Dataset Information

A classification algorithm for predicting progression from normal cognition to mild cognitive impairment across five cohorts: The preclinical AD consortium.

ABSTRACT:

Introduction

We established a method for diagnostic harmonization across multiple studies of preclinical Alzheimer's disease and validated the method by examining its relationship with clinical status and cognition.

Methods

Cognitive and clinical data were used from five studies (N = 1746). Consensus diagnoses established in each study used criteria to identify progressors from normal cognition to mild cognitive impairment. Correspondence was evaluated between these consensus diagnoses and three algorithmic classifications based on (1) objective cognitive impairment in 2+ tests only; (2) a Clinical Dementia Rating (CDR) of ≥0.5 only; and (3) both. Associations between baseline cognitive performance and cognitive change were each tested in relation to progression to algorithm-based classifications.

Results

In each study, an algorithmic classification based on both cognitive testing cutoff scores and a CDR ≥0.5 provided optimal balance of sensitivity and specificity (areas under the curve: 0.85-0.95). Over an average 6.6 years of follow-up (up to 28 years), N = 186 initially cognitively normal participants aged on average 64 years at baseline progressed (incidence rate: 15.3 people/1000 person-years). Baseline cognitive scores and cognitive change were associated with future diagnostic status using this algorithmic classification.

Discussion

Both cognitive tests and CDR ratings can be combined across multiple studies to obtain a reliable algorithmic classification with high specificity and sensitivity. This approach may be applicable to large cohort studies and to clinical trials focused on preclinical Alzheimer's disease because it provides an alternative to implementation of a time-consuming adjudication panel.

SUBMITTER: Gross AL

PROVIDER: S-EPMC5476965 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Recent evidence indicates that measures from cerebrospinal fluid, MRI scans and cognitive testing obtained from cognitively normal individuals can be used to predict likelihood of progression to mild cognitive impairment several years later, for groups of individuals. However, it remains unclear whether these measures are useful for predicting likelihood of progression for an individual. The increasing focus on early intervention in clinical trials for Alzheimer's disease emphasizes the importance of improving the ability to identify which cognitively normal individuals are more likely to progress over time, thus allowing researchers to efficiently screen participants, as well as determine the efficacy of any treatment intervention. The goal of this study was to determine which measures, obtained when individuals were cognitively normal, predict on an individual basis, the onset of clinical symptoms associated with a diagnosis of mild cognitive impairment due to Alzheimer's disease. Cognitively normal participants (n = 224, mean baseline age = 57 years) were evaluated with a range of measures, including: cerebrospinal fluid amyloid-? and phosphorylated-tau, hippocampal and entorhinal cortex volume, cognitive tests scores and APOE genotype. They were then followed to determine which individuals developed mild cognitive impairment over time (mean follow-up = 11 years). The primary outcome was progression from normal cognition to the onset of clinical symptoms of mild cognitive impairment due to Alzheimer's disease at 5 years post-baseline. Time-dependent receiver operating characteristic analyses examined the sensitivity and specificity of individual measures, and combinations of measures, as predictors of the outcome. Six measures, in combination, were the most parsimonious predictors of transition to mild cognitive impairment 5 years after baseline (area under the curve = 0.85; sensitivity = 0.80, specificity = 0.75). The addition of variables from each domain significantly improved the accuracy of prediction. The incremental accuracy of prediction achieved by adding individual measures or sets of measures successively to one another was also examined, as might be done when enrolling individuals in a clinical trial. The results indicate that biomarkers obtained when individuals are cognitively normal can be used to predict which individuals are likely to develop clinical symptoms at 5 years post-baseline. As a number of the measures included in the study could also be used as subject selection criteria in a clinical trial, the findings also provide information about measures that would be useful for screening in a clinical trial aimed at individuals with preclinical Alzheimer's disease.

Project description: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.

Project description:BackgroundAlthough previous studies have revealed many factors related to mild cognitive impairment (MCI) reversion, information about reversible factors related MCI reversion is limited, impeding the development of intervention strategies. The aim of the present study was to examine whether reversible factors such as lifestyle activities are associated with MCI reversion in elderly individuals using the National Center for Geriatrics and Gerontology-Study of Geriatric Syndromes database. A total of 396 community-living older adults (age ≥ 65 years) participated in the study. They were classified as reverters or non-reverters from mild cognitive impairment to normal cognition. We assessed lifestyle activities, potential confounding factors of cognitive decline, and reversion of mild cognitive impairment.ResultsIn a completed data set of 396 participants, 202 participants (51.0%) reverted from MCI to normal cognition. The reversion rate in participants for whom we imputed data was 34.3%. In the imputed group, a logistic regression model showed that the odds ratios (ORs) for reversion were significantly higher in participants who drove a car (OR 1.50, 95% confidence interval (CI) 1.41-1.60), used a map to travel to unfamiliar places (OR 1.12, 95% CI 1.06-1.18), read books or newspapers (OR 1.54, 95% CI 1.37-1.73), took cultural classes (OR 1.10, 95% CI 1.04-1.15), attended meetings in the community (OR 1.22, 95% CI 1.16-1.28), participated in hobbies or sports activities (OR 1.09, 95% CI 1.03-1.16), and engaged in fieldwork or gardening (OR 1.14, 95% CI 1.08-1.21). The imputed sample showed that non-reverters were more likely to discontinue fieldwork or gardening (11.0% vs. 6.1%) than reverters during the follow-up period.ConclusionsSpecific lifestyle activities may play important roles in MCI reversion in older adults. The longitudinal data indicate that it is reasonable to recommend that individuals continue to engage in fieldwork or gardening to increase their chance of recovery from MCI.

Project description:BackgroundLeukotriene receptor antagonists (LTRAs) alleviate Alzheimer's disease (AD) pathology and improve cognition in animal models; however, clinical evidence is limited. This study aimed to explore the associations between the use of LTRAs (montelukast or zafirlukast) and cognitive performance in people with normal cognition, mild cognitive impairment (MCI), or AD dementia. We hypothesized that LTRA use would be associated with better cognitive performance over time.MethodsThis longitudinal observational study used data from the National Alzheimer's Coordinating Center. Within groups of participants with normal cognition, MCI, or AD dementia, LTRA users were matched 1:3 to non-users using propensity score matching. Cognitive domains including immediate and delayed memory (Wechsler Memory Scale Revised-Logical Memory IA and IIA), psychomotor processing speed (Digit Symbol Substitution Test), and language (animal naming, vegetable naming, and Boston Naming Test) were compared between users and non-users in mixed-effects linear or Poisson regression models.ResultsIn AD dementia, LTRA use was associated with a slower decline in psychomotor processing speed, as measured by the Digit Symbol Substitution Test (Β = 1.466 [0.253, 2.678] symbols/year, n = 442), and language, as measured by animal naming (Β = 0.541 [0.215, 0.866] animals/year, n = 566), vegetable naming (B = 0.309 [0.056, 0.561] vegetables/year, n = 565), and the Boston Naming Test (B = 0.529 [0.005, 1.053] items/year, n = 561). Effect sizes were small but persisted after controlling for a 10% false discovery rate. LTRA use was not associated with changes in memory performance in AD, nor was it associated with changes in cognitive performance in people with normal cognition or MCI. In a post hoc analysis, LTRA use was associated with a slower decline in clinical progression in MCI (B = -0.200 [-0.380, -0.019] points/year, n = 800) and AD dementia (B = -0.321 [-0.597, -0.046] points/year, n = 604) as measured by CDR Sum of Boxes.ConclusionsThe use of LTRAs was associated with preserved function in non-amnestic cognitive domains in AD dementia. The role of leukotrienes and their receptors in cognitive decline warrants further investigation and the leukotriene pathway may represent a target for AD treatment.