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1.  The Alzheimer’s Disease Centers’ Uniform Data Set (UDS): The Neuropsychological Test Battery 
The neuropsychological test battery from the Uniform Data Set (UDS) of the Alzheimer’s Disease Centers (ADC) program of the National Institute on Aging (NIA) consists of brief measures of attention, processing speed, executive function, episodic memory and language. This paper describes development of the battery and preliminary data from the initial UDS evaluation of 3,268 clinically cognitively normal men and women collected over the first 24 months of utilization. The subjects represent a sample of community-dwelling, individuals who volunteer for studies of cognitive aging. Subjects were considered “clinically cognitively normal” based on clinical assessment, including the Clinical Dementia Rating scale and the Functional Assessment Questionnaire. The results demonstrate performance on tests sensitive to cognitive aging and to the early stages of Alzheimer disease (AD) in a relatively well-educated sample. Regression models investigating the impact of age, education, and gender on test scores indicate that these variables will need to be incorporated in subsequent normative studies. Future plans include: 1) determining the psychometric properties of the battery; 2) establishing normative data, including norms for different ethnic minority groups; and 3) conducting longitudinal studies on cognitively normal subjects, individuals with mild cognitive impairment, and individuals with AD and other forms of dementia.
doi:10.1097/WAD.0b013e318191c7dd
PMCID: PMC2743984  PMID: 19474567
2.  Prediction of Driving Ability with Neuropsychological Tests: Demographic Adjustments Diminish Accuracy 
Demographically-adjusted norms are used to enhance accuracy of inferences based on neuropsychological assessment. However, we hypothesized that predictive accuracy regarding complex real-world activities is diminished by demographic corrections. Driving performance was assessed with a standardized on-road test in participants aged 65+ (24 healthy elderly, 26 Alzheimer’s disease, 33 Parkinson’s disease). Neuropsychological measures included Trailmaking A and B, Complex Figure, Benton Visual Retention, and Block Design tests. A multiple regression model with raw neuropsychological scores was significantly predictive of driving errors (R2 = .199, p <.005); a model with demographically-adjusted scores was not (R2 = .113, p >.10). Raw scores were more highly correlated than adjusted scores with each neuropsychological measure, and among both healthy elderly and Parkinson’s patients. Demographic corrections diminished predictive accuracy for driving performance, extending findings of Silverberg and Millis (2009) that competency in complex real-world activities depends on ability levels, regardless of demographic considerations.
doi:10.1017/S1355617710000470
PMCID: PMC3152745  PMID: 20441682
aged; age factors; automobile driving; geriatric assessment; Parkinson’s; Alzheimer disease
3.  A Novel Study Paradigm for Long-term Prevention Trials in Alzheimer Disease: The Placebo Group Simulation Approach (PGSA) 
INTRODUCTION
The PGSA (Placebo Group Simulation Approach) aims at avoiding problems of sample representativeness and ethical issues typical of placebo-controlled secondary prevention trials with MCI patients. The PGSA uses mathematical modeling to forecast the distribution of quantified outcomes of MCI patient groups based on their own baseline data established at the outset of clinical trials. These forecasted distributions are then compared with the distribution of actual outcomes observed on candidate treatments, thus substituting for a concomitant placebo group. Here we investigate whether a PGSA algorithm that was developed from the MCI population of ADNI 1*, can reliably simulate the distribution of composite neuropsychological outcomes from a larger, independently selected MCI subject sample.
METHODS
Data available from the National Alzheimer’s Coordinating Center (NACC) were used. We included 1523 patients with single or multiple domain amnestic mild cognitive impairment (aMCI) and at least two follow-ups after baseline. In order to strengthen the analysis and to verify whether there was a drift over time in the neuropsychological outcomes, the NACC subject sample was split into 3 subsamples of similar size. The previously described PGSA algorithm for the trajectory of a composite neuropsychological test battery (NTB) score was adapted to the test battery used in NACC. Nine demographic, clinical, biological and neuropsychological candidate predictors were included in a mixed model; this model and its error terms were used to simulate trajectories of the adapted NTB.
RESULTS
The distributions of empirically observed and simulated data after 1, 2 and 3 years were very similar, with some over-estimation of decline in all 3 subgroups. The by far most important predictor of the NTB trajectories is the baseline NTB score. Other significant predictors are the MMSE baseline score and the interactions of time with ApoE4 and FAQ (functional abilities). These are essentially the same predictors as determined for the original NTB score.
CONCLUSION
An algorithm comprising a small number of baseline variables, notably cognitive performance at baseline, forecasts the group trajectory of cognitive decline in subsequent years with high accuracy. The current analysis of 3 independent subgroups of aMCI patients from the NACC database supports the validity of the PGSA longitudinal algorithm for a NTB. Use of the PGSA in long-term secondary AD prevention trials deserves consideration.
PMCID: PMC4268776  PMID: 25530953
Placebo Group Simulation Approach (PGSA); clinical AD trials; phase 3 clinical trials; MCI; modelling AD trajectories; prodromal AD
4.  The Relationship between Perceived Cognitive Dysfunction and Objective Neuropsychological Performance in Persons with Rheumatoid Arthritis 
Arthritis care & research  2013;65(3):481-486.
OBJECTIVE
Research shows a gap between perceived cognitive dysfunction and objective neuropsychological performance in persons with chronic diseases. We explored this relationship in persons with rheumatoid arthritis (RA).
METHODS
Individuals from a longitudinal cohort study of RA participated in a study visit that included physical, psychosocial, and biological metrics. Subjective cognitive dysfunction was assessed using the Perceived Deficits Questionnaire (PDQ; 0–20, higher scores = greater perceived impairment). Objective cognitive impairment was assessed using a battery of 12 standardized neuropsychological measures yielding 16 indices. On each test, subjects were classified as ‘impaired’ if they performed 1 SD below age-based population norms. Total cognitive function scores were calculated by summing the transformed scores (0–16, higher scores = greater impairment). Multiple linear regression analyses determined the relationship of total cognitive function score with PDQ score, controlling for gender, race, marital status, income, education, disease duration, disease severity, depression, and fatigue.
RESULTS
120 subjects (mean ± SD age: 58.5 ± 11.0 years) were included. Mean ± SD scores of total cognitive function and PDQ were 2.5 ± 2.2 (0–10) and 5.8 ± 3.8 (0–16), respectively. In multivariate analysis, there was no significant relationship between total cognitive function score and PDQ score. However, depression and fatigue (β = 0.31, p < 0.001; β = 0.31, p = 0.001) were significantly associated with PDQ score.
CONCLUSION
The findings emphasize the gap between subjective and objective measures of cognitive impairment and the importance of considering psychological factors within the context of cognitive complaints in clinical settings.
doi:10.1002/acr.21814
PMCID: PMC3786333  PMID: 22899659
5.  Age and education effects and norms on a cognitive test battery from a population-based cohort: The Monongahela –Youghiogheny Healthy Aging Team (MYHAT) 
Aging & mental health  2010;14(1):100-107.
Objectives
Performance on cognitive tests can be affected by age, education, and also selection bias. We examined the distribution of scores on a several cognitive screening tests by age and educational levels in a population-based cohort.
Method
An age-stratified random sample of individuals aged 65+ years was drawn from the electoral rolls of an urban U.S. community. Those obtaining age and education-corrected scores ≥ 21/30 on the Mini-Mental State Examination were designated as cognitively normal or only mildly impaired, and underwent a full assessment including a battery of neuropsychological tests. Participants were also rated on the Clinical Dementia Rating scale. The distribution of neuropsychological test scores within demographic strata, among those receiving a CDR of 0 (no dementia), are reported here as cognitive test norms. After combining individual test scores into cognitive domain composite scores, multiple linear regression models were used to examine associations of cognitive test performance with age, and education.
Results
In this cognitively normal sample of older adults, younger age and higher education were associated with better performance in all cognitive domains. Age and education together explained 22% of the variation of memory, and less of executive function, language, attention, and visuospatial function.
Conclusion
Older age and lesser education are differentially associated with worse neuropsychological test performance in cognitively normal older adults representative of the community at large. The distribution of scores in these participants can serve as population-based norms for these tests, and be especially useful to clinicians and researchers assessing older adults outside specialty clinic settings.
doi:10.1080/13607860903071014
PMCID: PMC2828360  PMID: 20155526
Neuropsychological tests; epidemiology; normative; community
6.  Relationship of ethnicity, age, education, and reading level to speed and executive function among HIV+ and HIV- women: The WIHS Neurocognitive Substudy 
Use of neuropsychological tests to identify HIV-associated neurocognitive dysfunction must involve normative standards that are well-suited to the population of interest. Norms should be based on a population of HIV-uninfected individuals as closely matched to the HIV-infected group as possible, and must include examination of the potential effects of demographic factors on test performance. This is the first study to determine the normal range of scores on measures of psychomotor speed and executive function among a large group of ethnically and educationally diverse HIV-uninfected, high risk women, as well as their HIV-infected counterparts. Participants (n = 1653) were administered the Trailmaking Test Parts A and B (Trails A and Trails B), the Symbol Digit Modalities Test (SDMT), and the Wide Range Achievement Test-3 (WRAT-3). Among HIV-uninfected women, race/ethnicity accounted for almost 5% of the variance in cognitive test performance. The proportion of variance in cognitive test performance accounted for by age (13.8%), years of school (4.1%) and WRAT-3 score (11.5%) were each significant, but did not completely account for the effect of race (3%). HIV-infected women obtained lower scores than HIV-uninfected women on time to complete Trails A and B, SDMT total correct, and SDMT incidental recall score, but after adjustment for age, years of education, racial/ethnic classification, and reading level, only the difference on SDMT total correct remained significant. Results highlight the need to adjust for demographic variables when diagnosing cognitive impairment in HIV-infected women. Advantages of demographically adjusted regression equations developed using data from HIV-uninfected women are discussed.
doi:10.1080/13803395.2010.547662
PMCID: PMC3383771  PMID: 21950512
7.  Distinguishing Neurocognitive Functions in Schizophrenia Using Partially Ordered Classification Models 
Schizophrenia Bulletin  2006;32(4):679-691.
Current methods for statistical analysis of neuropsychological test data in schizophrenia are inherently insufficient for revealing valid cognitive impairment profiles. While neuropsychological tests aim to selectively sample discrete cognitive domains, test performance often requires several cognitive operations or “attributes.” Conventional statistical approaches assign each neuropsychological score of interest to a single attribute or “domain” (e.g., attention, executive, etc.), and scores are calculated for each. This can yield misleading information about underlying cognitive impairments. We report findings applying a new method for examining neuropsychological test data in schizophrenia, based on finite partially ordered sets (posets) as classification models.
A total of 220 schizophrenia outpatients were administered the Positive and Negative Symptom Scale (PANSS) and a neuropsychological test battery. Selected tests were submitted to cognitive attribute analysis a priori by two neuropsychologists. Applying Bayesian classification methods (posets), each patient was classified with respect to proficiency on the underlying attributes, based upon his or her individual test performance pattern.
Twelve cognitive “classes” are described in the sample. Resulting classification models provided detailed “diagnoses” into “attribute-based” profiles of cognitive strength/weakness, mimicking expert clinician judgment. Classification was efficient, requiring few measures to achieve accurate classification. Attributes were associated with PANSS factors in the expected manner (only the negative and cognition factors were associated with the attributes), and a double dissociation was observed in which divergent thinking was selectively associated with negative symptoms, possibly reflecting a manifestation of Kraepelin's hypothesis regarding the impact of volitional disturbances on thought.
Using posets for extracting more precise cognitive information from neuropsychological data may reveal more valid cognitive endophenotypes, while dramatically reducing the amount of testing required.
doi:10.1093/schbul/sbj038
PMCID: PMC2632274  PMID: 16424379
schizophrenia; neurocognitive deficits; neuropsychological test domains; neuropsychological test data reduction; clustering techniques; Bayesian methods
8.  Age, gender, and education norms on the CERAD neuropsychological battery in the oldest old 
Neurology  2006;67(6):1006-1010.
Objective
To evaluate the performance of nondemented subjects 85 years and older on the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) neuropsychological battery, and to assess its relationship with sociodemographic variables.
Methods
We studied 196 subjects enrolled in an Alzheimer’s Disease Research Center study who had a complete CERAD neuropsychological assessment. We used multiple regression analysis to predict performance on the neuropsychological tests from age, education, and sex. Eight representative hypothetical individuals were created (for example, an 87-year-old man, with high education). For each test, estimates of performance at the 10th, 25th, 50th, and 75th percentiles were reported for the eight representative hypothetical individuals.
Results
Mean age was 89.2 years (SD = 3.2), mean years of education was 14.9 (SD = 3.2), and 66% of the sample were women. For 11 of the 14 neuropsychological tests, there was a significant multiple regression model using education, age, and sex as predictors. Neither the models nor the predictors used individually were significant for Delayed Recall, Savings, or correct Recognition. Among the significant results, seven had education as the strongest predictor. Lower age and higher education were associated with better performance. Women performed better than men in three of four tests with significant results for sex.
Conclusions
In a sample of oldest old whose primary language is English, neuropsychological testing is influenced mainly by education and age. Cutoff scores based on younger populations and applied to the oldest old might lead to increased false-positive misclassifications.
doi:10.1212/01.wnl.0000237548.15734.cd
PMCID: PMC3163090  PMID: 17000969
9.  Cognition in Non-Demented Diabetic Older Adults 
Current aging science  2012;5(2):131-135.
Evidence links diabetes mellitus to cognitive impairment and increased risk of Alzheimer's disease (AD) and suggests that insulin therapy improves cognition. With an increasing percentage of the US elderly population at high risk for diabetes and AD, the evidence of an association between diabetes and poor cognition in non-demented elderly may have implications for diagnosis, prevention and treatment of cognitive decline including AD.
In our study, we hypothesized that diabetic elders with normal cognition would demonstrate poorer cognitive outcomes than non-diabetic elders and that diabetic elders receiving diabetes treatment would demonstrate better outcomes than those not receiving treatment.
Data were evaluated from the National Alzheimer's Coordinating Center's Uniform Data Set (UDS). The UDS consists of clinical and neuropsychological assessments of a sample of elderly research subjects recruited from thirty-one Alzheimer's Disease Centers nationwide. The UDS provides a unique opportunity to study cognition in a nationally recruited sample with structured neuropsychological tests.
We examined the impact of diabetes and diabetes treatment on cognitive measures in 3421 elderly research subjects from 2005-2007 with normal cognition. We performed linear regression analyses to compare cognitive scores between diabetic subjects and non-diabetic subjects. Diabetic subjects had lower scores than non-diabetic subjects including attention, psychomotor function and executive function, but no differences in memory or semantic memory language. There was no association between diabetes treatment and cognitive scores.
These subtle but significant cognitive deficits in diabetic subjects compared to non-diabetic subjects may contribute to difficulty with compliance with complex diabetes medication regimens. A specific role of diabetes as a risk for cognitive impairment will require longitudinal study.
PMCID: PMC3659164  PMID: 22023096
Diabetes; Cognition; Alzheimer's; Elderly
10.  Normative data and validation of a regression based summary score for assessing meaningful neuropsychological change 
Reliable detection and quantification of longitudinal cognitive change are of considerable importance in many neurological disorders, particularly to monitor central nervous system effects of disease progression and treatment. In the current study, we developed normative data for repeated neuropsychological (NP) assessments (6 testings) using a modified Standard Regression-Based (SRB) approach in a sample that includes both HIV-uninfected (HIV−, N=172) and neuromedically stable HIV-infected (HIV+, N=124) individuals. Prior analyzes indicated no differences in NP change between the infected and uninfected participants. The norms for change included correction for factors found to significantly affect follow-up performance, using hierarchical regression. The most robust and consistent predictors of follow-up performance were the prior performance on the same test (which contributed in all models) and a measure of prior overall NP competence (predictor in 97% of all models). Demographic variables were predictors in 10%-46% of all models and in small amounts; while test retest interval contributed in only 6% of all models. Based on the regression equations, standardized change scores (z-scores) were computed for each test measure at each interval; these z scores were then averaged to create a total battery change score. An independent sample of HIV− participants who had completed 8 of the 15 tests was used to validate an abridged summary change score. The normative data are available in an electronic format by email request to the first author. Correction for practice effects based on normative data improved the consistency of NP impairment classification in a clinically stable longitudinal cohort after baseline.
doi:10.1080/13803395.2010.535504
PMCID: PMC3151558  PMID: 21391011
Normative data; longitudinal studies; regression; regression change score; SRB; practice effect
11.  Fetal Growth and Risk of Stillbirth: A Population-Based Case–Control Study 
PLoS Medicine  2014;11(4):e1001633.
Radek Bukowski and colleagues conducted a case control study in 59 US hospitals to determine the relationship between fetal growth and stillbirth, and find that both restrictive and excessive growth could play a role.
Please see later in the article for the Editors' Summary
Background
Stillbirth is strongly related to impaired fetal growth. However, the relationship between fetal growth and stillbirth is difficult to determine because of uncertainty in the timing of death and confounding characteristics affecting normal fetal growth.
Methods and Findings
We conducted a population-based case–control study of all stillbirths and a representative sample of live births in 59 hospitals in five geographic areas in the US. Fetal growth abnormalities were categorized as small for gestational age (SGA) (<10th percentile) or large for gestational age (LGA) (>90th percentile) at death (stillbirth) or delivery (live birth) using population, ultrasound, and individualized norms. Gestational age at death was determined using an algorithm that considered the time-of-death interval, postmortem examination, and reliability of the gestational age estimate. Data were weighted to account for the sampling design and differential participation rates in various subgroups. Among 527 singleton stillbirths and 1,821 singleton live births studied, stillbirth was associated with SGA based on population, ultrasound, and individualized norms (odds ratio [OR] [95% CI]: 3.0 [2.2 to 4.0]; 4.7 [3.7 to 5.9]; 4.6 [3.6 to 5.9], respectively). LGA was also associated with increased risk of stillbirth using ultrasound and individualized norms (OR [95% CI]: 3.5 [2.4 to 5.0]; 2.3 [1.7 to 3.1], respectively), but not population norms (OR [95% CI]: 0.6 [0.4 to 1.0]). The associations were stronger with more severe SGA and LGA (<5th and >95th percentile). Analyses adjusted for stillbirth risk factors, subset analyses excluding potential confounders, and analyses in preterm and term pregnancies showed similar patterns of association. In this study 70% of cases and 63% of controls agreed to participate. Analysis weights accounted for differences between consenting and non-consenting women. Some of the characteristics used for individualized fetal growth estimates were missing and were replaced with reference values. However, a sensitivity analysis using individualized norms based on the subset of stillbirths and live births with non-missing variables showed similar findings.
Conclusions
Stillbirth is associated with both growth restriction and excessive fetal growth. These findings suggest that, contrary to current practices and recommendations, stillbirth prevention strategies should focus on both severe SGA and severe LGA pregnancies.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Pregnancy is usually a happy time, when the parents-to-be anticipate the arrival of a new baby. But, sadly, about 20% of pregnancies end in miscarriage—the early loss of a fetus (developing baby) that is unable to survive independently. Other pregnancies end in stillbirth—fetal death after 20 weeks of pregnancy (in the US; after 24 weeks in the UK). Stillbirths, like miscarriages, are common. In the US, for example, one in every 160 pregnancies ends in stillbirth. How women discover that their unborn baby has died varies. Some women simply know something is wrong and go to hospital to have their fears confirmed. Others find out when a routine check-up detects no fetal heartbeat. Most women give birth naturally after their baby has died, but if the mother's health is at risk, labor may be induced. Common causes of stillbirth include birth defects and infections. Risk factors for stillbirth include being overweight and smoking during pregnancy.
Why Was This Study Done?
Stillbirths are often associated with having a “small for gestational age” (SGA) fetus. Gestation is the period during which a baby develops in its mother's womb. Gestational age is estimated from the date of the woman's last menstrual period and/or from ultrasound scans. An SGA fetus is lighter than expected for its age based on observed distributions (norms) of fetal weights for gestational age. Although stillbirth is clearly associated with impaired fetal growth, the exact relationship between fetal growth and stillbirth remains unclear for two reasons. First, studies investigating this relationship have used gestational age at delivery rather than gestational age at death as an estimate of fetal age, which overestimates the gestational age of stillbirths and leads to errors in estimates of the proportions of SGA and “large for gestational age” (LGA) stillbirths. Second, many characteristics that affect normal fetal growth are also associated with the risk of stillbirth, and this has not been allowed for in previous studies. In this population-based case–control study, the researchers investigate the fetal growth abnormalities associated with stillbirth using a new approach to estimate gestational age and accounting for the effect of characteristics that affect both fetal growth and stillbirth. A population-based case–control study compares the characteristics of patients with a condition in a population with those of unaffected people in the same population.
What Did the Researchers Do and Find?
The researchers investigated all the stillbirths and a sample of live births that occurred over 2.5 years at 59 hospitals in five US regions. They used a formula developed by the Stillbirth Collaborative Research Network to calculate the gestational age at death of the stillbirths. They categorized fetuses as SGA if they had a weight for gestational age within the bottom 10% (below the 10th percentile) of the population and as LGA if they had a weight for gestational age above the 90th percentile at death (stillbirth) or delivery (live birth) using population, ultrasound, and individualized norms of fetal weight for gestational age. Population norms incorporate weights for gestational age from normal pregnancies and from pregnancies complicated by growth abnormalities, whereas the other two norms include weights for gestational age from normal pregnancies only. Having an SGA fetus was associated with a 3- to 4-fold increased risk of stillbirth compared to having a fetus with “appropriate” weight for gestational age based on all three norms. LGA was associated with an increased risk of stillbirth based on the ultrasound and individualized norms but not the population norms. Being more severely SGA or LGA (below the 5th percentile or above the 95th percentile) was associated with an increased risk of stillbirth.
What Do These Findings Mean?
These findings indicate that, when the time of death is accounted for and norms for weight for gestational age only from uncomplicated pregnancies are used, stillbirth is associated with both restricted and excessive fetal growth. Overall, abnormal fetal growth was identified in 25% of stillbirths using population norms and in about 50% of stillbirths using ultrasound or individualized norms. Although the accuracy of these findings is likely to be affected by aspects of the study design, these findings suggest that, contrary to current practices, strategies designed to prevent stillbirth should focus on identifying both severely SGA and severely LGA fetuses and should use norms for the calculation of weight for gestational age based on normal pregnancies only. Such an approach has the potential to identify almost half of the pregnancies likely to result in stillbirth.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001633.
The March of Dimes, a nonprofit organization for pregnancy and baby health, provides information on stillbirth
Tommy's, a UK nonprofit organization that funds research into stillbirth, premature birth, and miscarriage and provides information for parents-to-be, also provides information on stillbirth (including personal stories)
The UK National Health Service Choices website provides information about stillbirth (including a video about dealing with grief after a stillbirth)
MedlinePlus provides links to other resources about stillbirth (in English and Spanish)
Information about the Stillbirth Collaborative Research Network is available
doi:10.1371/journal.pmed.1001633
PMCID: PMC3995658  PMID: 24755550
12.  Normative Performance on the CLOX Task in a Multi-Ethnic Bilingual Cohort: A Project FRONTIER Study 
The CLOX test is a neuropsychological measure intended to aid in the assessment and detection of dementia in elderly populations. Few studies have provided normative data for this measure, with even less research available regarding the impact of socio-demographic factors on test scores. This study presents normative data for the CLOX in a sample of English- and Spanish-speaking Hispanic and non-Hispanic Whites. The total sample included 445 cognitively healthy older adults seen as part of an ongoing study of rural cognitive aging, Project FRONTIER. Unlike previous studies, criteria for “normality” (i.e., unimpaired) for CLOX1 and CLOX2 were based not merely on global impairment, but also on domain-specific impairment of executive functioning on the EXIT25 and/or Trail Making Test B (Trails B), or visuospatial/constructional impairment on the Line Orientation and Figure Copy subtests of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), respectively. Hierarchical regression analyses revealed that CLOX1 scores require adjustment by Age across ethnicities, while Education and Gender are necessary stratification markers for CLOX1 performance only in non-Hispanic Whites. None of the demographic variables were valid predictors of CLOX2 performance, negating the need for such adjustments. In addition to being the first study to provide separate normative data for CLOX performance in Hispanic and non-Hispanic White samples, the current study offers a novel approach to defining “normal” by cognitive domain. We also highlight the need to directly examine the impact of socio-demographic factors before applying normative corrections based on factors that have negligible impact on test scores.
doi:10.1002/gps.2810
PMCID: PMC4142441  PMID: 22052628
Executive functioning; visuospatial skills; norms; geriatrics; cognition
13.  Normative Data for Neuropsychological Tests in a Rural Elderly Chinese Cohort 
The Clinical Neuropsychologist  2012;26(4):641-653.
Normative information is important for appropriate interpretation of cognitive test scores as a critical component of dementia diagnosis in the elderly population. A cross-sectional evaluation of 1826 participants aged 65 years and older from four rural counties in China was conducted using six cognitive instruments including tests of global cognitive function (the Community Screening Instrument for Dementia), Memory (Word List Learning and Recall tasks from the Consortium to Establish a Registry for Alzheimer’s Disease, IU Story), Language (Animal Fluency Test), and executive function (IU Token). Multiple regression models adjusting for demographic variables were used to provide standardized residuals z-scores and corresponding percentile ranking for each cognitive test. In all cognitive tests, older age was associated with worse test performance while exposure to education was related to better cognitive test performance. We also detected a significant gender difference with men scoring better than women and a significant gender by education interaction on two tests. The interaction indicates that gender difference in test scores was much smaller in participants with more education than those who had less or no education. These demographically adjusted, regression-based norms can be a useful tool to clinicians involved with differential diagnosis of cognitive and memory disorders in older adults in rural China.
doi:10.1080/13854046.2012.666266
PMCID: PMC3349802  PMID: 22439633
Normative Study; Neuropsychological Test; Age; Gender; Education; Regression- Based Norms
14.  The Alzheimer’s Prevention Initiative composite cognitive test score: Sample size estimates for the evaluation of preclinical Alzheimer’s disease treatments in presenilin 1 E280A mutation carriers 
Objective
There is a need to identify a cognitive composite that is sensitive to tracking preclinical AD decline to be used as a primary endpoint in treatment trials.
Method
We capitalized on longitudinal data, collected from 1995 to 2010, from cognitively unimpaired presenilin 1 (PSEN1) E280A mutation carriers from the world’s largest known early-onset autosomal dominant AD (ADAD) kindred to identify a composite cognitive test with the greatest statistical power to track preclinical AD decline and estimate the number of carriers age 30 and older needed to detect a treatment effect in the Alzheimer’s Prevention Initiative’s (API) preclinical AD treatment trial. The mean-to-standard-deviation ratios (MSDRs) of change over time were calculated in a search for the optimal combination of one to seven cognitive tests/sub-tests drawn from the neuropsychological test battery in cognitively unimpaired mutation carriers during a two and five year follow-up period, using data from non-carriers during the same time period to correct for aging and practice effects. Combinations that performed well were then evaluated for robustness across follow-up years, occurrence of selected items within top performing combinations and representation of relevant cognitive domains.
Results
This optimal test combination included CERAD Word List Recall, CERAD Boston Naming Test (high frequency items), MMSE Orientation to Time, CERAD Constructional Praxis and Ravens Progressive Matrices (Set A) with an MSDR of 1.62. This composite is more sensitive than using either the CERAD Word List Recall (MSDR=0.38) or the entire CERAD-Col battery (MSDR=0.76). A sample size of 75 cognitively normal PSEN1-E280A mutation carriers age 30 and older per treatment arm allows for a detectable treatment effect of 29% in a 60-month trial (80% power, p=0.05).
Conclusions
We have identified a composite cognitive test score representing multiple cognitive domains that has improved power compared to the most sensitive single test item to track preclinical AD decline in ADAD mutation carriers and evaluate preclinical AD treatments. This API composite cognitive test score will be used as the primary endpoint in the first API trial in cognitively unimpaired ADAD carriers within 15 years of their estimated age at clinical onset. We have independently confirmed our findings in a separate cohort of cognitively healthy older adults who progressed to the clinical stages of late-onset AD, described in a separate report, and continue to refine the composite in independent cohorts and compared with other analytical approaches.
doi:10.4088/JCP.13m08927
PMCID: PMC4331113  PMID: 24816373
composite cognitive score; API; Alzheimer’s Prevention Initiative; E280A; PSEN1; presenilin1; sample size; preclinical; cognitively unimpaired; autosomal dominant; ADAD
15.  Dynamics of cognitive change in impaired HIV-positive patients initiating antiretroviral therapy 
Neurology  2009;73(5):342-348.
Objective:
To rigorously evaluate the time course of cognitive change in a cohort of individuals with HIV-associated neurocognitive disorders (HAND) initiating combination antiretroviral therapy (CART), and to investigate which demographic, laboratory, and treatment factors are associated with neuropsychological (NP) outcome (or “any NP improvement”).
Methods:
Study participants included 37 HIV+ individuals with mild to moderate NP impairment who initiated CART and underwent NP testing at 12, 24, 36, and 48 weeks thereafter. NP change was assessed using a regression-based change score that was normed on a separate NP-stable group thereby controlling for regression toward the mean and practice effect. Mixed-effect regression models adjusting for loss to follow-up were used to evaluate the time course of cognitive change and its association with baseline and time-varying predictors.
Results:
In persons with HAND initiating CART, cognitive improvement happens soon after initiation (13% at week 12), but more often 24, 36, and up to 48 weeks after initiation (up to 41%), with fewer than 5% demonstrating significant worsening. In multivariate analyses, unique predictors of NP improvement included more severe baseline NP impairment and higher CART CNS penetration index. Greater viral load decrease was associated with NP improvement only in univariate analyses.
Conclusion:
Clinically meaningful neuropsychological improvement seemed to peak around 24–36 weeks after combination antiretroviral therapy initiation and was prolonged over the 1-year study period. This study also provides new evidence that benefit may be maximized by choosing antiretroviral medications that reach therapeutic concentrations in the CNS.
GLOSSARY
= asymptomatic neurocognitive impairment;
= combination antiretroviral therapy;
= confidence interval;
= Cognitive Intervention Trial;
= CNS penetration effectiveness;
= Global Deficit Score;
= interquartile range;
= HIV-associated dementia;
= HIV-associated neurocognitive disorders;
= mild neurocognitive disorder;
= mean scaled score regression-based change score;
= neuropsychological.
doi:10.1212/WNL.0b013e3181ab2b3b
PMCID: PMC2725933  PMID: 19474412
16.  Education and rates of cognitive decline in incident Alzheimer's disease 
Background
Some (but not all) epidemiological studies have noted faster rates of progression in high education patients with Alzheimer's disease (AD), which has been attributed to harbouring/tolerating a higher pathological burden at the time of clinical dementia for subjects with higher education. We wanted to assess the relationship between education and rates of decline in AD.
Methods
During the course of a community based multiethnic prospective cohort study of individuals aged ⩾65 years living in New York, 312 patients were diagnosed with incident AD and were followed overall for 5.6 (up to 13.3) years. The subjects received an average of 3.7 (up to 9) neuropsychological assessments consisting of 12 individual tests. With the aid of a normative sample, a standardised composite cognitive score as well as individual cognitive domain scores were calculated. Generalised estimating equation models were used to examine the association between education and rates of cognitive decline.
Results
Composite cognitive performance declined by 9% of a standard deviation per year. Rates of decline before and after AD incidence were similar. For each additional year of education there was 0.3% standard deviation lower composite cognitive performance for each year of follow up. The association between higher education and faster decline was noted primarily in the executive speed (0.6%) and memory (0.5%) cognitive domains and was present over and above age, gender, ethnicity, differential baseline cognitive performance, depression, and vascular comorbidity.
Conclusions
We conclude that higher education AD patients experience faster cognitive decline.
doi:10.1136/jnnp.2005.072306
PMCID: PMC2077720  PMID: 16484637
Alzheimer's disease; cognitive decline; cognitive reserve; education; incidence
17.  A solution to limitations of cognitive testing in children with intellectual disabilities: the case of fragile X syndrome 
Intelligence testing in children with intellectual disabilities (ID) has significant limitations. The normative samples of widely used intelligence tests, such as the Wechsler Intelligence Scales, rarely include an adequate number of subjects with ID needed to provide sensitive measurement in the very low ability range, and they are highly subject to floor effects. The IQ measurement problems in these children prevent characterization of strengths and weaknesses, poorer estimates of cognitive abilities in research applications, and in clinical settings, limited utility for assessment, prognosis estimation, and planning intervention. Here, we examined the sensitivity of the Wechsler Intelligence Scale for Children (WISC-III) in a large sample of children with fragile X syndrome (FXS), the most common cause of inherited ID. The WISC-III was administered to 217 children with FXS (age 6–17 years, 83 girls and 134 boys). Using raw norms data obtained with permission from the Psychological Corporation, we calculated normalized scores representing each participant’s actual deviation from the standardization sample using a z-score transformation. To validate this approach, we compared correlations between the new normalized scores versus the usual standard scores with a measure of adaptive behavior (Vineland Adaptive Behavior Scales) and with a genetic measure specific to FXS (FMR1 protein or FMRP). The distribution of WISC-III standard scores showed significant skewing with floor effects in a high proportion of participants, especially males (64.9%–94.0% across subtests). With the z-score normalization, the flooring problems were eliminated and scores were normally distributed. Furthermore, we found correlations between cognitive performance and adaptive behavior, and between cognition and FMRP that were very much improved when using these normalized scores in contrast to the usual standardized scores. The results of this study show that meaningful variation in intellectual ability in children with FXS, and probably other populations of children with neurodevelopmental disorders, is obscured by the usual translation of raw scores into standardized scores. A method of raw score transformation may improve the characterization of cognitive functioning in ID populations, especially for research applications.
doi:10.1007/s11689-008-9001-8
PMCID: PMC2768415  PMID: 19865612
FMR1 gene; IQ; Mental retardation; Assessment; FMRP
18.  A solution to limitations of cognitive testing in children with intellectual disabilities: the case of fragile X syndrome 
Intelligence testing in children with intellectual disabilities (ID) has significant limitations. The normative samples of widely used intelligence tests, such as the Wechsler Intelligence Scales, rarely include an adequate number of subjects with ID needed to provide sensitive measurement in the very low ability range, and they are highly subject to floor effects. The IQ measurement problems in these children prevent characterization of strengths and weaknesses, poorer estimates of cognitive abilities in research applications, and in clinical settings, limited utility for assessment, prognosis estimation, and planning intervention. Here, we examined the sensitivity of the Wechsler Intelligence Scale for Children (WISC-III) in a large sample of children with fragile X syndrome (FXS), the most common cause of inherited ID. The WISC-III was administered to 217 children with FXS (age 6–17 years, 83 girls and 134 boys). Using raw norms data obtained with permission from the Psychological Corporation, we calculated normalized scores representing each participant’s actual deviation from the standardization sample using a z-score transformation. To validate this approach, we compared correlations between the new normalized scores versus the usual standard scores with a measure of adaptive behavior (Vineland Adaptive Behavior Scales) and with a genetic measure specific to FXS (FMR1 protein or FMRP). The distribution of WISC-III standard scores showed significant skewing with floor effects in a high proportion of participants, especially males (64.9%–94.0% across subtests). With the z-score normalization, the flooring problems were eliminated and scores were normally distributed. Furthermore, we found correlations between cognitive performance and adaptive behavior, and between cognition and FMRP that were very much improved when using these normalized scores in contrast to the usual standardized scores. The results of this study show that meaningful variation in intellectual ability in children with FXS, and probably other populations of children with neurodevelopmental disorders, is obscured by the usual translation of raw scores into standardized scores. A method of raw score transformation may improve the characterization of cognitive functioning in ID populations, especially for research applications.
doi:10.1007/s11689-008-9001-8
PMCID: PMC2768415  PMID: 19865612
FMR1 gene; IQ; Mental retardation; Assessment; FMRP
19.  Abbreviated neuropsychological assessment in schizophrenia 
The aim of this study was to identify the best subset of neuropsychological tests for prediction of several different aspects of functioning in a large (n = 236) sample of older people with schizophrenia. While the validity of abbreviated assessment methods has been examined before, there has never been a comparative study of the prediction of different elements of cognitive impairment, real-world outcomes, and performance-based measures of functional capacity. Scores on 10 different tests from a neuropsychological assessment battery were used to predict global neuropsychological (NP) performance (indexed with averaged scores or calculated general deficit scores), performance-based indices of everyday-living skills and social competence, and case-manager ratings of real-world functioning. Forward entry stepwise regression analyses were used to identify the best predictors for each of the outcomes measures. Then, the analyses were adjusted for estimated premorbid IQ, which reduced the magnitude, but not the structure, of the correlations. Substantial amounts (over 70%) of the variance in overall NP performance were accounted for by a limited number of NP tests. Considerable variance in measures of functional capacity was also accounted for by a limited number of tests. Different tests constituted the best predictor set for each outcome measure. A substantial proportion of the variance in several different NP and functional outcomes can be accounted for by a small number of NP tests that can be completed in a few minutes, although there is considerable unexplained variance. However, the abbreviated assessments that best predict different outcomes vary across outcomes. Future studies should determine whether responses to pharmacological and remediation treatments can be captured with brief assessments as well.
doi:10.1080/13803390802251386
PMCID: PMC2668735  PMID: 18720182
Schizophrenia; Disability; Neuropsychological assessment; Functional capacity; Abbreviated assessments
20.  For debate: substituting placebo controls in long-term Alzheimer's prevention trials 
Introduction
Novel compounds with potential to attenuate or stop the progression of Alzheimer's disease (AD) from its presymptomatic stage to dementia are being tested in man. The study design commonly used is the long-term randomized, placebo-controlled trial (RPCT), meaning that many patients will receive placebo for 18 months or longer. It is ethically problematic to expose presymptomatic AD patients, who by definition are at risk of developing dementia, to prolonged placebo treatment. As an alternative to long-term RPCTs we propose a novel clinical study design, termed the placebo group simulation approach (PGSA), using mathematical models to forecast outcomes of presymptomatic AD patients from their own baseline data. Forecasted outcomes are compared with outcomes observed on candidate drugs, thus replacing a concomitant placebo group.
Methods
First models were constructed using mild cognitive impairment (MCI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. One outcome is the Alzheimer Disease Assessment Scale - cognitive subscale (ADAScog) score after 24 months, predicted in a linear regression model; the other is the trajectory over 36 months of a composite neuropsychological test score (Neuro-Psychological Battery (NP-Batt)), using a mixed model. Demographics and clinical, biological and neuropsychological baseline values were tested as potential predictors in both models.
Results
ADAScog scores after 24 months are predicted from gender, obesity, Functional Assessment Questionnaire (FAQ) and baseline scores of Mini-Mental State Examination, ADAScog and NP-Batt with an R2 of 0.63 and a residual standard deviation of 0.67, allowing reasonably precise estimates of sample means. The model of the NP-Batt trajectory has random intercepts and slopes and fixed effects for body mass index, time, apolipoprotein E4, age, FAQ, baseline scores of ADAScog and NP-Batt, and four interaction terms. Estimates of the residual standard deviation range from 0.3 to 0.5 on a standard normal scale. If novel drug candidates are expected to diminish the negative slope of scores with time, a change of 0.04 per year could be detected in samples of 400 with a power of about 80%.
Conclusions
First PGSA models derived from ADNI MCI data allow prediction of cognitive endpoints and trajectories that correspond well with real observed values. Corroboration of these models with data from other observational studies is ongoing. It is suggested that the PGSA may complement RPCT designs in forthcoming long-term drug studies with presymptomatic AD individuals.
doi:10.1186/alzrt68
PMCID: PMC3226271  PMID: 21418632
21.  Exploration of 100 commonly used drugs and supplements on cognition in older adults 
Background
There are conflicting reports and a lack of evidence-based data regarding effects of medications on cognition in cognitively normal older adults. We explored whether use of 100 common medications taken by older adults is associated with longitudinal cognitive performance.
Methods
A longitudinal observational cohort was used with analysis of data collected September 2005 through May 2011 and maintained in the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set. Participants were aged 50 years or older and cognitively normal (N=4414). Composite scores were constructed from 10 psychometric tests. Scores for each participant reflecting change in the psychometric composite score from the baseline clinical assessment to the next assessment were calculated. General linear models were used to test whether the mean composite change score differed for participants who reported starting, stopping, continuing, or not taking each of the 100 most frequently-used medications in the NACC sample.
Results
The average time between assessments was 1.2 years (SD=0.42). Nine medications showed a difference (p<0.05) across the four participant groups in mean psychometric change scores from the first to the second assessment. Medications associated with improved psychometric performance were: naproxen, calcium-vitamin D, ferrous sulfate, potassium chloride, flax, and sertraline. Medications associated with declining psychometric performance were: bupropion, oxybutynin, and furosemide.
Conclusions
Reported use of common medications is associated with cognitive performance in older adults, but studies are needed to investigate the mechanisms underlying these effects.
doi:10.1016/j.jalz.2012.12.002
PMCID: PMC3823812  PMID: 23954027
cognition; medications; psychometric tests; National Alzheimer’s Coordinating Center
22.  Comparing measures of decline to dementia in amnestic MCI subjects in the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set 
International psychogeriatrics / IPA  2012;24(10):1553-1560.
Background
Many studies have investigated factors associated with the rate of decline and evolution from mild cognitive impairment to Alzheimer’s disease (AD) dementia in elderly patients. In this analysis we compared the rates of decline to dementia estimated from three common global measures of cognition: Mini Mental Status Examination (MMSE) score, Clinical Dementia Rating sum of boxes score (CDR-SB), and a neuropsychological tests composite score (CS).
Methods
A total of 2,899 subjects in the National Alzheimer’s Coordinating Center Uniform Data Set age 65+ years diagnosed with amnestic mild cognitive impairment (aMCI) were included in this analysis. Population-averaged decline to dementia rates were estimated and compared for standardized MMSE, CDR-SB, and Composite scores using Generalized Estimating Equations (GEE). Associations between rate of decline and several potential correlates of decline were also calculated and compared across measures.
Results
The CDR-SB had the steepest estimated slope, with a decline of .49 standard deviations (SD) per year, followed by the MMSE with .22 SD/year, and finally the CS with .07 SD/year. The rate of decline of the three measures differed significantly in a global test for differences (p<.0001). Age at visit, BMI at visit, APOE ε4 allele status, and race (black vs. white) had significantly different relationships with rate of decline in a global test for difference among the three measures.
Conclusions
These results suggest that both the rate of decline and the effects of AD risk factors on decline to dementia can vary depending on the evaluative measure used.
doi:10.1017/S1041610212000452
PMCID: PMC3614357  PMID: 22717299
neuropsychological testing; Alzheimer’s Disease; cognitive assessment; aging
23.  Athlete Characteristics and Outcome Scores for Computerized Neuropsychological Assessment: A Preliminary Analysis 
Journal of Athletic Training  2007;42(4):515-523.
Context: Computerized neuropsychological testing is used in athletics; however, normative data on an athletic population are lacking.
Objective: To investigate factors, such as sex, SAT score, alertness, and sport, and their effects on baseline neuropsychological test scores. A secondary purpose was to begin establishing preliminary reference data for nonsymptomatic collegiate athletes.
Design: Observational study.
Setting: Research laboratory.
Patients or Other Participants: The study population comprised 327 National Collegiate Athletic Association Division I athletes from 12 men's and women's sports.
Main Outcome Measure(s): Athletes were baseline tested before their first competitive season. Athletes completed demographics forms and self-reported history of concussion (1 or no concussion and 2 or more concussions) and SAT scores (<1000, 1000 to 1200, and >1200). The 108 women had a mean age of 18.39 ± 0.09 years, height of 167.94 ± 0.86 cm, and mass of 62.36 ± 1.07 kg. The 219 men had a mean age of 18.49 ± 0.07 years, height of 183.24 ± 1.68 cm, and mass of 88.05 ± 1.82 kg. Sports participation included women's soccer, lacrosse, basketball, and field hockey; men's football, soccer, lacrosse, and wrestling; and women's and men's track and cheerleading. We used the Automated Neuropsychological Assessment Metrics (Army Medical Research and Materiel Command, Ft Detrick, MD) and measured throughput scores (the number of correct responses per minute) as the dependent variable for each subtest, with higher scores reflecting increased speed and accuracy of responses. Subsets included 2 simple reaction time (SRT) tests, math processing (MTH), Sternberg memory search (ST6), matching to sample pairs (MSP), procedural reaction time (PRO), code digit substitution (CDS), and the Stanford sleep scale Likert-type score.
Results: Women scored better than men on the ST6 (P < .05), while men scored significantly better than women on the SRT and MSP tests. The highest-scoring SAT group performed better than other SAT groups on selected subtests (SRT, MTH, ST6, MSP, and CDS) (P < .05), and athletes tested during their season were more likely to score lower on the alertness scale (χ22[n = 322] = 11.32, P = .003). The lowest alertness group performed worse on the MSP and CDS subtests (P < .05). No differences were found between the group with a history of 1 or no concussion and the group with a history of 2 or more concussions (P > .05).
Conclusions: Performance on computerized neuropsychological tests may be affected by a number of factors, including sex, SAT scores, alertness at the time of testing, and the athlete's sport. To avoid making clinical misinterpretations, clinicians should acknowledge that individual baselines vary over time and should account for this variation.
PMCID: PMC2140078  PMID: 18174940
concussion; cognitive testing
24.  Interactive Effects of apoE4 Genotype and Cerebrovascular Risk on Neuropsychological Performance and Structural Brain Changes 
Objective
To determine if the presence of the apoE4 allele, a known risk factor for Alzheimer’s disease, interacts with cerebrovascular risk factors to produce a disproportionate impairment in neuropsychological performance and alterations in structural morphometry as measured by magnetic resonance imaging.
Methods
1,995 participants from the community based Framingham Offspring Cohort participants (mean age 61; 1,063 women) underwent neuropsychological testing and structural magnetic resonance imaging in 1999-2002.
Multivariate linear regression was used to estimate the relationships between Framingham Stroke Risk Profile scores, neuropsychological variables and magnetic resonance imaging measures; interaction terms were included to examine modification of these relationships by the presence of the apoE4 allele. All analyses were cross sectional.
Results
We found significant interactions between the presence of the apoE4 allele and the top sex-specific quartile of the Stroke Risk Profile and their effects on verbal memory (p=<0.001), verbal organization (p=<0.001), non-verbal memory (p=0.015), as well as set shifting and complex attention (p=0.005). Systolic blood pressure was the only individual risk factor significantly linked to these cognitive measures. With the exception of lateral ventricular volume, there were no significant interactions between presence of apoE4, the top sex-specific quartile of the Stroke Risk Profile and any of the magnetic resonance imaging variables.
Conclusion
The apoE4 allele exacerbates the effects of cerebrovascular risk factors on neuropsychological function. This relationship appears to be driven by systolic blood pressure, suggesting that treatment of high systolic blood pressure could potentially reduce risk of cognitive impairment among those already at increased risk for Alzheimer’s disease.
doi:10.1016/j.jstrokecerebrovasdis.2009.05.001
PMCID: PMC2900511  PMID: 20471857
25.  Diagnostic utility of the NAB List Learning test in Alzheimer’s disease and amnestic mild cognitive impairment 
Measures of episodic memory are often used to identify Alzheimer’s disease (AD) and mild cognitive impairment (MCI). The Neuropsychological Assessment Battery (NAB) List Learning test is a promising tool for the memory assessment of older adults due to its simplicity of administration, good psychometric properties, equivalent forms, and extensive normative data. This study examined the diagnostic utility of the NAB List Learning test for differentiating cognitively healthy, MCI, and AD groups. One-hundred fifty-three participants (age: range = 57-94 years, M = 74 years, S. D. = 8 years; sex: 61% women) were diagnosed by a multidisciplinary consensus team as cognitively normal, amnestic MCI (aMCI; single and multiple domain), or AD, independent of NAB List Learning performance. In univariate analyses, receiver operating characteristics curve analyses were conducted for four demographically-corrected NAB List Learning variables. Additionally, multivariate ordinal logistic regression and five-fold cross-validation was used to create and validate a predictive model based on NAB List Learning test T-scores. At optimal cutoff scores, univariate sensitivity values ranged from .58 - .92 and univariate specificity values ranged from .52 - .97. Multivariate ordinal regression produced a model that classified individuals with 80% accuracy and good predictive power.
doi:10.1017/S1355617708090176
PMCID: PMC2666978  PMID: 19128535
Dementia; Sensitivity and Specificity; Differential Diagnosis; Neuropsychology; Neuropsychological Tests; Memory

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