Adjusting for mortality when identifying risk factors for transitions to mild cognitive impairment and dementia

Health care utilization and costs in the years preceding dementia identification

INTRODUCTION

There is evidence that health care utilization increases after incident dementia, particularly after dementia diagnosis and toward the end of life; however, less is known about utilization in the years before dementia identification.

METHODS

In this retrospective cohort study we obtained data on n = 5547 beneficiaries from the Health and Retirement Study (HRS)-Medicare linked sample (n = 1241 with and n = 4306 without dementia) to compare longitudinal trends in health care costs and utilization in the 6 years preceding dementia identification relative to a confounder-balanced reference group without dementia.

RESULTS

We found that persons with dementia had a greater prevalence of outpatient emergency department (ED), inpatient hospital, skilled nursing, and home health use, and total health care costs in the years preceding dementia identification compared to their similar counterparts without dementia across a comparable timespan in later life.

CONCLUSIONS

This study provides evidence to suggest greater healthcare burden may exist well before clinical manifestation and identification of dementia.

HIGHLIGHTS

Several studies have documented the tremendous healthcare-related costs of living with dementia, particularly toward the end of life. Dementia is a progressive neurodegenerative disease, which, for some, includes a prolonged pre-clinical phase. However, health services research to date has seldom considered the time before incident dementia. This study documents that health care utilization and costs are significantly elevated in the years before incident dementia relative to a demographically-similar comparison group without dementia.

The Preventing Alzheimer's with Cognitive Training (PACT) randomized clinical trial

BACKGROUND

To address the rising prevalence of Alzheimer's disease and related dementias, effective interventions that can be widely disseminated are warranted. The Preventing Alzheimer's with Cognitive Training study (PACT) investigates a commercially available computerized cognitive training program targeting improved Useful Field of View Training (UFOVT) performance. The primary goal is to test the effectiveness of UFOVT to reduce incidence of clinically defined mild cognitive impairment (MCI) or dementia with a secondary objective to examine if effects are moderated by plasma β-amyloid level or apolipoprotein E e4 (APOE e4) allele status.

METHODS/DESIGN

This multisite study utilizes a randomized, controlled experimental design with blinded assessors and investigators. Individuals who are 65 years of age and older are recruited from the community. Eligible participants who demonstrate intact cognitive status (Montreal Cognitive Assessment score > 25) are randomized and asked to complete 45 sessions of either a commercially available computerized-cognitive training program (UFOVT) or computerized games across 2.5 years. After three years, participants are screened for cognitive decline. For those demonstrating decline or who are part of a random subsample, a comprehensive neuropsychological assessment is completed. Those who perform below a pre-specified level are asked to complete a clinical evaluation, including an MRI, to ascertain clinical diagnosis of normal cognition, MCI, or dementia. Participants are asked to provide blood samples for analyses of Alzheimer's disease related biomarkers.

DISCUSSION

The PACT study addresses the rapidly increasing prevalence of dementia. Computerized cognitive training may provide a non-pharmaceutical option for reducing incidence of MCI or dementia to improve public health.

REGISTRATION

The PACT study is registered at http://Clinicaltrials.govNCT03848312.

Mortality rate of high cardiovascular risk patients with mild cognitive impairment

People with mild cognitive impairment (MCI) may be at higher risk of death than normal aging ones. On the other hand, patients with cardiovascular risk factors are also with higher risk of death. It may be logical to question then if the combination of MCI and cardio-vascular risk factors (in most cases arterial hypertension) can lead to higher mortality rate than expected both for high cardio-vascular risk patients and for the general population. This hypothesis is important in the light of effective early screening and prophylaxis. The general death rate of patients with very high-cardio-vascular-risk was compared in the subgroups of normal cognition and MCI. We used MMSE and MoCA (reassessment 6 months apart), Geriatric Depression scale and 4-point version of the scale for evaluating the performance in instrumental activities of daily living (4-IADL) in 249 patients. The patients also had laboratory testing, ambulatory blood pressure monitoring, ECG and echocardiography. The general mortality rate of this very high cardio-vascular risk group was assessed 8–10 years afterwards and also compared to the general national death rate published for the corresponding period from the National Social Security Institute of Bulgaria. We registered significantly higher general death rate in patients with MCI and very high cardio-vascular risk as compared to the group without MCI. The logistic regression analysis attributed approximately 14.6% of the mortality rate in this high-risk group to MCI. The major cardio-vascular risk factor was arterial hypertension—with 63.85% of the patients with home blood pressure values not in the target range at the initial cognitive screening. During the neuropsychological reevaluation 56.43% were with poor control despite the multidrug antihypertensive regimen. It is known that MCI is correlated with cardiovascular risk factors with the leading role of arterial hypertension. We found that the combination of MCI and arterial hypertension can lead to higher mortality rate than in the general aging population. This has important clinical implications for the everyday practice.

The Relationship Between Low-Density Lipoprotein Cholesterol and Progression of Mild Cognitive Impairment: The Influence of rs6859 in PVRL2

Background: Genome-wide association studies have identified many Alzheimer's disease (AD) genetic-risk single nucleotide polymorphisms (SNPs) and indicated the important role of the cholesterol/lipid metabolism pathway in AD pathogenesis. This study aims to investigate the effects of cholesterol and genetic risk factors on progression of mild cognitive impairment (MCI) to AD. Methods: We prospectively followed 316 MCI participants aged ≥50 years with a baseline cholesterol profile and SNP genotyping data for 4.5 years on average in a sub-cohort of the Shanghai Aging Study. Total cholesterol, low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol in serum were measured at baseline. SNP genotyping was performed using a MassARRAY system. At follow-up, consensus diagnosis of incident dementia and AD were established based on medical, neurological, and neuropsychological examinations. Cox regression models were used to assess the association of cholesterol and SNP with incident AD. Results: The AG/AA genotypes of PVRL2 rs6859 were significantly associated with increased incident AD in MCI participants, compared with GG genotype (adjusted hazard ratio [HR] 2.75, 95% confidence interval [CI] 1.32-5.76, p = .007, false discovery rate-adjusted p = .030). In PVRL2 rs6859 AG/AA carriers, each-1 mmol/L higher level of LDL-C was significantly associated with a 48% decreased risk of AD (adjusted HR 0.52, 95%CI 0.33-0.84, p = .007). Consistent results were obtained when using LDL-C as the categorical variable (P for trend = 0.016). Conclusion: The relationship between LDL-C and progression of MCI may be influenced by genetic variants.

Cognitive Reserve and Mild Cognitive Impairment: Predictors and Rates of Reversion to Intact Cognition vs Progression to Dementia

Background and Objectives

Little is known about the effect of education or other indicators of cognitive reserve on the rate of reversion from mild cognitive impairment (MCI) to normal cognition (NC) or the relative rate (RR) of reversion from MCI to NC vs progression from MCI to dementia. Our objectives were to (1) estimate transition rates from MCI to NC and dementia and (2) determine the effect of age, APOE, and indicators of cognitive reserve on the RR of reversion vs progression using multistate Markov modeling.

Methods

We estimated instantaneous transition rates between NC, MCI, and dementia after accounting for transition to death across up to 12 assessments in the Nun Study, a cohort study of religious sisters aged 75+ years. We estimated RRs of reversion vs progression for age, APOE, and potential cognitive reserve indicators: education, academic performance (high school grades), and written language skills (idea density, grammatical complexity).

Results

Of the 619 participants, 472 were assessed with MCI during the study period. Of these 472, 143 (30.3%) experienced at least one reverse transition to NC, and 120 of the 143 (83.9%) never developed dementia (mean follow-up = 8.6 years). In models adjusted for age group and APOE, higher levels of education more than doubled the RR ratio of reversion vs progression. Novel cognitive reserve indicators were significantly associated with a higher adjusted RR of reversion vs progression (higher vs lower levels for English grades: RR ratio = 1.83; idea density: RR ratio = 3.93; and grammatical complexity: RR ratio = 5.78).

Discussion

Knowledge of frequent reversion from MCI to NC may alleviate concerns of inevitable cognitive decline in those with MCI. Identification of characteristics predicting the rate of reversion from MCI to NC vs progression from MCI to dementia may guide population-level interventions targeting these characteristics to prevent or postpone MCI and dementia. Research on cognitive trajectories would benefit from incorporating predictors of reverse transitions and competing events, such as death, into statistical modeling. These results may inform the design and interpretation of MCI clinical trials, given that a substantial proportion of participants may experience improvement without intervention.

Prevalence, Lifestyle Correlates, and Psychosocial Functioning Among Multi-Ethnic Older Adults with Mild Cognitive Impairment in Singapore: Preliminary Findings from a 10/66 Population Study

Asia, which has the highest increase in dementia prevalence, is unfortunately lacking recent up-to-date research, with regions of Southeast Asia being the most inadequate. Preventive approaches, such as the understanding of Mild Cognitive Impairment (MCI), are currently the most effective approach in reducing the risk or delaying the onset of dementia but are not adequately understood. Additionally, there is a paucity of research examining lifestyle and sociodemographic correlates of MCI that are relevant to the local population of Singapore. To address these gaps, this study aimed to explore: 1) the prevalence of MCI and Amnestic Mild Cognitive Impairment (aMCI), 2) the psychosocial and lifestyle correlates of MCI and aMCI. Data were drawn from the Well-being of the Singapore Elderly (WiSE) population study, which is a single-phase cross-sectional household survey conducted among older adult residents aged 60 years and above. Analyses revealed that the weighted MCI prevalence (1.2%) was lower than global figures. Few sociodemographic and lifestyle habits were related to MCI prevalence, as only age and physical activeness emerged as significant correlates. Despite the low prevalence of MCI, individuals with MCI experienced marked disability, clinical levels of depression and anxiety, which are all concerning finds. Due to the exploratory and cross-sectional nature of the study, future longitudinal research could further refine our understanding of MCI and confirm the present findings.

Tobacco Smoking and Dementia in a Kentucky Cohort: A Competing Risk Analysis

Tobacco smoking was examined as a risk for dementia and neuropathological burden in 531 initially cognitively normal older adults followed longitudinally at the University of Kentucky's Alzheimer's Disease Center. The cohort was followed for an average of 11.5 years; 111 (20.9%) participants were diagnosed with dementia, while 242 (45.6%) died without dementia. At baseline, 49 (9.2%) participants reported current smoking (median pack-years = 47.3) and 231 (43.5%) former smoking (median pack-years = 24.5). The hazard ratio (HR) for dementia for former smokers versus never smokers based on the Cox model was 1.64 (95% CI: 1.09, 2.46), while the HR for current smokers versus never smokers was 1.20 (0.50, 2.87). However, the Fine-Gray model, which accounts for the competing risk of death without dementia, yielded a subdistribution hazard ratio (sHR) = 1.21 (0.81, 1.80) for former and 0.70 (0.30, 1.64) for current smokers. In contrast, current smoking increased incidence of death without dementia (sHR = 2.38; 1.52, 3.72). All analyses were adjusted for baseline age, education, sex, diabetes, head injury, hypertension, overweight, APOEɛ4, family history of dementia, and use of hormone replacement therapy. Once adjusted for the competing risk of death without dementia, smoking was not associated with incident dementia. This finding was supported by neuropathology on 302 of the participants.

[Mild cognitive impairment: what's next?]

The concept of mild cognitive impairment is one of the promising directions for studying the predementia stages of different diseases. The feasibility of studying this phenomenon is due not only to a high risk of dementia, but also the potential reversibility of cognitive decline in old age. Long-term follow-up of patients shows different trajectories of cognitive decline in aging. The study of risk factors for the progression of moderate cognitive impairment provided an opportunity to highlight new horizons of prevention of dementia of various etiologies. Despite the insufficient effectiveness of drug therapy in patients with moderate cognitive impairment, exploring the opportunities for possible treatment of their subtypes seems promising from the point of view of improving clinical symptoms and a possible reduction in the rate of disease progression.

Hyperpolarized [1-13C] pyruvate MR spectroscopy detect altered glycolysis in the brain of a cognitively impaired mouse model fed high-fat diet

Higher dietary intakes of saturated fatty acid increase the risk of developing Alzheimer’s disease and dementia, and even in people without diabetes higher glucose levels may be a risk factor for dementia. The mechanisms causing neuronal dysfunction and dementia by consuming high-fat diet degrading the integrity of the blood-brain barrier (BBB) has been suggested but are not yet fully understood, and metabolic state of the brain by this type of insult is still veiled. The objective of this study was to investigate the effect of high-fat diet on the brain metabolism by a multimodal imaging method using the hyperpolarizedcarbon 13 (¹³C)-pyruvate magnetic resonance (MR) spectroscopy and dynamic contrast-enhanced MR imaging in conjunction with the biochemical assay and the behavior test in a mouse model fed high-fat diet (HFD). In mice were fed 60% HFD for 6 months, hyperpolarized [1-¹³C] pyruvate MR spectroscopy showed decreased perfusion (p < 0.01) and increased conversion from pyruvate to lactate (p < 0.001) in the brain. The hippocampus and striatum showed the highest conversion ratio. The functional integrity of the blood-brain barrier tested by dynamic contrast-enhanced MR imaging showed no difference to the control. Lactate was increased in the cortex (p < 0.01) and striatum (p < 0.05), while PDH activity was decreased in the cortex (p < 0.01) and striatum (p < 0.001) and the phosphorylated PDH was increased in the striatum (p < 0.05). Mice fed HFD showed less efficiency in learning memory compared with control (p < 0.05). To determine whether hyperpolarized ¹³C-pyruvate magnetic resonance (MR) spectroscopy could detect a much earier event in the brain. Mice fed HFD for 3 months did not show a detectable cognitive decline in water maze based learning memory. Hyperpolarized [1-¹³C] pyruvate MR spectroscopy showed increased lactate conversion (P < .001), but no difference in cerebral perfusion. These results suggest that the increased hyperpolarized [1-¹³C] lactate signal in the brain of HFD-fed mice represent that altered metabolic alteration toward to glycolysis and hypoperfusion by the long-term metabolic stress by HFD further promote to glycolysis. The hyperpolarized [1-¹³C] pyruvate MR spectroscopy can be used to monitor the brain metabolism and will provide information helpful to understand the disease process.

An Update on Type 2 Diabetes Mellitus as a Risk Factor for Dementia

With the rapidly expanding evidence on brain structural and functional changes in type 2 diabetes mellitus (T2DM) patients, there is an increasing need to update our understanding on how T2DM associates with dementia as well as the underlying pathophysiological mechanisms. A literature search of T2DM and dementia or cognition impairments was carried out in electronic databases Medline, EMBASE, and Google Scholar. In this review, the chosen evidence was limited to human subject studies only, and data on either type 1 diabetes mellitus (T1DM) or non-classified diabetes were excluded. T2DM is a risk factor for both vascular dementia (VaD) and Alzheimer's disease (AD), although AD pathological marker studies have not provided sufficient evidence. T2DM interacts additively or synergistically with many factors, including old age, hypertension, total cholesterol, and APOEɛ4 carrier status for impaired cognition functions seen in patients with T2DM. In addition, comorbid T2DM can worsen the clinical presentations of patients with either AD or VaD. In summary, T2DM increases the risk for AD through different mechanisms for VaD although some mechanisms may overlap. Tau-related neurofibrillary tangles instead of amyloid-β plaques are more likely to be the pathological biomarkers for T2DM-related dementia. Degeneration of neurons in the brain, impaired regional blood supply/metabolism, and genetic predisposition are all involved in T2DM-associated dementia or cognitive impairments.

A stochastic estimation procedure for intermittently-observed semi-Markov multistate models with back transitions

Multistate models provide an important method for analyzing a wide range of life history processes including disease progression and patient recovery following medical intervention. Panel data consisting of the states occupied by an individual at a series of discrete time points are often used to estimate transition intensities of the underlying continuous-time process. When transition intensities depend on the time elapsed in the current state and back transitions between states are possible, this intermittent observation process presents difficulties in estimation due to intractability of the likelihood function. In this manuscript, we present an iterative stochastic expectation-maximization algorithm that relies on a simulation-based approximation to the likelihood function and implement this algorithm using rejection sampling. In a simulation study, we demonstrate the feasibility and performance of the proposed procedure. We then demonstrate application of the algorithm to a study of dementia, the Nun Study, consisting of intermittently-observed elderly subjects in one of four possible states corresponding to intact cognition, impaired cognition, dementia, and death. We show that the proposed stochastic expectation-maximization algorithm substantially reduces bias in model parameter estimates compared to an alternative approach used in the literature, minimal path estimation. We conclude that in estimating intermittently observed semi-Markov models, the proposed approach is a computationally feasible and accurate estimation procedure that leads to substantial improvements in back transition estimates.

Risk factors of transition from mild cognitive impairment to Alzheimer's disease and death: A cohort study

BACKGROUND

Knowledge of risk factors is essential for developing strategies that prevent or minimise transitions from mild cognitive impairment (MCI) to Alzheimer's disease (AD) and death. The aim of this study was to assess risk factors for progression to AD and death among Chinese individuals with cognitive impairment.

METHODS

We conducted a multisite, population-based cohort study on 437 community-dwelling elderly MCI residents in Taiyuan, China from 2010 to 2014. MCI, AD, death from AD and death from a cause other than AD were specified as disease states during the natural history of dementia. Transition-specific Cox model was fitted and hazard ratio (HR) with 95% confidence intervals (CIs) was estimated.

RESULTS

Analyses showed that risk factors played different roles in affecting transitions to AD and death. Risk factors for transition from MCI to AD were being female (HR: 1.82; 95%CI: 1.20-2.77), older age (HR: 3.09; 95%CI: 1.81-5.25), reading occasionally (HR: 1.79; 95%CI: 1.11-2.89), current smoking (HR: 1.74; 95%CI: 1.15-2.65), light-moderate alcohol drinker (HR: 2.24; 95%CI: 1.42-3.53), cerebrovascular disease (HR: 2.70; 95%CI: 1.68-4.34), hyperlipidemia (HR: 1.87; 95%CI: 1.16-3.02) and diabetes (HR: 1.81; 95%CI: 1.18-2.77). Only cerebrovascular disease (HR: 3.04; 95%CI: 1.22-7.58) was a significant risk factor for transition from MCI to death from a cause other than AD. Older age (HR: 10.68; 95%CI: 1.16-97.93) and low level education (HR: 0.14; 95%CI: 0.05-0.44) were significant predictors for transition from AD to death from a cause other than AD.

CONCLUSIONS

Participants with advanced age, low-level education, history of harmful alcohol consumption or smoking, cerebrovascular disease, hyperlipidemia, diabetes or who were female were at increased risk of transitioning to AD or death. Strategies to control modifiable risk factors in specific disease stage should be implemented to decrease the conversion to AD or death among Chinese patients with MCI.

Multi-state models and missing covariate data: Expectation-Maximization algorithm for likelihood estimation

Multi-state models have been widely used to analyze longitudinal event history data obtained in medical and epidemiological studies. The tools and methods developed recently in this area require completely observed data. However, missing data within variables of interest is very common in practice, and it has been an issue in applications. We propose a type of EM algorithm, which handles missingness within multiple binary covariates efficiently, for multi-state model applications. Simulation studies show that the EM algorithm performs well for both missing completely at random (MCAR) and missing at random (MAR) covariate data. We apply the method to a longitudinal aging and cognition study dataset, the Klamath Exceptional Aging Project (KEAP), whose data were collected at Oregon Health & Science University and integrated into the Statistical Models of Aging and Risk of Transition (SMART) database at the University of Kentucky.

Outcomes after diagnosis of mild cognitive impairment in a large autopsy series

OBJECTIVE

To determine clinical and neuropathological outcomes following a clinical diagnosis of mild cognitive impairment (MCI).

METHODS

Data were drawn from a large autopsy series (N = 1,337) of individuals followed longitudinally from normal or MCI status to death, derived from 4 Alzheimer Disease (AD) Centers in the United States.

RESULTS

Mean follow-up was 7.9 years. Of the 874 individuals ever diagnosed with MCI, final clinical diagnoses were varied: 39.2% died with an MCI diagnosis, 46.8% with a dementia diagnosis, and 13.9% with a diagnosis of intact cognition. The latter group had pathological features resembling those with a final clinical diagnosis of MCI. In terms of non-AD pathologies, both primary age-related tauopathy (p < 0.05) and brain arteriolosclerosis pathology (p < 0.001) were more severe in MCI than cognitively intact controls. Among the group that remained MCI until death, mixed AD neuropathologic changes (ADNC; ≥1 comorbid pathology) were more frequent than "pure" ADNC pathology (55% vs 22%); suspected non-Alzheimer pathology comprised the remaining 22% of cases. A majority (74%) of subjects who died with MCI were without "high"-level ADNC, Lewy body disease, or hippocampal sclerosis pathologies; this group was enriched in cerebrovascular pathologies. Subjects who died with dementia and were without severe neurodegenerative pathologies tended to have cerebrovascular pathology and carry the MCI diagnosis for a longer interval.

INTERPRETATION

MCI diagnosis usually was associated with comorbid neuropathologies; less than one-quarter of MCI cases showed "pure" AD at autopsy. Ann Neurol 2017;81:549-559.

Staging cognitive impairment and incidence of dementia

AIMS

In a background of interest in staging models in psychiatry, we tested the validity of a simple staging model of cognitive impairment to predict incident dementia.

METHOD

A large community sample of adults aged ≥55 years (N = 4803) was assessed in the baseline of a longitudinal, four-wave epidemiological enquiry. A two-phase assessment was implemented in each wave, and the instruments used included the Mini-Mental Status Examination (MMSE); the History and Aetiology Schedule and the Geriatric Mental State-AGECAT. For the standardised degree of cognitive impairment Perneczky et al's MMSE criteria were applied. A panel of psychiatrists diagnosed cases of dementia according to DSM-IV criteria, and cases and sub-cases of dementia were excluded for the follow-up waves. Competing risk regression models, adjusted by potential confounders, were used to test the hypothesised association between MMSE levels and dementia risk.

RESULTS

Out of the 4057 participants followed up, 607 (14.9%) were classified as 'normal' (no cognitive impairment), 2672 (65.8%) as 'questionable' cognitive impairment, 732 (18.0%) had 'mild' cognitive impairment, 38 (0.9%) had 'moderate' cognitive impairment and eight (0.2%) had 'severe' impairment. Cognitive impairment was associated with risk of dementia, the risk increasing in parallel with the level of impairment (hazard ratio: 2.72, 4.78 and 8.38 in the 'questionable', 'mild' and 'moderate' level of cognitive impairment, respectively).

CONCLUSIONS

The documented gradient of increased risk of dementia associated with the severity level of cognitive impairment supports the validity of the simple staging model based on the MMSE assessment.

Type 2 diabetes mellitus is associated with brain atrophy and hypometabolism in the ADNI cohort

OBJECTIVE

We investigated type 2 diabetes mellitus (T2DM) as a risk factor for brain atrophy and glucose hypometabolism in older adults with or at risk of cognitive impairment.

METHODS

Participants with the T2DM were identified from the Alzheimer's Disease Neuroimaging Initiative (ADNI-1/GO/2 cohorts). Analysis of covariance models were used to compare participants with and without T2DM, controlling for potential confounding factors.

RESULTS

Whole brain volume and whole brain [(18)F]-fluorodeoxyglucose (FDG) uptake were significantly different as a function of T2DM status, independent of baseline clinical diagnosis. On post hoc analysis, a lower whole brain volume was seen in participants with both mild cognitive impairment (MCI) and T2DM (n = 76) compared with participants who had MCI but not T2DM (n = 747; p = 0.009). Similarly, mean FDG uptake in gray matter and white matter was lower in participants with both MCI and T2DM (n = 72) than in participants with MCI without T2DM (n = 719; p = 0.04). Subsequent regional analysis revealed that the decreased FDG uptake in participants with both MCI and T2DM was mainly manifested in 3 brain regions: frontal lobe, sensory motor cortex, and striatum.

CONCLUSIONS

T2DM may accelerate cognition deterioration in patients with MCI by affecting glucose metabolism and brain volume.

The influence of smoking, sedentary lifestyle and obesity on cognitive impairment-free life expectancy

BACKGROUND

Smoking, sedentary lifestyle and obesity are risk factors for mortality and dementia. However, their impact on cognitive impairment-free life expectancy (CIFLE)has not previously been estimated.

METHODS

Data were drawn from the DYNOPTA dataset which was derived by harmonizing and pooling common measures from five longitudinal ageing studies. Participants for whom the Mini-Mental State Examination was available were included (N¼8111,48.6% men). Data on education, sex, body mass index, smoking and sedentary lifestyle were collected and mortality data were obtained from Government Records via data linkage.Total life expectancy (LE), CIFLE and years spent with cognitive impairment (CILE)were estimated for each risk factor and total burden of risk factors.

RESULTS

CILE was approximately 2 years for men and 3 years for women, regardless of age. For men and women respectively, reduced LE associated with smoking was 3.82and 5.88 years, associated with obesity was 0.62 and 1.72 years and associated with being sedentary was 2.50 and 2.89 years. Absence of each risk factor was associated with longer LE and CIFLE, but also longer CILE for smoking in women and being sedentary in both sexes. Compared with participants with no risk factors, those with 2þ had shorter CIFLE of up to 3.5 years depending on gender and education level.

CONCLUSIONS

Population level reductions in smoking, sedentary lifestyle and obesity increase longevity and number of years lived without cognitive impairment. Years lived with cognitive impairment may also increase.

Cognitive performance before and after the onset of subjective cognitive decline in old age

Background

Our objectives were (1) to test the association between the report of subjective cognitive decline (SCD) and prospective objective cognitive performance in high age individuals and (2) to study the course of longitudinal cognitive performance before and after the first report of SCD.

Methods

Cognitively normal elderly participants of the German Study on Ageing, Cognition, and Dementia study (N = 2330) with SCD (subjective decline in memory with and without associated concerns) and without SCD at baseline were assessed over 8 years with regard to immediate and delayed verbal recall, verbal fluency, working memory, and global cognition. Baseline performance and cognitive trajectories were compared between groups. In addition, cognitive trajectories before and after the initial report of SCD (incident SCD) were modelled in those without SCD at baseline.

Results

Baseline performance in the SCD group was lower and declined more steeply in immediate and delayed verbal recall than in the control group (no SCD at baseline). This effect was more pronounced in the SCD group with concerns. Incident SCD was preceded by decline in immediate and delayed memory and word fluency.

Conclusions

SCD predicts future memory decline. Incident SCD is related to previous cognitive decline. The latter finding supports the concept of SCD indicating first subtle decline in cognitive performance that characterizes preclinical Alzheimer's disease.

The Statistical Modeling of Aging and Risk of Transition Project: Data Collection and Harmonization Across 11 Longitudinal Cohort Studies of Aging, Cognition, and Dementia

Longitudinal cognitive trajectories and other factors associated with mixed neuropathologies (such as Alzheimer's disease with co-occurring cerebrovascular disease) remain incompletely understood, despite being the rule and not the exception in older populations. The Statistical Modeling of Aging and Risk of Transition study (SMART) is a consortium of 11 different high-quality longitudinal studies of aging and cognition (N=11,541 participants) established for the purpose of characterizing risk and protective factors associated with subtypes of age-associated mixed neuropathologies (N=3,001 autopsies). While brain donation was not required for participation in all SMART cohorts, most achieved substantial autopsy rates (i.e., > 50%). Moreover, the studies comprising SMART have large numbers of participants who were followed from intact cognition and transitioned to cognitive impairment and dementia, as well as participants who remained cognitively intact until death. These data provide an exciting opportunity to apply sophisticated statistical methods, like Markov processes, that require large, well-characterized samples. Thus, SMART will serve as an important resource for the field of mixed dementia epidemiology and neuropathology.

Self-reported memory complaints: implications from a longitudinal cohort with autopsies

OBJECTIVE

We assessed salience of subjective memory complaints (SMCs) by older individuals as a predictor of subsequent cognitive impairment while accounting for risk factors and eventual neuropathologies.

METHODS

Subjects (n = 531) enrolled while cognitively intact at the University of Kentucky were asked annually if they perceived changes in memory since their last visit. A multistate model estimated when transition to impairment occurred while adjusting for intervening death. Risk factors affecting the timing and probability of an impairment were identified. The association between SMCs and Alzheimer-type neuropathology was assessed from autopsies (n = 243).

RESULTS

SMCs were reported by more than half (55.7%) of the cohort, and were associated with increased risk of impairment (unadjusted odds ratio = 2.8, p < 0.0001). Mild cognitive impairment (dementia) occurred 9.2 (12.1) years after SMC. Multistate modeling showed that SMC reporters with an APOE ε4 allele had double the odds of impairment (adjusted odds ratio = 2.2, p = 0.036). SMC smokers took less time to transition to mild cognitive impairment, while SMC hormone-replaced women took longer to transition directly to dementia. Among participants (n = 176) who died without a diagnosed clinical impairment, SMCs were associated with elevated neuritic amyloid plaques in the neocortex and medial temporal lobe.

CONCLUSION

SMC reporters are at a higher risk of future cognitive impairment and have higher levels of Alzheimer-type brain pathology even when impairment does not occur. As potential harbingers of future cognitive decline, physicians should query and monitor SMCs from their older patients.

Semi-Markov models for interval censored transient cognitive states with back transitions and a competing risk

Continuous-time multi-state stochastic processes are useful for modeling the flow of subjects from intact cognition to dementia with mild cognitive impairment and global impairment as intervening transient cognitive states and death as a competing risk. Each subject's cognition is assessed periodically resulting in interval censoring for the cognitive states while death without dementia is not interval censored. Since back transitions among the transient states are possible, Markov chains are often applied to this type of panel data. In this manuscript, we apply a semi-Markov process in which we assume that the waiting times are Weibull distributed except for transitions from the baseline state, which are exponentially distributed and in which we assume no additional changes in cognition occur between two assessments. We implement a quasi-Monte Carlo (QMC) method to calculate the higher order integration needed for likelihood estimation. We apply our model to a real dataset, the Nun Study, a cohort of 461 participants.

Markov chains and semi-Markov models in time-to-event analysis

A variety of statistical methods are available to investigators for analysis of time-to-event data, often referred to as survival analysis. Kaplan-Meier estimation and Cox proportional hazards regression are commonly employed tools but are not appropriate for all studies, particularly in the presence of competing risks and when multiple or recurrent outcomes are of interest. Markov chain models can accommodate censored data, competing risks (informative censoring), multiple outcomes, recurrent outcomes, frailty, and non-constant survival probabilities. Markov chain models, though often overlooked by investigators in time-to-event analysis, have long been used in clinical studies and have widespread application in other fields.