combined with history, physical examination, and cognitive, laboratory, and neuroimaging studies, we staged 471 community-dwelling subjects for dementia severity by using the Clinical Dementia Rating Scale. We then used correspondence analysis (CA) to derive a weighted score for each subject from their item responses over the three immediate- and one delayed-recall trials of the CWL. These CA-weighted scores were used with logistic regression to predict each subject's probability of impairment, and receiver operating characteristic analysis was used to measure accuracy. For MCI vs. normal, accuracy was 97% [confidence interval (C.I.) 97-98%], sensitivity was 94% (C.I. 93-95%), and specificity was 89% (C.I. 88-91%). For MCI/mild dementia vs. normal, accuracy was 98% (C.I. 98-99%), sensitivity was 96% (C.I. 95-97%), and specificity was 91% (C.I. 89-93%). MCI sensitivity was 12% higher (without lowering specificity) than that obtained with the delayed-recall total score (the standard method for CWL interpretation). Optimal positive and negative predictive values were 100% and at least 96.6%. These results show that CA-weighted scores can significantly improve early detection of Alzheimer's disease and related disorders.