Impact of early intervention and disease modification in patients with predementia Alzheimer's disease: a Markov model simulation

Montreal Cognitive Assessment (MoCA) XpressO: Validation of a digital self-administered cognitive prescreening tool

BACKGROUND

The need for cognitive testing is increasing with the aging population and the advent of new Alzheimer disease therapies. To respond to the increased demand, the XpressO was developed as a self-administered digital cognitive prescreening tool that will help distinguish between populations of subjective and objective cognitive impairment according to the Montreal Cognitive Assessment (MoCA).

METHODS

This is a prospective validation study. XpressO is composed of tasks that assess memory and executive functions. It is validated compared to the digital MoCA as a gold standard. Out of 118 participants screened from the MoCA Clinic and a family practice clinic, 88 met inclusion criteria, two participants had missing data due to incomplete tasks, 86 participants were included in the analysis; the mean age was 70.34 years. A logistic regression model was built, and its accuracy was evaluated by the sensitivity, specificity, and Area Under the Curve (AUC) of the Receiver Operating Characteristic.

RESULTS

Analysis showed strong correlation between (1) XpressO memory tasks scores and the MoCA Memory Index Score (p-values < 0.001), and between (2) XpressO sub-test scores and MoCA total score (p-values < 0.005). The AUC for predicting MoCA performance is 0.845. To classify individuals with normal and abnormal MoCA scores, two threshold values were introduced for the total XpressO scores: sensitivity of 91% at a cutoff of 72, specificity of 90% at a cutoff of 42, and an undetermined range in between.

CONCLUSION

XpressO demonstrated high AUC, high sensitivity and specificity to predict cognitive performance compared to the digital MoCA. It may provide efficient cognitive prescreening by identifying individuals who would benefit from further clinical assessments, potentially reducing waiting times and high burden on healthcare clinics.

The computerized LASSI-BC Test versus the Standard LASSI-L Paper-and-Pencil Version in Community-Based-Samples

Proactive Semantic Interference (PSI) and failure to recover from PSI (frPSI), are novel constructs assessed by the LASSI-L. These measures are sensitive to cognitive changes in early Mild Cognitive Impairment (MCI) and preclinical AD determined by Aβ load using PET. The goal of this study was to compare a new computerized version of the LASSI-L (LASSI-Brief Computerized) to the standard paper-and-pencil version of the test. In this study, we examined 110 cognitively unimpaired (CU) older adults and 79 with amnestic MCI (aMCI) who were administered the paper-and-pencil form of the LASSI-L. Their performance was compared with 62 CU older adults and 52 aMCI participants examined using the LASSI-BC. After adjustment for covariates (degree of initial learning, sex, education, and language of evaluation) both the standard and computerized versions distinguished between aMCI and CU participants. The performance of CU and aMCI groups using either form was relatively commensurate. Importantly, an optimal combination of Cued B2 recall and Cued B1 intrusions on the LASSI-BC yielded an area under the ROC curve of .927, a sensitivity of 92.3% and specificity of 88.1%, relative to an area under the ROC curve of .815, a sensitivity of 72.5%, and a specificity of 79.1% obtained for the paper-and-pencil LASSI-L. Overall, the LASSI-BC was comparable, and in some ways, superior to the paper-and-pencil LASSI-L. Advantages of the LASSI-BC include a more standardized administration, suitability for remote assessment, and an automated scoring mechanism that can be verified by a built-in audio recording of responses.

Associations between recall of proper names in story recall and CSF amyloid and tau in adults without cognitive impairment

Neuropsychological measures sensitive to decline in the preclinical phase of Alzheimer's disease are needed. We previously demonstrated that higher amyloid-beta (Aβ) assessed by positron emission tomography in adults without cognitive impairment was associated with recall of fewer proper names in Logical Memory story recall. The current study investigated the association between proper names and cerebrospinal fluid biomarkers (Aβ42/40, phosphorylated tau181 [pTau181], neurofilament light) in 223 participants from the Wisconsin Registry for Alzheimer's Prevention. We assessed associations between biomarkers and delayed Logical Memory total score and proper names using binary logistic regressions. Sensitivity analyses used multinomial logistic regression and stratified biomarker groups. Lower Logical Memory total score and proper names scores from the most recent visit were associated with biomarker positivity. Relatedly, there was a 27% decreased risk of being classified Aβ42/40+/pTau181+ for each additional proper name recalled. A linear mixed effects model found that longitudinal change in proper names recall was predicted by biomarker status. These results demonstrate a novel relationship between proper names and Alzheimer's disease-cerebrospinal fluid pathology.

Adjunctive transcranial direct current stimulation (tDCS) plus sodium benzoate for the treatment of early-phase Alzheimer's disease: A randomized, double-blind, placebo-controlled trial

Previous studies found that an NMDA receptor (NMDAR) enhancer, sodium benzoate, improved cognitive function of patients with early-phase Alzheimer's disease (AD). Transcranial direct current stimulation (tDCS) induces NMDAR-dependent synaptic plasticity and strengthens cognitive function of AD patients. This study aimed to evaluate efficacy and safety of tDCS plus benzoate in early-phase dementia. In this 24-week randomized, double-blind, placebo-controlled trial, 97 patients with early-phase AD received 10-session tDCS during the first 2 weeks. They then took benzoate or placebo for 24 weeks. We assessed the patients using Alzheimer's disease assessment scale - cognitive subscale (ADAS-cog), Clinician's Interview-Based Impression of Change plus Caregiver Input, Mini Mental Status Examination, Alzheimer's disease Cooperative Study scale for ADL in MCI, and a battery of additional cognitive tests. Forty-seven patients received sodium benzoate, and the other 50 placebo. The two treatment groups didn't differ significantly in ADAS-cog or other measures. Addition of benzoate to tDCS didn't get extra benefit or side effect in this study. For more thoroughly studying the potential of combining tDCS with benzoate in the AD treatment, future research should use other study designs, such as longer-term benzoate treatment, adding benzoate in the middle of tDCS trial sessions, or administering benzoate then tDCS.

The effect of a digital health coaching and health education protocol on cognition in adults at-risk for Alzheimer's

Several modifiable lifestyle factors have been linked to cognitive ability and the risk of developing Alzheimer's disease and related dementias (ADRD). Health coaching (HC) is an intervention that addresses lifestyle factors associated with cognition. The effectiveness of an HC protocol was evaluated and compared with a health education (HE) intervention, representing the current standard of care, in a sample of 216 adults between the ages of 45 and 75 years who were at-risk for developing ADRD. Outcomes examined were global cognition, neuropsychological cognition, and Alzheimer's risk. HC participants received personalized coaching from a health coach focusing on nutrition, physical activity, sleep, stress, social engagement, and cognitive activity. HE participants received biweekly education materials focusing on the same modifiable lifestyle factors addressed by HC. Participants were assessed at baseline and again 4 months later. Self-reported global cognition scores improved only in the HC group (16.18 to 15.52, p = .03) and neuropsychological cognitive ability improved in the HE group (104.48 to 108.76, p < .001). When non-adherence in the HC group was accounted for, however, the mean change in neuropsychological score was similar between groups (p > .05), self-reported global cognition demonstrated an even larger mean improvement in the HC group (16.20 to 15.41, p = .01), and the HC group saw an improvement in ADRD protective risk score (- 10.39 to - 11.45, p = .007). These results indicate that HC and HE can both improve cognition, but HC may be more effective and may yield increased protection against ADRD risk.

Effect of mortality in cost-effectiveness modeling of disease-modifying treatment for Alzheimer's disease

INTRODUCTION

We examined (1) the magnitude of mortality attributed to Alzheimer's disease (AD), and (2) the effect of mortality in cost-effectiveness modeling of hypothetical disease-modifying treatment (DMT) in AD.

METHOD

Data were derived from Swedish Dementia Registry (N = 39,308). Mortality was analyzed with survival analysis and multinomial logistic regression. A Markov microsimulation model was used to model the cost effectiveness of DMT using routine care as a comparator. Three scenarios were simulated: (1) indirect effect, (2) no effect on overall mortality, (3) indirect effect on AD-related mortality.

RESULTS

Overall mortality increased with cognitive decline, age, male sex, number of medications used, and lower body mass index. Nearly all cause-specific mortality was associated with cognitive decline. DMT increased survival by 0.35 years in scenario 1 and 0.14 years in scenario 3. DMT with no mortality effect is the least cost effective.

DISCUSSION

The results provide key mortality estimates and demonstrate influences on the cost effectiveness of DMT.

Highlights

We describe cause-specific mortality in relation to disease severity in Alzheimer's disease (AD).We model different assumptions of disease-modifying treatment (DMT) on AD survival.DMT was the least cost effective when assuming no effect on AD survival.Cost effectiveness is mainly influenced by the relative cost of staying in each disease state.

Predicting Progression to Clinical Alzheimer's Disease Dementia Using the Random Survival Forest

BACKGROUND

Assessing the risk of developing clinical Alzheimer's disease (AD) dementia, by machine learning survival analysis approaches, among participants registered in Alzheimer's Disease Centers is important for AD dementia management.

OBJECTIVE

To construct a prediction model for the onset time of clinical AD dementia using the National Alzheimer Coordinating Center (NACC) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) registered cohorts.

METHODS

A model was constructed using the Random Survival Forest (RSF) approach and internally and externally validated on the NACC cohort and the ADNI cohort. An R package and a Shiny app were provided for accessing the model.

RESULTS

We built a predictive model having the six predictors: delayed logical memory score (story recall), CDR® Dementia Staging Instrument - Sum of Boxes, general orientation in CDR®, ability to remember dates and ability to pay bills in the Functional Activities Questionnaire, and patient age. The C indices of the model were 90.82% (SE = 0.71%) and 86.51% (SE = 0.75%) in NACC and ADNI respectively. The time-dependent AUC and accuracy at 48 months were 92.48% (SE = 1.12%) and 88.66% (SE = 1.00%) respectively in NACC, and 90.16% (SE = 1.12%) and 85.00% (SE = 1.14%) respectively in ADNI.

CONCLUSION

The model showed good prediction performance and the six predictors were easy to obtain, cost-effective, and non-invasive. The model could be used to inform clinicians and patients on the probability of developing clinical AD dementia in 4 years with high accuracy.

Diagnosing Alzheimer's Disease Specifically and Sensitively With pLG72 and Cystine/Glutamate Antiporter SLC7A11 AS Blood Biomarkers

BACKGROUND

Reliable blood biomarkers for Alzheimer's disease (AD) have been lacking. The D-amino acids oxidase modulator (named pLG72) modulates glutamate N-methyl-D-aspartate receptor activity. The cystine/glutamate antiporter contains a SLC7A11 subunit, which mediates glutamate release. This study aimed to determine the accuracy of pLG72 protein and SLC7A11 mRNA in diagnosing AD.

METHODS

This study enrolled 130 healthy controls and 109 unmatched AD patients; among them, 40 controls and 70 patients were selected to match by age. We measured their pLG72 protein in plasma and SLC7A11 mRNA in white blood cells.

RESULTS

AD patients had markedly higher pLG72 levels and SLC7A11 mRNA ΔCT values than healthy controls (in both unmatched and matched cohorts; all 4 P values <.001). The receiver operating characteristics analysis in the unmatched cohorts demonstrated that the pLG72 level had a high specificity (0.900) at the optimal cutoff value of 2.3285, the ΔCT of SLC7A11 mRNA displayed an excellent sensitivity (0.954) at the cutoff of 12.185, and the combined value of pLG72 and SLC7A11 ΔCT determined a favorable area under the curve (AUC) (0.882) at the cutoff of 21.721. The AUC of the combined value surpassed that of either biomarker. The specificity, sensitivity, and AUC of the matched cohort were like those of the unmatched cohort.

CONCLUSIONS

The findings suggest that pLG72 protein and SLC7A11 mRNA can distinguish AD patients from healthy controls with excellent specificity and sensitivity, respectively. The combination of pLG72 and SLC7A11 yields better AUC than either, suggesting the superiority of simultaneously measuring both biomarkers in identifying AD patients.

Costs of Persons with Dementia Living in Nursing Homes in The Netherlands

Background: Disease modifying treatments (DMTs) currently under development for Alzheimer’s disease, have the potential to prevent or postpone institutionalization and more expensive care and might delay institutionalization of persons with dementia. Objective: The current study estimates costs of living in a nursing home for persons with dementia in the Netherlands to help inform economic evaluations of future DMTs. Methods: Data were collected during semi-structured interviews with healthcare professionals and from the financial administration of a healthcare organization with several nursing homes. Personnel costs were calculated using a bottom-up approach by valuing the time estimates. Non-personnel costs were calculated using information from the financial administration of the healthcare organization. Results: Total personnel costs of a person with dementia per 24 hours, including both care staff and other healthcare providers, were € 151 for small-scale living wards and € 147 for independent living wards. Non-personnel costs were € 37 per day. Conclusion: This study provides Dutch estimates for total healthcare costs per day for institutionalized persons with dementia. These cost estimates can be used in cost-effectiveness analyses for future DMTs in dementia.

Natural Pattern of Cognitive Aging

BACKGROUND

Considering the world's rapidly increasing life expectancy, with people working and maintaining active lifestyles longer than ever before, addressing the effects of aging on cognition is of utmost importance. A greater understanding of cognitive aging may also be critical in distinguishing natural cognitive aging from pre-clinical stages of Alzheimer's disease and related cognitive disorders.

OBJECTIVE

To systematically examine the association between aging and cognitive performance in a cognitively and otherwise healthy probability population-based sample using a computer-based method.

METHODS

This cross-sectional study enrolled 673 cognitively and otherwise healthy participants aged 25-89 years (mean age 52.3±14.2 years, 52.5% of whom were female) from the Kardiovize study cohort. Mild cognitive impairment and dementia cases were excluded, followed by measurement of cognitive performance with the computer-administered Cogstate Brief Battery. We used ANCOVA and Modified Signed-Likelihood Ratio tests to examine patterns of cognition across age groups.

RESULTS

We found a gradual decrease in cognitive performance across the lifespan, which required two decades to demonstrate significant changes. In contrast to attention and learning, psychomotor speed and working memory showed the most significant age-related decrease and variability in performance. The established pattern of cognitive aging was not altered by sex or education.

CONCLUSION

These findings corroborate, validate, and extend the current understanding of natural cognitive aging and pinpoint specific cognitive domains with the most extensive age-related interindividual differences. This will contribute to the development of strategies to preserve cognition with aging and may also serve to improve early diagnostics of cognitive disorders using computer-based methods.

A Computerized Cognitive Test Battery for Detection of Dementia and Mild Cognitive Impairment: Instrument Validation Study

BACKGROUND

Early detection of dementia is critical for intervention and care planning but remains difficult. Computerized cognitive testing provides an accessible and promising solution to address these current challenges.

OBJECTIVE

The aim of this study was to evaluate a computerized cognitive testing battery (BrainCheck) for its diagnostic accuracy and ability to distinguish the severity of cognitive impairment.

METHODS

A total of 99 participants diagnosed with dementia, mild cognitive impairment (MCI), or normal cognition (NC) completed the BrainCheck battery. Statistical analyses compared participant performances on BrainCheck based on their diagnostic group.

RESULTS

BrainCheck battery performance showed significant differences between the NC, MCI, and dementia groups, achieving 88% or higher sensitivity and specificity (ie, true positive and true negative rates) for separating dementia from NC, and 77% or higher sensitivity and specificity in separating the MCI group from the NC and dementia groups. Three-group classification found true positive rates of 80% or higher for the NC and dementia groups and true positive rates of 64% or higher for the MCI group.

CONCLUSIONS

BrainCheck was able to distinguish between diagnoses of dementia, MCI, and NC, providing a potentially reliable tool for early detection of cognitive impairment.

Survival Analysis in Cognitively Normal Subjects and in Patients with Mild Cognitive Impairment Using a Proportional Hazards Model with Extreme Gradient Boosting Regression

BACKGROUND

Evaluating the risk of Alzheimer's disease (AD) in cognitively normal (CN) and patients with mild cognitive impairment (MCI) is extremely important. While MCI-to-AD progression risk has been studied extensively, few studies estimate CN-to-MCI conversion risk. The Cox proportional hazards (PH), a widely used survival analysis model, assumes a linear predictor-risk relationship. Generalizing the PH model to more complex predictor-risk relationships may increase risk estimation accuracy.

OBJECTIVE

The aim of this study was to develop a PH model using an Xgboost regressor, based on demographic, genetic, neuropsychiatric, and neuroimaging predictors to estimate risk of AD in patients with MCI, and the risk of MCI in CN subjects.

METHODS

We replaced the Cox PH linear model with an Xgboost regressor to capture complex interactions between predictors, and non-linear predictor-risk associations. We endeavored to limit model inputs to noninvasive and more widely available predictors in order to facilitate future applicability in a wider setting.

RESULTS

In MCI-to-AD (n = 882), the Xgboost model achieved a concordance index (C-index) of 84.5%. When the model was used for MCI risk prediction in CN (n = 100) individuals, the C-index was 73.3%. In both applications, the C-index was statistically significantly higher in the Xgboost in comparison to the Cox PH model.

CONCLUSION

Using non-linear regressors such as Xgboost improves AD dementia risk assessment in CN and MCI. It is possible to achieve reasonable risk stratification using predictors that are relatively low-cost in terms of time, invasiveness, and availability. Future strategies for improving AD dementia risk estimation are discussed.

Predicted Lifetime Health Outcomes for Aducanumab in Patients with Early Alzheimer's Disease

INTRODUCTION

Alzheimer's disease (AD) is a chronic and progressive neurodegenerative disease that places a substantial burden on patients and caregivers. Aducanumab is the first AD therapy approved by the US Food and Drug Administration to reduce a defining pathophysiological feature of the disease, brain amyloid plaques. In the phase 3 clinical trial EMERGE (NCT02484547), aducanumab reduced clinical decline in patients with mild cognitive impairment (MCI) due to AD and mild AD dementia and confirmed amyloid pathology.

METHODS

We used a Markov modeling approach to predict the long-term clinical benefits of aducanumab for patients with early AD based on EMERGE efficacy data. In the model, patients could transition between AD severity levels (MCI due to AD; mild, moderate, and severe AD dementia) and care settings (community vs. institution) or transition to death. The intervention was aducanumab added to standard of care (SOC), and the comparator was SOC alone. Data sources for base-case and scenario analyses included EMERGE, published National Alzheimer's Coordinating Center analyses, and other published literature.

RESULTS

Per patient over a lifetime horizon, aducanumab treatment corresponded to 0.65 incremental patient quality-adjusted life-years (QALYs) and 0.09 fewer caregiver QALYs lost compared with patients treated with SOC. Aducanumab treatment translated to a lower lifetime probability of transitioning to AD dementia, a lower lifetime probability of transitioning to institutionalization (25.2% vs. 29.4%), delays in the median time to transition to AD dementia (7.50 vs. 4.92 years from MCI to moderate AD dementia or worse), and an incremental median time in the community of 1.32 years compared with SOC.

CONCLUSION

The model predicted long-term benefits of aducanumab treatment in patients with MCI due to AD and mild AD dementia and their caregivers. The predicted outcomes provide a foundation for healthcare decision-makers and policymakers to understand the potential clinical and socioeconomic value of aducanumab.

Changes in LASSI-L performance over time among older adults with amnestic MCI and amyloid positivity: A preliminary study

There is a pressing need to develop measures that are sensitive to the earliest subtle cognitive changes of Alzheimer's disease (AD) to improve early detection and track disease progression. The Loewenstein-Acevedo Scales of Semantic Interference (LASSI-L) has been shown to successfully discriminate between cognitively unimpaired (CU) older adults and those with amnestic mild cognitive impairment (MCI) and to correlate with total and regional brain amyloid load. The present study investigated how the LASSI-L scores change over time among three distinct diagnostic groups. Eighty-six community-dwelling older adults underwent a baseline evaluation including: a clinical interview, a neuropsychological evaluation, Magnetic Resonance Imaging (MRI), and amyloid Positron Emission Tomography (PET). A follow up evaluation was conducted 12 months later. Initial mean values were calculated using one-way ANOVAs and chi-square analyses. Post-hoc comparisons were conducted using Tukey's Honestly Significant Difference (HSD). A 3 × 2 repeated measures analysis was utilized to examine differences in LASSI-L performance over time. The MCI amyloid positive group demonstrated a significantly greater decline in LASSI-L performance than the MCI amyloid negative and CU groups respectively. The scales that best differentiated the three groups included the Cued A2, which taps into maximum learning capacity, and Cued B2, which assesses the failure to recover from proactive semantic interference. Our findings further support the LASSI-L's discriminative validity.

How Much Value Would a Treatment for Alzheimer's Disease Offer? Cost-Effectiveness Thresholds for Pricing a Disease-Modifying Therapy

BACKGROUND

Recent trials suggest that disease-modifying therapy (DMT) for Alzheimer's disease may become available soon. With the expected high price and a large patient pool, the budget impact will be substantial.

OBJECTIVE

We explore combinations of effectiveness and price under which a DMT is cost-effective.

METHODS

We used an open-source model to conduct two-way scenario analyses for both payer and societal perspectives, varying price, and treatment effect size simultaneously. The analysis generates costeffectiveness threshold prices over a potential range of DMT effectiveness in patients aged 65+ with mild cognitive impairment due to Alzheimer's disease in the US.

RESULTS

Under the willingness-to-pay a threshold of $150,000 per quality-adjusted life year and assuming 30% risk reduction relative to the standard of care, the maximum cost-effective price of a DMT per patient per year is ~$22,000 and ~$15,000 from societal and payer perspectives, respectively.

CONCLUSION

Joint variation of price and treatment effect size can help assess the cost-effectiveness of a potential Alzheimer's disease treatment.

Supervised Digital Neuropsychological Tests for Cognitive Decline in Older Adults: Usability and Clinical Validity Study

Background

Dementia is a major and growing health problem, and early diagnosis is key to its management.

Objective

With the ultimate goal of providing a monitoring tool that could be used to support the screening for cognitive decline, this study aims to develop a supervised, digitized version of 2 neuropsychological tests: Trail Making Test and Bells Test. The system consists of a web app that implements a tablet-based version of the tests and consists of an innovative vocal assistant that acts as the virtual supervisor for the execution of the test. A replay functionality is added to allow inspection of the user’s performance after test completion.

Methods

To deploy the system in a nonsupervised environment, extensive functional testing of the platform was conducted, together with a validation of the tablet-based tests. Such validation had the two-fold aim of evaluating system usability and acceptance and investigating the concurrent validity of computerized assessment compared with the corresponding paper-and-pencil counterparts.

Results

The results obtained from 83 older adults showed high system acceptance, despite the patients’ low familiarity with technology. The system software was successfully validated. A concurrent validation of the system reported good ability of the digitized tests to retain the same predictive power of the corresponding paper-based tests.

Conclusions

Altogether, the positive results pave the way for the deployment of the system to a nonsupervised environment, thus representing a potential efficacious and ecological solution to support clinicians in the identification of early signs of cognitive decline.

Physical Exercise May Increase Plasma Concentration of High-Density Lipoprotein-Cholesterol in Patients With Alzheimer's Disease

Lifestyle factors have been shown to increase the risk of developing Alzheimer's disease (AD) later in life. Specifically, an unfavorable cholesterol profile, and insulin resistance are associated with increased risk of developing AD. One way to non-pharmacologically affect the levels of plasma lipids is by exercise, which has been shown to be beneficial in cognitively healthy individuals. In this randomized controlled trial y, we therefore aimed to clarify the effect of physical exercise on the lipid profile, insulin and glucose in patients with AD. In addition, we investigated the effect of apolipoproteinE genotype on total cholesterol, high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), and triglycerides (TG) in plasma from patients with AD. Plasma samples from 172 patients who underwent 16 weeks of moderate-to-high intensity exercise (n = 90) or treatment as usual (n = 82) were analyzed change from baseline for the levels of total cholesterol, LDL-C, HDL-C, TG, glucose, and insulin. In addition, we analyzed those from the exercise group who adhered to the protocol with an attendance of 2/3 or more of the exercise session and who followed the protocol of an intensity of 70% of the maximum heart rate. We found a significant increase in plasma HDL-C levels between the "high exercise sub-group" compared to control group. After intervention HDL-C was increased by 4.3% in the high-exercise group, and decreased by 0.7% in the control group, after adjustment for statin use. In conclusion, short term physical activity may be beneficial on the cholesterol profile in patients with AD.

Automatic speech analysis to early detect functional cognitive decline in elderly population

This study aimed at evaluating whether people with a normal cognitive function can be discriminated from subjects with a mild impairment of cognitive function based on a set of acoustic features derived from spontaneous speech. Voice recordings from 90 Italian subjects (age >65 years; group 1: 47 subjects with MMSE>26; group 2: 43 subjects with 20≤ MMSE ≤26) were collected. Voice samples were processed using a MATLAB-based custom software to derive a broad set of known acoustic features. Linear mixed model analyses were performed to select the features able to significantly distinguish between groups. The selected features (% of unvoiced segments, duration of unvoiced segments, % of voice breaks, speech rate, and duration of syllables), alone or in addition to age and years of education, were used to build a learning-based classifier. The leave-one-out cross validation was used for testing and the classifier accuracy was computed. When the voice features were used alone, an overall classification accuracy of 0.73 was achieved. When age and years of education were additionally used, the overall accuracy increased up to 0.80. These performances were lower than the accuracy of 0.86 found in a recent study. However, in that study the classification was based on several tasks, including more cognitive demanding tasks. Our results are encouraging because acoustic features, derived for the first time only from an ecologic continuous speech task, were able to discriminate people with a normal cognitive function from people with a mild cognitive decline. This study poses the basis for the development of a mobile application performing automatic voice analysis on-the-fly during phone calls, which might potentially support the detection of early signs of functional cognitive decline.

Assessing cost-effectiveness of early intervention in Alzheimer's disease: An open-source modeling framework

INTRODUCTION

We develop a framework to model disease progression across Alzheimer's disease (AD) and to assess the cost-effectiveness of future disease-modifying therapies (DMTs) for people with mild cognitive impairment (MCI) due to AD.

METHODS

Using data from the US National Alzheimer's Coordinating Center, we apply survival analysis to estimate transition from predementia to AD dementia and ordered probit regression to estimate transitions across AD dementia stages. We investigate the cost-effectiveness of a hypothetical treatment scenario for people in MCI due to AD.

RESULTS

We present an open-access model-based decision-analytic framework. Assuming a modest DMT treatment effect in MCI, we predict extended life expectancy and a reduction in time with AD dementia.

DISCUSSION

Any future DMT for AD is expected to pose significant economic challenges across all health-care systems, and decision-analytic modeling will be required to assess costs and outcomes. Further developments are needed to inform these health policy considerations.

Estimating Alzheimer's Disease Progression Rates from Normal Cognition Through Mild Cognitive Impairment and Stages of Dementia

BACKGROUND

Alzheimer's Disease (AD) can be conceptualized as a continuum: patients progress from normal cognition to mild cognitive impairment (MCI) due to AD, followed by increasing severity of AD dementia. Prior research has measured transition probabilities among later stages of AD, but not for the complete spectrum.

OBJECTIVE

To estimate annual progression rates across the AD continuum and evaluate the impact of a delay in MCI due to AD on the trajectory of AD dementia and clinical outcomes.

METHODS

Patient-level longitudinal data from the National Alzheimer's Coordinating Center for n=18,103 patients with multiple visits over the age of 65 were used to estimate annual, age-specific transitional probabilities between normal cognition, MCI due to AD, and AD severity states (defined by Clinical Dementia Rating score). Multivariate models predicted the likelihood of death and institutionalization for each health state, conditional on age and time from the previous evaluation. These probabilities were used to populate a transition matrix describing the likelihood of progressing to a particular disease state or death for any given current state and age. Finally, a health state model was developed to estimate the expected effect of a reduction in the risk of transitioning from normal cognition to MCI due to AD on disease progression rates for a cohort of 65-year-old patients over a 35-year time horizon.

RESULTS

Annual transition probabilities to more severe states were 8%, 22%, 25%, 36%, and 16% for normal cognition, MCI due to AD, and mild/moderate/severe AD, respectively, at age 65, and increased as a function of age. Progression rates from normal cognition to MCI due to AD ranged from 4% to 10% annually. Severity of cognitive impairment and age both increased the likelihood of institutionalization and death. For a cohort of 100 patients with normal cognition at age 65, a 20% reduction in the annual progression rate to MCI due to AD avoided 5.7 and 5.6 cases of MCI due to AD and AD, respectively. This reduction led to less time spent in severe AD dementia health states and institutionalized, and increased life expectancy.

CONCLUSION

Transition probabilities from normal cognition through AD severity states are important for understanding patient progression across the AD spectrum. These estimates can be used to evaluate the clinical benefits of reducing progression from normal cognition to MCI due to AD on lifetime health outcomes.

Where are we at with model-based economic evaluations of interventions for dementia? a systematic review and quality assessment

ABSTRACTObjective:To identify, review, and critically appraise model-based economic evaluations of all types of interventions for people with dementia and their carers.

DESIGN

A systematic literature search was undertaken to identify model-based evaluations of dementia interventions. A critical appraisal of included studies was carried out using guidance on good practice methods for decision-analytic models in health technology assessment, with a focus on model structure, data, and model consistency.

SETTING

Interventions for people with dementia and their carers, across prevention, diagnostic, treatment, and disease management.

RESULTS

We identified 67 studies, with 43 evaluating pharmacological products, 19 covering prevention or diagnostic strategies, and 5 studies reporting non-pharmacological interventions. The majority of studies use Markov models with a simple structure to represent dementia symptoms and disease progression. Half of all studies reported taking a societal perspective, with the other half adopting a third-party payer perspective. Most studies follow good practices in modeling, particularly related to the decision problem description, perspective, model structure, and data inputs. Many studies perform poorly in areas related to the reporting of pre-modeling analyses, justifying data inputs, evaluating data quality, considering alternative modeling options, validating models, and assessing uncertainty.

CONCLUSIONS

There is a growing literature on the model-based evaluations of interventions for dementia. The literature predominantly reports on pharmaceutical interventions for Alzheimer's disease, but there is a growing literature for dementia prevention and non-pharmacological interventions. Our findings demonstrate that decision-makers need to critically appraise and understand the model-based evaluations and their limitations to ensure they are used, interpreted, and applied appropriately.

A computerized, self-administered test of verbal episodic memory in elderly patients with mild cognitive impairment and healthy participants: A randomized, crossover, validation study

Introduction

Performance of “Revere”, a novel iPad-administered word-list recall (WLR) test, in quantifying deficits in verbal episodic memory, was evaluated versus examiner-administered Rey Auditory Verbal Learning Test (RAVLT) in patients with mild cognitive impairment and cognitively normal participants.

Methods

Elderly patients with clinically diagnosed mild cognitive impairment (Montreal Cognitive Assessment score 24–27) and cognitively normal (Montreal Cognitive Assessment score ≥28) were administered RAVLT or Revere in a randomized crossover design.

Results

A total of 153/161 participants (Revere/RAVLT n = 75; RAVLT/Revere n = 78) were randomized; 148 (97%) completed study; 121 patients (mean [standard deviation] age: 70.4 [7.84] years) were included for analysis. Word-list recall scores (8 trials) were comparable between Revere and RAVLT (Pearson's correlation coefficients: 0.12–0.70; least square mean difference [Revere-RAVLT]: −0.84 [90% CI, −1.15; −0.54]). Model factor estimates indicated trial (P < .001), period (P < .001) and evaluation sequence (P = .038) as significant factors. Learning over trials index and serial position effects were comparable.

Discussion

Participants' verbal recall performance on Revere and RAVLT were equivalent.

Using Cerebrospinal Fluid Biomarker Testing to Target Treatment to Patients with Mild Cognitive Impairment: A Cost-Effectiveness Analysis

OBJECTIVE

Cerebrospinal fluid (CSF) biomarkers are shown to facilitate a risk identification of patients with mild cognitive impairment (MCI) into different risk levels of progression to Alzheimer's disease (AD). Knowing a patient's risk level provides an opportunity for earlier interventions, which could result in potential greater benefits. We assessed the cost effectiveness of the use of CSF biomarkers in MCI patients where the treatment decision was based on patients' risk level.

METHODS

We developed a state-transition model to project lifetime quality-adjusted life-years (QALYs) and costs for a cohort of 65-year-old MCI patients from a US societal perspective. We compared four test-and-treat strategies where the decision to treat was based on a patient's risk level (low, intermediate, high) of progressing to AD with two strategies without testing, one where no patients were treated during the MCI phase and in the other all patients were treated. We performed deterministic and probabilistic sensitivity analyses to evaluate parameter uncertainty.

RESULTS

Testing and treating low-risk MCI patients was the most cost-effective strategy with an incremental cost-effectiveness ratio (ICER) of US$37,700 per QALY. Our results were most sensitive to the level of treatment effectiveness for patients with mild AD and for MCI patients. Moreover, the ICERs for this strategy at the 2.5th and 97.5th percentiles were US$18,900 and US$50,100 per QALY, respectively.

CONCLUSION

Based on the best available evidence regarding the treatment effectiveness for MCI, this study suggests the potential value of performing CSF biomarker testing for early targeted treatments among MCI patients with a narrow range for the ICER.

The development of a stochastic mathematical model of Alzheimer's disease to help improve the design of clinical trials of potential treatments

Alzheimer's disease (AD) is a neurodegenerative disorder characterised by a slow progressive deterioration of cognitive capacity. Drugs are urgently needed for the treatment of AD and unfortunately almost all clinical trials of AD drug candidates have failed or been discontinued to date. Mathematical, computational and statistical tools can be employed in the construction of clinical trial simulators to assist in the improvement of trial design and enhance the chances of success of potential new therapies. Based on the analysis of a set of clinical data provided by the Alzheimer's Disease Neuroimaging Initiative (ADNI) we developed a simple stochastic mathematical model to simulate the development and progression of Alzheimer's in a longitudinal cohort study. We show how this modelling framework could be used to assess the effect and the chances of success of hypothetical treatments that are administered at different stages and delay disease development. We demonstrate that the detection of the true efficacy of an AD treatment can be very challenging, even if the treatment is highly effective. An important reason behind the inability to detect signals of efficacy in a clinical trial in this therapy area could be the high between- and within-individual variability in the measurement of diagnostic markers and endpoints, which consequently results in the misdiagnosis of an individual's disease state.

Discrimination between patients with mild Alzheimer's disease and healthy subjects based on cerebral blood flow images of the lateral views in xenon-enhanced computed tomography

BACKGROUND

Quantitative cerebral blood flow (CBF) measurement is expected to help early detection of functional abnormalities caused by Alzheimer's disease (AD) and enable AD treatment to begin in its early stages. Recently, a technique of layer analysis was reported that allowed CBF to be analyzed from the outer to inner layers of the brain. The aim of this work was to develop methods for discriminating between patients with mild AD and healthy subjects based on CBF images of the lateral views created with the layer analysis technique in xenon-enhanced computed tomography.

METHODS

Xenon-enhanced computed tomography using a wide-volume CT was performed on 17 patients with mild AD aged 75 or older and on 15 healthy age-matched volunteers. For each subject, we created CBF images of the right and left lateral views with a depth of 10-15 mm from the surface of the brain. Ten circular regions of interest (ROI) were placed on each image, and CBF was calculated for each ROI. We determined discriminant ROI that had CBF that could be used to differentiate between the AD and volunteer groups. AD patients' CBF range (mean - SD to mean + SD) and healthy volunteers' CBF range (mean - SD to mean + SD) were obtained for each ROI. Receiver-operator curves were created to identify patients with AD for each of the discriminant ROI and for the AD patients' and healthy volunteers' CBF ranges.

RESULTS

We selected an ROI on both the right and left temporal lobes as the discriminant ROI. Areas under the receiver-operator curve were 93.3% using the ROI on the right temporal lobe, 95.3% using the ROI on the left temporal lobe, and 92.4% using the AD patients' and healthy volunteers' CBF ranges.

CONCLUSIONS

We could effectively discriminate between patients with mild AD and healthy subjects using ROI placed on CBF images of the lateral views in xenon-enhanced computed tomography.

Digitally translated Self-Administered Gerocognitive Examination (eSAGE): relationship with its validated paper version, neuropsychological evaluations, and clinical assessments

BACKGROUND

The original paper Self-Administered Gerocognitive Examination (SAGE) is a valid and reliable cognitive assessment tool used to identify individuals with mild cognitive impairment (MCI) or early dementia. We evaluated identical test questions in a digital format (eSAGE) made for tablet use with the goals of calibrating it against SAGE and establishing its association with other neuropsychological tests and clinical assessments of cognitive impairment.

METHODS

Subjects aged 50 and over who had taken SAGE were recruited from community and clinic settings. Subjects were randomly selected to participate in a clinical evaluation including neuropsychological evaluations. SAGE and eSAGE were administered using a crossover design. Subjects were identified as dementia, MCI, or normal based on standard clinical criteria. Associations were investigated using Spearman correlations, linear regression, and sensitivity and specificity measures.

RESULTS

Of the 426 subjects screened, 66 completed the evaluation. eSAGE score correlation to a battery of neuropsychological tests was 0.73 (p < 0.0001) with no significant difference between the paper and digital format. Spearman correlation of SAGE versus eSAGE was 0.88 (p < 0.0001), and they are related by the formula: eSAGE score = -1.05 + 0.99 × SAGE score. Since the slope is very close to 1 (p = 0.86) there is strong evidence that the scaling is identical between eSAGE and SAGE, with no scale bias. Overall, eSAGE scores are lower by an average of 1.21 and the decrease is statistically significant (p < 0.0001). For those subjects familiar with smartphones or tablets (one measure of digital proficiency), eSAGE scores are lower by an average of 0.83 points (p = 0.029). With a score 16 and higher being classified as normal, eSAGE had 90% specificity and 71% sensitivity in detecting those with cognitive impairment from normal subjects.

CONCLUSIONS

Tablet-based eSAGE shows a strong association with the validated paper SAGE and a neuropsychological battery. It shows no scale bias compared to SAGE. Both have the advantage of self-administration, brevity, four interchangeable forms, and high sensitivity and specificity in detecting cognitive impairment from normal subjects. Their potential widespread availability will be a major factor in overcoming the many obstacles in identifying early cognitive changes.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT02544074 . Registered on 18 March 2015.

Timely Diagnosis for Alzheimer's Disease: A Literature Review on Benefits and Challenges

Background:

Timely diagnosis of Alzheimer’s disease (AD) refers to a diagnosis at the stage when patients come to the attention of clinicians because of concerns about changes in cognition, behavior, or functioning and can be still free of dementia and functionally independent.

Objectives:

To comprehensively review existing scientific evidence on the benefits and potential challenges of making a timely diagnosis of AD.

Methods:

Relevant studies were identified by searching electronic databases (Medline, Embase) and bibliographies for studies published in English between 1 January 2000 and 2 June 2014 on the consequences of a timely diagnosis of AD.

Results:

Nine studies were identified that investigated the consequences of diagnosing AD at the initial stages; none were specifically focused on prodromal AD. A timely diagnosis potentially offers the opportunities of early intervention, implementation of coordinated care plans, better management of symptoms, patient safety, cost savings, and postponement of institutionalization. Barriers to making a timely diagnosis include stigma, suicide risk, lack of training, diagnostic uncertainty, shortage of specialized diagnostic services, and the reluctance of healthcare providers to make a diagnosis when no effective disease-modifying options are available.

Conclusions:

Despite its potential benefits, few published studies have explored the advantages or risks of a timely diagnosis of AD. In light of the cultural shift toward diagnosis at the initial stage of the disease continuum, when the patient does not yet have dementia, more investigations are needed to evaluate the benefits and address the barriers that may impede making a timely AD diagnosis.

B-vitamins are potentially a cost-effective population health strategy to tackle dementia: Too good to be true?

Introduction

To respond to the threat of dementia to public health and the economy, we need to prioritize research resources on strategies that would be the most effective. In relation to the prevention of dementia, this article considers whether lowering plasma homocysteine by B-vitamin supplementation is one of the top priority and cost-effective treatments.

Method

A decision model was constructed to calculate the lifetime costs and quality-adjusted life years (QALYs) of providing B-vitamin treatment to people in the United Kingdom over 60 years with high levels (>13 μmol/L) of plasma homocysteine, which was compared to the lifetime costs and outcomes of not providing them with the treatment.

Results

Treatment with B-vitamins will save £60,021 per QALY gained and so is highly cost-effective.

Discussion

We anticipate that this provocative finding will be debated by scientists, clinicians, and policy makers and eventually be tested in future clinical trials.

•

We need to prioritize resources on strategies to prevent dementia.

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Treatment with B-vitamins at an early stage appears to be highly cost-effective.

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This provocative finding should be debated and tested.

Nasal Application of the Galantamine Pro-drug Memogain Slows Down Plaque Deposition and Ameliorates Behavior in 5X Familial Alzheimer's Disease Mice

The plant alkaloid galantamine is an established symptomatic drug treatment for Alzheimer's disease (AD), providing cognitive and global relief in human patients. However, as an acetylcholinesterase inhibitor, gastrointestinal side effects limit the dosage and duration of treatment. Memogain (Gln-1062), a pro-drug, liberates galantamine on cleavage by a carboxyesterase in the brain. The possibility to deliver Memogain intranasally may further circumvent side effects, allowing higher dosing compared to galantamine. In this study, the 5X Familial Alzheimer's Disease (5XFAD) mouse model was used to investigate the effect of chronic Memogain treatment on behavior and amyloid-β (Aβ) plaque deposition in the brain. Chronic intranasal dosage of 6 mg/kg body weight twice daily was tolerated well, whereas the double dose caused body weight loss in males and was less effective in some behavioral tests. 8 weeks of chronic treatment resulted in improved performance in behavioral tests, such as open field and light-dark avoidance, and in fear conditioning already at mildly affected stages at the age of 18 weeks compared to untreated controls. Furthermore, after treatment a significantly lower plaque density in the brain, i.e., in the entorhinal cortex (reduction 20% females, 40% males) and the hippocampus (19% females, 31% males) at the age of 18 weeks was observed. These results show that nasal application of Memogain effectively delivers the drug to the brain with the potential to retard plaque deposition and improve behavioral symptoms in AD similar to the approved galantamine.

The reliability and validity of the informant AD8 by comparison with a series of cognitive assessment tools in primary healthcare

BACKGROUND

The validity and reliability of the informant AD8 in primary healthcare has not been established. Therefore, the present study examined the validity and reliability of the informant AD8 in government subsidized primary healthcare centers in Singapore.

METHODS

Eligible patients (≥60 years old) were recruited from primary healthcare centers and their informants received the AD8. Patient-informant dyads who agreed for further cognitive assessments received the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Clinical Dementia Rating (CDR), and a locally validated formal neuropsychological battery at a research center in a tertiary hospital.

RESULTS

1,082 informants completed AD8 assessment at two primary healthcare centers. Of these, 309 patients-informant dyads were further assessed, of whom 243 (78.6%) were CDR = 0; 22 (7.1%) were CDR = 0.5; and 44 (14.2%) were CDR≥1. The mean administration time of the informant AD8 was 2.3 ± 1.0 minutes. The informant AD8 demonstrated good internal consistency (Cronbach's α = 0.85); inter-rater reliability (Intraclass Correlation Coefficient (ICC) = 0.85); and test-retest reliability (weighted κ = 0.80). Concurrent validity, as measured by the correlation between total AD8 scores and CDR global (R = 0.65, p < 0.001), CDR sum of boxes (R = 0.60, p < 0.001), MMSE (R = -0.39, p < 0.001), MoCA (R = -0.41, p < 0.001), as well as the formal neuropsychological battery (R = -0.46, p < 0.001), was good and consistent with previous studies. Construct validity, as measured by convergent validity (R ≥ 0.4) between individual items of AD8 with CDR and neuropsychological domains was acceptable.

CONCLUSIONS

The informant AD8 demonstrated good concurrent and construct validity and is a reliable measure to detect cognitive dysfunction in primary healthcare.

Risk Factors of Cognitive Impairment and Brief Cognitive Tests to Predict Cognitive Performance Determined by a Formal Neuropsychological Evaluation of Primary Health Care Patients

BACKGROUND

Case finding for cognitive impairment (CI) is recommended for all persons older than 70 years.

OBJECTIVE

The present study identified additional risk factors of CI so as to operationalize a composite total risk score (TRS) for case finding. We then examined the additive effect of the TRS and brief cognitive tests to improve the diagnosis of CI.

METHODS

The study was conducted in 2 primary health care centers in Singapore. A total of 1082 individuals (≥60 years old) were assessed for sociodemographic risk factors and their informants were administered the AD8; 309 individuals who agreed for further cognitive assessments completed the Mini-mental state examination (MMSE) and Montreal Cognitive Assessment (MoCA), and a neuropsychological battery at a research center. Primary health care medical records were accessed for data on vascular risk factors.

RESULTS

Of the 309 individuals who underwent neuropsychological evaluation, 4 were excluded due to missing medical data; 167 (54.8%) individuals had CI and 138 (45.2%) had No Cognitive Impairment (NCI). The β coefficients were standardized to calculate risk scores. CI was significantly predicted by age >70 years (odds ratio [OR] 5.99; score = 3), diabetes (OR 3.36; score = 2), stroke (OR 2.70; score = 1), female gender (OR 2.02; score = 1) and individual cognitive complaints (SCC) (OR 1.95; score = 1). The TRS had an optimal cutoff of ≥3 and explained considerable variance in global cognitive composite Z-scores (R(2) = 0.41, P < .001). The MoCA explained substantial variance compared with the MMSE and AD8 (R(2) changes of 0.474, 0.422, and 0.157, P < .001, respectively).

CONCLUSION

The TRS is a reasonable measure to predict individuals at risk of CI. The addition of the MoCA, in persons with positive TRS scores, is a useful approach to improve the diagnosis of CI for at-risk patients attending primary health care.

Direct medical costs and source of cost differences across the spectrum of cognitive decline: a population-based study

BACKGROUND

Objective cost estimates and source of cost differences are needed across the spectrum of cognition, including cognitively normal (CN), mild cognitive impairment (MCI), newly discovered dementia, and prevalent dementia.

METHODS

Subjects were a subset of the Mayo Clinic Study of Aging stratified-random sampling of Olmsted County, MN, residents aged 70 to 89 years. A neurologist reviewed provider-linked medical records to identify prevalent dementia (review date = index). Remaining subjects were invited to participate in prospective clinical/neuropsychological assessments; participants were categorized as CN, MCI, or newly discovered dementia (assessment date = index). Costs for medical services/procedures 1-year pre-index (excluding indirect and long-term care costs) were estimated using line-item provider-linked administrative data. We estimated contributions of care-delivery site and comorbid conditions (including and excluding neuropsychiatric diagnoses) to between-category cost differences.

RESULTS

Annual mean medical costs for CN, MCI, newly discovered dementia, and prevalent dementia were $6042, $6784, $9431, $11,678, respectively. Hospital inpatient costs contributed 70% of total costs for prevalent dementia and accounted for differences between CN and both prevalent and newly discovered dementia. Ambulatory costs accounted for differences between CN and MCI. Age-, sex-, education-adjusted differences reached significance for CN versus newly discovered and prevalent dementia and for MCI versus prevalent dementia. After considering all comorbid diagnoses, between-category differences were reduced (e.g., prevalent dementia minus MCI (from $4842 to $3575); newly discovered dementia minus CN (from $3578 to $711)). Following the exclusion of neuropsychiatric diagnoses from comorbidity adjustment, between-category differences tended to revert to greater differences.

CONCLUSIONS

Cost estimates did not differ significantly between CN and MCI. Substantial differences between MCI and prevalent dementia reflected high inpatient costs for dementia and appear partly related to co-occurring mental disorders. Such comparisons can help inform models aimed at identifying where, when, and for which individuals proposed interventions might be cost-effective.

Monitoring the early signs of cognitive decline in elderly by computer games: an MRI study

Background

It is anticipated that current and future preventive therapies will likely be more effective in the early stages of dementia, when everyday functioning is not affected. Accordingly the early identification of people at risk is particularly important. In most cases, when subjects visit an expert and are examined using neuropsychological tests, the disease has already been developed. Contrary to this cognitive games are played by healthy, well functioning elderly people, subjects who should be monitored for early signs. Further advantages of cognitive games are their accessibility and their cost-effectiveness.

Purpose

The aim of the investigation was to show that computer games can help to identify those who are at risk. In order to validate games analysis was completed which measured the correlations between results of the 'Find the Pairs' memory game and the volumes of the temporal brain regions previously found to be good predictors of later cognitive decline.

Participants and Methods

34 healthy elderly subjects were enrolled in the study. The volume of the cerebral structures was measured by MRI. Cortical reconstruction and volumetric segmentation were performed by Freesurfer.

Results

There was a correlation between the number of attempts and the time required to complete the memory game and the volume of the entorhinal cortex, the temporal pole, and the hippocampus. There was also a correlation between the results of the Paired Associates Learning (PAL) test and the memory game.

Conclusions

The results gathered support the initial hypothesis that healthy elderly subjects achieving lower scores in the memory game have increased level of atrophy in the temporal brain structures and showed a decreased performance in the PAL test. Based on these results it can be concluded that memory games may be useful in early screening for cognitive decline.

Fitting the epidemiology and neuropathology of the early stages of Alzheimer's disease to prevent dementia

Introduction

Recent research on biomarkers has made possible the diagnosis of pre-dementia and even preclinical Alzheimer’s disease (AD), thus providing the ideal context for prevention. The aim of this study was to investigate the epidemiology of the early stages of AD by fitting neuropathologic and epidemiological data to assess the feasibility of prevention programs.

Methods

The study addressed primarily the construction of a discrete event simulation model of the stages of dementia. Age was included in the mathematical functions to combine the two competitive risks that determine the epidemiology of AD, that is, time to onset of dementia and time until death by other causes. Subsequently, this model was calibrated to reproduce the prevalence of pathological findings associated with AD. The beginning of the preclinical stage was taken to coincide with Thal phase 1 deposition of amyloid-beta. The duration of the prodromal stage, marked by mild cognitive impairment, was based on a 10% annual conversion rate from this level of impairment to dementia. The validation of prevalence figures also permitted estimation of the incidence and duration of preclinical and prodromal stages.

Results

In Spain, half of the nearly 10 million people aged more than 60 years are in the early stages of AD; 35.9% are in a preclinical stage, and up to 14.2% are in a prodromal stage. However, dementia will develop in only 38% of this population. The weighted mean time to dementia was 22.0 years from the start of Thal phase 1 and 9.0 years from the start of phase 2. Results of simulation models showed a lack of correlation between clinical and pathological classifications.

Conclusions

These findings raise questions about the feasibility of drug-based prevention strategies. Currently, screening programs with biomarkers in the early stages of AD cannot be applied to the half of the general population older than 60 years. Hence, intensive research is needed regarding risk factors, so that more affordable strategies may be planned. More efficient criteria are also needed to select those subjects with mild cognitive impairment who have an increased probability of positive screening for biomarkers (prodromal stage).

Electronic supplementary material

The online version of this article (doi:10.1186/s13195-014-0079-9) contains supplementary material, which is available to authorized users.

Factors associated with cognitive evaluations in the United States

OBJECTIVE

We aimed to explore factors associated with clinical evaluations for cognitive impairment among older residents of the United States.

METHODS

Two hundred ninety-seven of 845 subjects in the Aging, Demographics, and Memory Study (ADAMS), a nationally representative community-based cohort study, met criteria for dementia after a detailed in-person study examination. Informants for these subjects reported whether or not they had ever received a clinical cognitive evaluation outside of the context of ADAMS. Among subjects with dementia, we evaluated demographic, socioeconomic, and clinical factors associated with an informant-reported clinical cognitive evaluation using bivariate analyses and multivariable logistic regression.

RESULTS

Of the 297 participants with dementia in ADAMS, 55.2% (representing about 1.8 million elderly Americans in 2002) reported no history of a clinical cognitive evaluation by a physician. In a multivariable logistic regression model (n = 297) controlling for demographics, physical function measures, and dementia severity, marital status (odds ratio for currently married: 2.63 [95% confidence interval: 1.10-6.35]) was the only significant independent predictor of receiving a clinical cognitive evaluation among subjects with study-confirmed dementia.

CONCLUSIONS

Many elderly individuals with dementia do not receive clinical cognitive evaluations. The likelihood of receiving a clinical cognitive evaluation in elderly individuals with dementia associates with certain patient-specific factors, particularly severity of cognitive impairment and current marital status.

Benzoate, a D-amino acid oxidase inhibitor, for the treatment of early-phase Alzheimer disease: a randomized, double-blind, placebo-controlled trial

BACKGROUND

N-methyl-D-aspartate receptor (NMDAR)-mediated neurotransmission is vital for learning and memory. Hypofunction of NMDAR has been reported to play a role in the pathophysiology of Alzheimer disease (AD), particularly in the early phase. Enhancing NMDAR activation might be a novel treatment approach. One of the methods to enhance NMDAR activity is to raise the levels of NMDA coagonists by blocking their metabolism. This study examined the efficacy and safety of sodium benzoate, a D-amino acid oxidase inhibitor, for the treatment of amnestic mild cognitive impairment and mild AD.

METHODS

We conducted a randomized, double-blind, placebo-controlled trial in four major medical centers in Taiwan. Sixty patients with amnestic mild cognitive impairment or mild AD were treated with 250-750 mg/day of sodium benzoate or placebo for 24 weeks. Alzheimer's Disease Assessment Scale-cognitive subscale (the primary outcome) and global function (assessed by Clinician Interview Based Impression of Change plus Caregiver Input) were measured every 8 weeks. Additional cognition composite was measured at baseline and endpoint.

RESULTS

Sodium benzoate produced a better improvement than placebo in Alzheimer's Disease Assessment Scale-cognitive subscale (p = .0021, .0116, and .0031 at week 16, week 24, and endpoint, respectively), additional cognition composite (p = .007 at endpoint) and Clinician Interview Based Impression of Change plus Caregiver Input (p = .015, .016, and .012 at week 16, week 24, and endpoint, respectively). Sodium benzoate was well-tolerated without evident side-effects.

CONCLUSIONS

Sodium benzoate substantially improved cognitive and overall functions in patients with early-phase AD. The preliminary results show promise for D-amino acid oxidase inhibition as a novel approach for early dementing processes.

Value-based assessment of pharmacodiagnostic testing from early stage development to real-world use

Disease etiology may be regarded as a consequence of both genotypic and biochemical phenomena, which impact individual patients in different ways. Disease prognosis, beneficial treatment response, and susceptibility to adverse drug effects are often intimately tied to individual biology. Clinical and genetic biomarkers applied individually or in concert are increasingly used to stratify patient populations in terms of prognosis, therapeutic benefit, or safety. As a result, clinical trialists are challenged to design studies that reflect these determinants of outcome, to optimize the patient's eventual clinical course both in the trial and in actual practice. These designs are informed both by preclinical studies and by real-world research that can establish proof of concept for a novel biomarker and provide a basic understanding of the relationship between biomarker and clinical outcome. As clinical and real-world studies unfold, a deeper understanding of the nature of the biomarker and its potential uses in drug development is gained. Specifically, one can eventually define the biomarker as prognostic (i.e., predicts disease progression), predictive (predicts treatment response or adverse outcome(s)), or exhibiting both prognostic and predictive properties. One must further validate the performance of these emerging biomarkers, again in both the trial and real-world environments. The eventual adoption of the biomarker as a useful pharmacodiagnostic test is premised upon this early translational research. In this article, the development and validation of predictive and prognostic biomarkers is discussed by using selected examples that highlight factors contributing to the valuation of biomarkers and their application to personalized medicine in the real world.