Background/Aims

An item response theory (IRT)-based scoring approach to the Clinical Dementia Rating (CDR) scale can account for the pattern of scores across the CDR items (domains) and the items’ differential abilities to indicate dementia severity. In doing so, an IRT-based approach can provide greater precision than other CDR scoring algorithms. However, neither a good set of item parameters nor an easily digestible set of instructions needed to implement this approach is readily available.

Methods

Participants were 1,326 patients at the Baylor College of Medicine Alzheimer’s Disease and Memory Disorders Clinic.

Results

The item parameters necessary for an IRT-based scoring approach were identified (a parameters ranged from 3.01 to 6.22; b parameters ranged from −2.46 to 2.07).

Conclusion

This study provides and demonstrates how to easily apply IRT-based item parameters for the CDR.

Background

A strong inverse relationship of functional limitation and socioeconomic status has been established in western ageing society. Functional limitation can be related to chronic diseases, disuse, cognitive decline, and ageing. Among chronic diseases in the Thai population, cerebrovascular diseases, diabetes, and arthritis are common. These factors are known to contribute to disability and poor quality of life in the elder population. Neuropsychiatric problems, cognitive decline, dementia, and cultural issues in elderly people also can alter the quality of life of the elderly.

Methods

The Dementia and Disability Project in Thai Elderly (DDP) aims at comprehensively assessing community dwelling Thai elderly to understand the relationship between disability and motor function, neuropsychiatric symptoms, cognitive function, and chronic diseases. The DDP is the first study to look at the prevalence and etiology of dementia and of mild cognitive impairment (MCI) in Thai elders and to explore the relationship of cognition, disability, small vessel diseases and cortical degeneration with neuroimaging in Thai elderly people. 1998 Thai elders were screened in 2004–2006 and diagnosed as having MCI or dementia. 223 elders with MCI or dementia and cognitively normal elderly had brain magnetic resonance imaging (MRI) or at baseline. 319 elders from the 3 groups had blood tests to investigate the risks and possible etiologies of dementia including genotyping at baseline.

Results

The mean age of elders in this study is 69.51(SD=6.71, min=60, max=95) years. 689(34.9%) are men and 1284(65.1%) are women. Mean body weight was 58.36(SD=11.20) kgs. The regression model reveals that performance on gait and balance and serum triglyceride predicts activity of daily living performance (adjusted r2 = 0.280, f=2.644, p=0.003). The majority of abnormal gait in Thai elders was lower level gait disturbance. Only 1.5% (29/1952) had highest level gait disorders. 39.5% of 1964 subjects were free of chronic diseases. Treatment gap (indicating those who have untreated or inadequate treatment) of diabetes mellitus and hypertension in Thai elders in this study was 37% and 55.5% respectively. 62.6% of Thai elders have ApoE3E3 allele. Prevalence of positive ApoE4 gene in this study is 22.85%. 38.6% of Thai elders who had MRI brain study have moderate to severe white matter lesions.

Conclusion

The large and comprehensive set of measurements in DDP allows a wide-ranging explanation of the functional and clinical features to be investigated in relation to white matter lesions or cortical atrophy of the brain in Thai elderly population. An almost 2 year follow up was made available to those with MCI and dementia and some of the cognitively normal elderly. The longitudinal design will provide great understanding of the possible contributors to disability in the elderly and to the progression of cognitive decline in Thai elders.

Background

We previously created a serum-based algorithm that yielded excellent diagnostic accuracy in Alzheimer's disease. The current project was designed to refine that algorithm by reducing the number of serum proteins and by including clinical labs. The link between the biomarker risk score and neuropsychological performance was also examined.

Methods

Serum-protein multiplex biomarker data from 197 patients diagnosed with Alzheimer's disease and 203 cognitively normal controls from the Texas Alzheimer's Research Consortium were analyzed. The 30 markers identified as the most important from our initial analyses and clinical labs were utilized to create the algorithm.

Results

The 30-protein risk score yielded a sensitivity, specificity, and AUC of 0.88, 0.82, and 0.91, respectively. When combined with demographic data and clinical labs, the algorithm yielded a sensitivity, specificity, and AUC of 0.89, 0.85, and 0.94, respectively. In linear regression models, the biomarker risk score was most strongly related to neuropsychological tests of language and memory.

Conclusions

Our previously published diagnostic algorithm can be restricted to only 30 serum proteins and still retain excellent diagnostic accuracy. Additionally, the revised biomarker risk score is significantly related to neuropsychological test performance.

Background

The Clinical Dementia Rating Scale Sum of Boxes (CDR-SOB) score is commonly used, although the utility regarding this score in staging dementia severity is not well established.

Obiective

To investigate the effectiveness of CDRSOB scores in staging dementia severity compared with the global CDR score.

Design

Retrospective study.

Setting

Texas Alzheimer's Research Consortium minimum data set cohort.

Participants

A total of 1577 participants (110 controls, 202 patients with mild cognitive impairment, and 1265 patients with probable Alzheimer disease) were available for analysis.

Main Outcome Measures

Receiver operating characteristic curves were generated from a derivation sample to determine optimal cutoff scores and ranges, which were then applied to the validation sample.

Results

Optimal ranges of CDR-SOB scores corresponding to the global CDR scores were 0.5 to 4.0 for a global score of 0.5, 4.5 to 9.0 for a global score of 1.O, 9.5 to 15.5 for a global score of 2.0, and 16.0 to 18.0 for a global score of 3.0. When applied to the validation sample, κ scores ranged from 0.86 to 0.94 (P <.001 for all), with 93.0% of the participants falling within the new staging categories.

Conclusions

The CDR-SOB score compares well with the global CDR score for dementia staging. Owing to the increased range of values, the CDR-SOB score offers several advantages over the global score, including increased utility in tracking changes within and between stages of dementia severity. Interpretive guidelines for CDR-SOB scores are provided.

Introduction

This longitudinal study examined multiple factors that influence survival in a cohort of Alzheimer patients followed over two decades.

Methods

Time to death after symptom onset was determined in 641 probable AD patients who were evaluated annually until death or loss to follow-up, and information was entered into a longitudinal database. Date of death was available for everyone including those eventually lost. Baseline variables included age, sex, race, disease severity, a calculated index of rate of initial cognitive decline from symptom onset to cohort entry (pre-progression rate or PPR), years of education, and medical comorbidities (diabetes, hypertension, hyperlipidemia, coronary disease, cerebrovascular disease). Multivariable Cox proportional hazard regression analysis was used to analyze the baseline and/or time dependent association in Mini-mental Status Exam (MMSE) severity, Physical Self Maintenance Scale (PSMS), Persistency Index (PI) of exposure to antipsychotic and antidementia drugs, and psychotic symptoms (hallucinations, delusions) with mortality.

Results

Baseline covariates significantly associated with increased survival were younger age (p = .0016), female sex (p = .0001), and a slower PPR (p < .0001). Overall disease severity at baseline, medical comorbidities, and education did not influence time to death. Time-dependent changes in antipsychotic drug use, development of psychotic symptoms, antidementia drug use, and observed MMSE change were not predictive. In the final model the only time-dependent covariate that significantly decreased survival was worsening of functional ability on the PSMS (hazard ratio = 1.10; CI: 1.07-1.11).

Conclusions

In this large AD cohort survival is influenced by age, sex, and the development of functional disability during follow-up. The most important predictor of mortality was a faster rate of cognitive decline at the initial patient visit (PPR). The currently available antidementia drugs do not prolong survival in Alzheimer patients.

Limitations on the duration of clinical trials, and the constraints of participant selection for such studies, have left many unanswered questions regarding the optimal duration of drug treatment for Alzheimer's disease patients, as well as the subgroups of patients that benefit most. Carefully designed observational studies in naturalistic settings can provide important supplementary information to aid clinical decision-making and patient counseling. A paper by Wattmo and colleagues published recently in Alzheimer's Research & Therapy has provided important new information on differential responses to cholinesterase inhibitor (ChEI) treatment in specific subgroups of patients over a 3-year follow-up period. All of the participants in their study were started on one of three ChEIs after their initial assessment, and periodic assessments of cognitive change and the dosage of ChEIs as well as concomitant medications were subsequently recorded. In addition to providing strong evidence of nondifferential effects on cognition of the three ChEIs as used in this practice, the study identified clinically significant differences in the responses of specific subgroups of patients to the initiation of ChEI treatment. Of particular interest to clinicians is the finding that older patients and those with worse cognitive functioning at baseline had a better treatment response. The notion that treatment may be futile in the oldest or the most impaired patients was thus not supported by Wattmo and colleagues' cohort. Additional well-designed naturalistic studies of this type are needed to advance our knowledge of the long-term outcomes obtained with different therapeutic agents, and of the covariates that significantly modify responses to Alzheimer's disease treatments.

Context

There is no rapid and cost effective tool that can be implemented as a front-line screening tool for Alzheimer's disease (AD) at the population level.

Objective

To generate and cross-validate a blood-based screener for AD that yields acceptable accuracy across both serum and plasma.

Design, Setting, Participants

Analysis of serum biomarker proteins were conducted on 197 Alzheimer's disease (AD) participants and 199 control participants from the Texas Alzheimer's Research Consortium (TARC) with further analysis conducted on plasma proteins from 112 AD and 52 control participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The full algorithm was derived from a biomarker risk score, clinical lab (glucose, triglycerides, total cholesterol, homocysteine), and demographic (age, gender, education, APOE*E4 status) data.

Major Outcome Measures

Alzheimer's disease.

Results

11 proteins met our criteria and were utilized for the biomarker risk score. The random forest (RF) biomarker risk score from the TARC serum samples (training set) yielded adequate accuracy in the ADNI plasma sample (training set) (AUC = 0.70, sensitivity (SN) = 0.54 and specificity (SP) = 0.78), which was below that obtained from ADNI cerebral spinal fluid (CSF) analyses (t-tau/Aβ ratio AUC = 0.92). However, the full algorithm yielded excellent accuracy (AUC = 0.88, SN = 0.75, and SP = 0.91). The likelihood ratio of having AD based on a positive test finding (LR+) = 7.03 (SE = 1.17; 95% CI = 4.49–14.47), the likelihood ratio of not having AD based on the algorithm (LR−) = 3.55 (SE = 1.15; 2.22–5.71), and the odds ratio of AD were calculated in the ADNI cohort (OR) = 28.70 (1.55; 95% CI = 11.86–69.47).

Conclusions

It is possible to create a blood-based screening algorithm that works across both serum and plasma that provides a comparable screening accuracy to that obtained from CSF analyses.

Plasma sphingolipids have been shown to predict cognitive impairment and hippocampal volume loss, but there is little research in patients with Alzheimer’s disease dementia (AD). In this study we sought to determine whether plasma ceramides, dihydroceramides (DHCer), sphingomyelins (SM), or dihydrosphingomyelin (DHSM) levels and ratios of SM/ceramide or DHSM/DHCer were predictive of progression in AD. Probable AD patients (n=120) were enrolled in the Alzheimer’s Disease and Memory Disorders Center at Baylor College of Medicine. Plasma sphingolipids were assessed using ESI/MS/MS. Linear mixed effects models were used to examine the relation between baseline plasma sphingolipid levels and cross-sectional and longitudinal performance on the Mini-Mental State Exam (MMSE), Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), and Clinical Dementia Rating-Sum of Boxes (CDR-Sum). Participants were followed a mean of 4.2 visits and 2.3 years. There were no cross-sectional associations. In longitudinal analyses, high levels of DHCer and ceramide were associated with greater progression, but findings did not reach significance (p>0.05). In contrast, higher plasma levels of SM, DHSM, SM/ceramide and DHSM/DHCer ratios were associated with less progression on the MMSE and ADAS-Cog; the ratios were the strongest predictors of clinical progression. Compared to the lowest tertiles, the highest tertiles of DHSM/DHCer and SM/ceramide ratios declined 1.35 points (p=0.001) and 1.19 (p=0.004) less per year on the MMSE and increased 3.18 points (p=0.001) and 2.42 (p=0.016) less per year on the ADAS-Cog. These results suggest that increased SM/ceramide and DHSM/DHCer ratios dose-dependently predict slower progression among AD patients and may be sensitive blood-based biomarkers for clinical progression.

Background

Alzheimer's disease (AD) is the most common form of age-related dementia and one of the most serious health problems in the industrialized world. Biomarker approaches to diagnostics would be more time and cost effective and may also be useful for identifying endophenotypes within AD patient populations.

Methods

We analyzed serum protein-based multiplex biomarker data from 197 patients diagnosed with AD and 203 controls from a longitudinal study of Alzheimer's disease being conducted by the Texas Alzheimer's Research Consortium to develop an algorithm that separates AD from controls. The total sample was randomized equally into training and test sets and random forest methods were applied to the training set to create a biomarker risk score.

Findings

The biomarker risk score had a sensitivity and specificity of 0.80 and 0.91, respectively and an AUC of 0.91 in detecting AD. When age, gender, education, and APOE status were added to the algorithm, the sensitivity, specificity, and AUC were 0.94, 0.84, and 0.95, respectively.

Interpretation

These initial data suggest that serum protein-based biomarkers can be combined with clinical information to accurately classify AD. Of note, a disproportionate number of inflammatory and vascular markers were weighted most heavily in analyses. Additionally, these markers consistently distinguished cases from controls in SAM, logistic regression and Wilcoxon analyses, suggesting the existence of an inflammatory-related endophenotype of AD that may provide targeted therapeutic opportunities for this subset of patients.

Alzheimer disease (AD) is a devastating neurodegenerative disease affecting 1 in 68 in the population. An arbitrary cutoff 65 years as the age of onset to distinguish between early- and late-onset AD has been proposed and has been used in the literature for decades. As the majority of patients develop AD after 65 years of age, most clinical trials address this population. While the early-onset cases represent only 1% to 6% of AD cases, this population is the active working subset and thus contributes to a higher public health burden per individual, and early-onset cases are the most devastating at the level of the individual and their families. In this review, we compare and contrast the clinical, neuropsychological, imaging, genetic, biomarker, and pathological features of these two arbitrary groups. Finally, we discuss the ethical dilemma of non-abandonment and justice as it pertains to exclusion of the early-onset AD patients from clinical trials.

Background

Vitamin E at a dose of 2,000 IU per day has been shown to delay Alzheimer's disease (AD) progression, but recent studies have questioned the safety of this dose level and the overall efficacy of vitamin E in AD treatment.

Methods

We analyzed the survival history of 847 probable or mixed AD patients followed in a research center between 1990 and the censoring date of December 31, 2004. Standard practice during this period was to recommend vitamin E at 1,000 IU twice daily to all patients. We used Cox proportional hazards modeling to assess the association of vitamin E alone, or in combination with a cholinesterase inhibitor (ChEI), with all-cause mortality, adjusting for important covariates. Approximately two thirds of the patients took vitamin E with a ChEI, 10% took vitamin E alone, and 15% took no antidementia drug.

Results

The adjusted hazard ratio (HR) associated with vitamin E (with or without a ChEI) was 0.71 (95% CI: 0.57–0.89; p = 0.003). Compared to the no drug treatment group, the HR for vitamin E alone or with another drug was 0.77 (95% CI: 0.60–1.0); the HR for ChEI use alone was 1.2 (95% CI: 0.87–1.60).

Conclusion

The results do not support a concern over increased mortality with high-dose vitamin E supplementation.

Introduction

The Alzheimer's Disease Cooperative Study - Clinical Global Impression of Change (ADCS-CGIC) was modified for use in mild cognitive impairment (MCI) trials and tested in the ADCS MCI randomized clinical trial of donepezil, vitamin E and placebo. We assessed feasibility for its use by determining whether or not: (1) it distinguished a medication effect at 6- and 12- months, (2) baseline demographic or clinical characteristics predicted change, (3) there was an association between MCI-CGIC and change in other clinical measures in order to evaluate external or concurrent validity.

Methods

We used a generalized estimating equations approach for ordinal outcome data to test the effects of treatment, baseline characteristics and change in clinical measures on the MCI-CGIC over 12 months, and ordinal logistic regression to assess the association between MCI-CGIC and change in clinical measures at 6 months and 12 months.

Results

On the MCI-CGIC overall, 12.9% and 10.6% were rated as having improved, and 31.6% and 39.8% as having worsened over 6- and 12-months, respectively. The MCI-CGIC did not distinguish the donepezil or vitamin E groups from placebo at 6 and 12 months treatment. Variables at screening or baseline that were associated with worse CGIC scores over 6 and 12 months included white race, greater years of education, worse depression, dementia severity rating, cognitive, and daily activities scores, and lower memory domain scores on a neuropsychological battery. Rate of worsening on the MCI-CGIC over 12 months was associated with change on the AD Assessment Scale-cognitive (ADAS-cog) and on executive function. Worsening at 6 months and 12 months, separately, were associated with the corresponding change in ADAS-cog, ADL, BDI, MMSE, CDR-sb, memory, and executive function.

Conclusions

Change detected by the MCI-CGIC was associated with baseline clinical severity and with change in clinical ratings over 6 and 12 months, supporting the validity of a CGIC approach in MCI. The effect size of the donepezil-placebo difference was similar to that of other outcomes at 12 months. About 40% of MCI patients were judged worse and about 11% improved, consistent with clinical experience and other ratings.

Introduction

Clinicians need to predict prognosis of Alzheimer's disease (AD), and researchers need models of progression to develop biomarkers and clinical trials designs. We tested a calculated initial progression rate to see whether it predicted performance on cognition, function and behavior over time, and to see whether it predicted survival.

Methods

We used standardized approaches to assess baseline characteristics and to estimate disease duration, and calculated the initial (pre-progression) rate in 597 AD patients followed for up to 15 years. We designated slow, intermediate and rapidly progressing groups. Using mixed effects regression analysis, we examined the predictive value of a pre-progression group for longitudinal performance on standardized measures. We used Cox survival analysis to compare survival time by progression group.

Results

Patients in the slow and intermediate groups maintained better performance on the cognitive (ADAScog and VSAT), global (CDR-SB) and complex activities of daily living measures (IADL) (P values < 0.001 slow versus fast; P values < 0.003 to 0.03 intermediate versus fast). Interaction terms indicated that slopes of ADAScog and PSMS change for the slow group were smaller than for the fast group, and that rates of change on the ADAScog were also slower for the intermediate group, but that CDR-SB rates increased in this group relative to the fast group. Slow progressors survived longer than fast progressors (P = 0.024).

Conclusions

A simple, calculated progression rate at the initial visit gives reliable information regarding performance over time on cognition, global performance and activities of daily living. The slowest progression group also survives longer. This baseline measure should be considered in the design of long duration Alzheimer's disease clinical trials.

Despite the public health implications of self-neglect, no tool exists for characterizing this condition. Self-neglecters often have no caregivers or surrogates to interview regarding the neglect, and are often too cognitively impaired to provide valid self-reports. In response to this need, researchers from the Consortium for Research in Elder Self-neglect of Texas (CREST), collaborated with other experts in the field of elder self-neglect to design the Self-neglect Severity Scale (SSS). The SSS assesses three domains of self-neglect: hygiene, functioning, and environment and relies on observational ratings assigned by trained observers. Following pilot testing and revision, the SSS was field tested in the homes of subjects who had been reported to and substantiated by Texas Adult Protective Services (APS) as self-neglecting, and compared to subjects recruited from a local geriatric clinic who were reported to APS and who had no history of self-neglect.

The first field test demonstrated that the SSS could distinguish elder self-neglecters from community dwellers that do not self-neglect. The SSS exhibited adequate scale reliability (Cronbach’s alpha) and correlation with case status. Interrater reliability also appeared adequate although sensitivity and specificity fell below the conventional acceptable range. Future methods are proposed for refining the SSS to improve its use as the benchmark for identifying elder self-neglect.

The vitamin E and donepezil trial for the treatment of amnestic mild cognitive impairment (MCI) was conducted at 69 centers in North America; 24 centers participated in an MRI sub study. The objective of this study was to evaluate the effect of treatment on MRI atrophy rates; and validate rate measures from serial MRI as indicators of disease progression in multi center therapeutic trials for MCI. Annual percent change (APC) from baseline to follow-up was measured for hippocampus, entorhinal cortex, whole brain, and ventricle in the 131 subjects who remained in the treatment study and completed technically satisfactory baseline and follow-up scans. Although a non-significant trend toward slowing of hippocampal atrophy rates was seen in APOE ∈4 carriers treated with donepezil; no treatment effect was confirmed for any MRI measure in either treatment group. For each of the four brain atrophy rate measures, APCs were greater in subjects who converted to AD than non-converters, and were greater in APOE ∈4 carriers than non-carriers. MRI APCs and changes in cognitive test performance were uniformly correlated in the expected direction (all p < 0.000). Results of this study support the feasibility of using MRI as an outcome measure of disease progression in multi center therapeutic trials for MCI.

Introduction

There are no empiric data to support guidelines for duration of therapy with antidementia drugs. This study examined whether persistent use of antidementia drugs slows clinical progression of Alzheimer disease (AD) assessed by repeated measures on serial tests of cognition and function.

Methods

Six hundred forty-one probable AD patients were followed prospectively at an academic center over 20 years. Cumulative drug exposure was expressed as a persistency index (PI) reflecting total years of drug use divided by total years of disease symptoms. Baseline and annual testing consisted of Mini-Mental State Examination (MMSE), Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), Baylor Profound Mental Status Examination (BPMSE), Clinical Dementia Rating-Sum of Boxes (CDR-SB), Physical Self-Maintenance Scale (PSMS), and Instrumental Activities of Daily Living (IADL). Annual change in slope of neuropsychological and functional tests as predicted by follow-up time, PI, and the interaction of these two variables was evaluated.

Results

PI was associated with significantly slower rates of decline (with, without adjustment for covariates) on MMSE (P < 0.0001), PSMS (P < 0.05), IADL (P < 0.0001), and CDR-SB (P < 0.001). There was an insignificant trend (P = 0.053) for the PI to be associated with slower rate of decline on BPMSE. The association of PI with ADAS-Cog followed a quadratic trend (P < 0.01). Analysis including both linear and quadratic terms suggests that PI slowed ADAS-Cog decline temporarily. The magnitude of the favorable effect of a rate change in PI was: MMSE 1 point per year, PSMS 0.4 points per year, IADL 1.4 points per year, and CDR-SB 0.6 points per year. The change in mean test scores is additive over the follow-up period (3 ± 1.94 years).

Conclusions

Persistent drug treatment had a positive impact on AD progression assessed by multiple cognitive, functional, and global outcome measures. The magnitude of the treatment effect was clinically significant. Positive treatment effects were even found in those with advanced disease.