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1.  Neuropsychological Test Performance and Cognitive Reserve in Healthy Aging and the Alzheimer’s Disease Spectrum: A Theoretically-Driven Factor Analysis 
Accurate measurement of cognitive function is critical for understanding the disease course of Alzheimer’s disease (AD). Detecting cognitive change over time can be confounded by level of premorbid intellectual function or cognitive reserve and lead to under or over diagnosis of cognitive impairment and AD. Statistical models of cognitive performance that include cognitive reserve can improve sensitivity to change and clinical efficacy. We used confirmatory factor analysis to test a four-factor model comprised of memory/language, processing speed/executive function, attention, and cognitive reserve factors in a group of cognitively healthy older adults and a group of participants along the spectrum of amnestic mild cognitive impairment to AD (aMCI-AD). The model showed excellent fit for the control group (χ2 = 100, df = 78, CFI = .962, RMSEA = .049) and adequate fit for the aMCI-AD group (χ2 = 1750, df = 78, CFI = .932, RMSEA = .085). Though strict invariance criteria were not met, invariance testing to determine if factor structures are similar across groups yielded acceptable absolute model fits and provide evidence in support of configural, metric, and scalar invariance. These results provide further support for the construct validity of cognitive reserve in healthy and memory impaired older adults.
PMCID: PMC3600814  PMID: 23039909
mild cognitive impairment; brain reserve; executive function; memory function; dementia; cognition
2.  A web-based normative calculator for the uniform data set (UDS) neuropsychological test battery 
With the recent publication of new criteria for the diagnosis of preclinical Alzheimer's disease (AD), there is a need for neuropsychological tools that take premorbid functioning into account in order to detect subtle cognitive decline. Using demographic adjustments is one method for increasing the sensitivity of commonly used measures. We sought to provide a useful online z-score calculator that yields estimates of percentile ranges and adjusts individual performance based on sex, age and/or education for each of the neuropsychological tests of the National Alzheimer's Coordinating Center Uniform Data Set (NACC, UDS). In addition, we aimed to provide an easily accessible method of creating norms for other clinical researchers for their own, unique data sets.
Data from 3,268 clinically cognitively-normal older UDS subjects from a cohort reported by Weintraub and colleagues (2009) were included. For all neuropsychological tests, z-scores were estimated by subtracting the raw score from the predicted mean and then dividing this difference score by the root mean squared error term (RMSE) for a given linear regression model.
For each neuropsychological test, an estimated z-score was calculated for any raw score based on five different models that adjust for the demographic predictors of SEX, AGE and EDUCATION, either concurrently, individually or without covariates. The interactive online calculator allows the entry of a raw score and provides five corresponding estimated z-scores based on predictions from each corresponding linear regression model. The calculator produces percentile ranks and graphical output.
An interactive, regression-based, normative score online calculator was created to serve as an additional resource for UDS clinical researchers, especially in guiding interpretation of individual performances that appear to fall in borderline realms and may be of particular utility for operationalizing subtle cognitive impairment present according to the newly proposed criteria for Stage 3 preclinical Alzheimer's disease.
PMCID: PMC3308021  PMID: 22078663
Alzheimer's disease; cognitive aging; MCI; memory; norms
3.  Long-term Course and Effectiveness of Combination Therapy in Alzheimer’s Disease 
To compare the real-world clinical effectiveness and long-term clinical trajectory in patients with Alzheimer’s disease (AD) treated with combination (COMBO) therapy consisting of cholinesterase-inhibitor (CI) plus memantine (MEM) versus CI alone versus no treatment with either.
382 subjects with Probable AD underwent serial clinical evaluations at a memory disorders unit. Cognition was assessed by the Information-Memory-Concentration subscale of the Blessed Dementia Scale (BDS) and function was assessed by the Weintraub Activities of Daily Living Scale (ADL) at six-month intervals. 144 subjects received standard care without CI or MEM (NO-RX), 122 received CI-monotherapy (CI), and 116 received combination therapy (COMBO) with CI plus MEM. Mean follow-up was 30 months (4.1 visits) and mean cumulative medication treatment time was 22.5 months. Rates of declines were analyzed using mixed-effects regression models, and Cohen’s d effect sizes were calculated annually for years 1–4.
Covarying for baseline scores, age, education and duration of illness, the COMBO group had significantly lower mean annualized rates of deterioration in BDS and ADL scores compared to the CI (p<0.001; Cohen’s dBDS=0.10–0.34 and dADL=0.23–0.46 at 1–2 years) and NO-RX groups (p<0.001; Cohen’s dBDS=0.56–0.73 and dADL=0.32–0.48 at 1–2 years). For the COMBO group, Cohen’s d effect sizes increased with treatment duration. Similar comparisons significantly favored the CI over the NO-RX group on the BDS.
Combination therapy slows cognitive and functional decline in AD compared to CI-monotherapy and no treatment. These benefits had small-to-medium effect sizes that increased with time on treatment and were sustained for years.
PMCID: PMC2718545  PMID: 18580597
treatment efficacy; modeling progression; cholinesterase inhibitor; memantine; memory; cognition and function in dementia

Results 1-3 (3)