A published predictor model in a single-site cohort study (questionable dementia, QD) that contained episodic verbal memory (SRT total recall), informant report of function (FAQ), and MRI measures was tested using logistic regression and ROC analyses with comparable measures in a second multisite cohort study (Alzheimer’s Disease Neuroimaging Initiative, ADNI). There were 126 patients in QD and 282 patients in ADNI with MCI followed for 3 years. Within each sample, the differences in AUCs between the statistical models were very similar. Adding hippocampal and entorhinal cortex volumes to the model containing AVLT/SRT, FAQ, age and MMSE increased the area under the curve (AUC) in ADNI but not QD, with sensitivity increasing by 2% in ADNI and 2% in QD for a fixed specificity of 80%. Conversely, adding episodic verbal memory (SRT/AVLT) and FAQ to the model containing age, Mini Mental State Exam (MMSE), hippocampal and entorhinal cortex volumes increased the AUC in ADNI and QD, with sensitivity increasing by 17% in ADNI and 10% in QD for 80% specificity. The predictor models showed similar differences from each other in both studies, supporting independent validation. MRI hippocampal and entorhinal cortex volumes showed limited added predictive utility to memory and function measures. 1. Introduction Mild cognitive impairment (MCI) often represents a transitional state between normal cognition and Alzheimer’s disease (AD) [1, 2]. Accurate prediction of transition from MCI to AD aids in prognosis and targeting early treatment [3]. Episodic verbal memory impairment and informant report of functional deficits in complex social and cognitive tasks are features of incipient AD, and impairment in these domains is associated with transition from MCI to AD [4, 5]. Most biomarkers of MCI transition to AD are related to the underlying disease pathology of amyloid plaques and neurofibrillary tangles [6]. Hippocampal and entorhinal cortex atrophy on MRI scan of brain [7], parietotemporal hypometabolism on 18FDG PET [8], increased amyloid uptake using PET [9], and decreased amyloid beta-42 (Aβ42) with increased tau/phospho-tau levels in the cerebrospinal fluid (CSF) [10, 11] each significantly predict transition from MCI to AD. The apolipoprotein E ε4 allele increases AD risk, but is not a strong biomarker of transition from MCI to AD [3]. In a meta-analysis, memory deficits appeared to be superior to MRI hippocampal atrophy in predicting transition to AD [12], but studies in the meta-analysis had highly variable subject inclusion/exclusion criteria and assessment
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