BackgroundAlzheimer’s disease is a neurodegenerative syndrome characterized by multiple dimensions including cognitive decline, decreased daily functioning and psychiatric symptoms. This systematic review aims to investigate the relation between somatic comorbidity burden and progression in late-onset Alzheimer’s disease (LOAD).MethodsWe searched four databases for observational studies that examined cross-sectional or longitudinal associations of cognitive or functional or neuropsychiatric outcomes with comorbidity in individuals with LOAD. From the 7966 articles identified originally, 11 studies were included in this review. The Newcastle-Ottawa quality assessment was used. The large variation in progression measures, comorbidity indexes and study designs hampered the ability to perform a meta-analysis. This review was registered with PROSPERO under DIO: 10.15124/CRD42015027046.ResultsNine studies indicated that comorbidity burden was associated with deterioration in at least one of the three dimensions of LOAD examined. Seven out of ten studies investigating cognition found comorbidities to be related to decreased cognitive performance. Five out of the seven studies investigating daily functioning showed an association between comorbidity burden and decreased daily functioning. Neuropsychiatric symptoms (NPS) increased with increasing comorbidity burden in two out of three studies investigating NPS. Associations were predominantly found in studies analyzing the association cross-sectionally, in a time-varying manner or across short follow-up (≤2 years). Rarely baseline comorbidity burden appeared to be associated with outcomes in studies analyzing progression over longer follow-up periods (>2 years).ConclusionThis review provides evidence of an association between somatic comorbidities and multifaceted LOAD progression. Given that time-varying comorbidity burden, but much less so baseline comorbidity burden, was associated with the three dimensions prospectively, this relationship cannot be reduced to a simple cause-effect relation and is more likely to be dynamic. Therefore, both future studies and clinical practice may benefit from regarding comorbidity as a modifiable factor with a possibly fluctuating influence on LOAD.

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Purpose of review To date, most research in dementia has focused either on the identification of dementia risk prediction or on understanding changes and predictors experienced by individuals before diagnosis. Despite little is known about how individuals change after dementia diagnosis, there is agreement that changes occur over different time scales and are multidomain. In this study, we present an overview of the literature regarding the longitudinal course of dementia. Recent findings Our review suggests the evidence is scarce and findings reported are often inconsistent. We identified large heterogeneity in dementia trajectories, risk factors considered and modelling approaches employed. The heterogeneity of dementia trajectories also varies across outcomes and domains investigated.

ObjectiveTo develop survival prediction tables to inform physicians and patients about survival probabilities after the diagnosis of dementia and to determine whether survival after dementia diagnosis can be predicted with good accuracy.MethodsWe conducted a nationwide registry-linkage study including 829 health centers, i.e., all memory clinics and ≈75% of primary care facilities, across Sweden. Data including cognitive function from 50,076 people with incident dementia diagnoses ≥65 years of age and registered with the Swedish Dementia Register in 2007 to 2015 were used, with a maximum follow-up of 9.7 years for survival until 2016. Sociodemographic factors, comorbidity burden, medication use, and dates of death were obtained from nationwide registries. Cox proportional hazards regression models were used to create tables depicting 3-year survival probabilities for different risk factor profiles.ResultsBy August 2016, 20,828 (41.6%) patients in our cohort had died. Median survival time from diagnosis of dementia was 5.1 (interquartile range 2.9–8.0) years for women and 4.3 (interquartile range 2.3–7.0) years for men. Predictors of mortality were higher age, male sex, increased comorbidity burden and lower cognitive function at diagnosis, a diagnosis of non-Alzheimer dementia, living alone, and using more medications. The developed prediction tables yielded c indexes of 0.70 (95% confidence interval [CI] 0.69–0.71) to 0.72 (95% CI 0.71–0.73) and showed good calibration.ConclusionsThree-year survival after dementia diagnosis can be predicted with good accuracy. The survival prediction tables developed in this study may aid clinicians and patients in shared decision-making and advance care planning.

Objective We sought to replicate a previously published prediction model for progression, developed in the Cache County Dementia Progression Study (CCDPS), using a clinical cohort from the National Alzheimer’s Coordinating Center. Methods We included 1120 incident AD cases with at least one assessment after diagnosis, originating from 31 Alzheimer Disease centers from the United States. Trajectories of the Mini-Mental State Examination (MMSE) and Clinical Dementia Rating sum of boxes (CDR-sb) were modeled jointly over time using parallel-process growth mixture models in order to identify latent classes of trajectories. Bias-corrected multinomial logistic regression was used to identify baseline predictors of class membership and compare these with the predictors found in the CCDPS. Results The best fitting model contained three classes; class 1 was the largest (63%) and showed the slowest progression on both MMSE and CDR-sb. Classes 2 (22%) and 3 (15%) showed moderate and rapid worsening, respectively. Significant predictors of membership in classes 2 and 3, relative to class 1, were worse baseline MMSE and CDR-sb, higher education and lack of hypertension. Combining all previously mentioned predictors yielded areas under the ROC curve of 0.70 and 0.75 for classes 2 and 3, relative to class 1. Conclusions Our replication study confirmed that it is possible to predict trajectories of progression in AD with relatively good accuracy. The class distribution was comparable with the original study, with most individuals being members of a class with stable or slow progression. This is important for informing newly diagnosed AD patients and their caregivers.

IntroductionThe aim of this study was to investigate the association between acetylcholinesterase inhibitor (AChEI) use and risk of ischemic stroke and death in people with dementia.MethodsA cohort study of 44,288 people with dementia registered in the Swedish Dementia Registry from 2007 to 2014. Propensity score‐matched competing risk regression models were used to compute hazard ratios and 95% confidence intervals for the association between time‐dependent AChEI use and risk of stroke and death.ResultsCompared with matched controls, AChEI users had a lower risk of stroke (hazard ratio: 0.85, 95% confidence interval: 0.75–0.95) and all‐cause death (hazard ratio: 0.76, 95% confidence interval: 0.72–0.80). After considering competing risk of death, high doses (≥1.33 defined daily doses) of AChEI remained significantly associated with reduced stroke risk.DiscussionThe use of AChEIs in people with dementia may be associated with reduced risk of ischemic stroke and death. These results call for a closer examination of the cardiovascular effects of AChEIs.

This study demonstrates the heterogeneity of dementia progression between individuals and between different dementia domains within individuals. To improve our understanding of dementia progression, future research should embrace a broader perspective encompassing multiple outcome measures along with the patient's profile, including neurological factors as well as physical, social, and psychiatric health.

Objectives: Previous studies have shown large heterogeneity in the progression of dementia, both within and between patients. This heterogeneity offers an opportunity to limit the global and individual burden of dementia through the identification of factors associated with slow disease progression in dementia. We explored the heterogeneity in dementia progression to detect disease, patient, and social context factors related to slow progression. Design: Two longitudinal population-based cohort studies with follow-up across 12 years. Setting and Participants: 512 people with incident dementia from Stockholm (Sweden) contributed to the Kungsholmen Project and the Swedish National Study of Aging and Care in Kungsholmen. Methods: We measured cognition using the Mini-Mental State Examination and daily functioning using the Katz Activities of Daily Living Scale. Latent classes of trajectories were identified using a bivariate growth mixture model. We then used bias-corrected logistic regression to identify predictors of slower progression. Results: Two distinct groups of progression were identified; 76% (n ¼ 394) of the people with dementia exhibited relatively slow progression on both cognition and daily functioning, whereas 24% (n ¼ 118) demonstrated more rapid worsening on both outcomes. Predictors of slower disease progression were Alzheimer's disease (AD) dementia type [odds ratio (OR) 2.07, 95% confidence interval (CI) 1.15-3.71], lower age (OR 0.88, 95% CI 0.83-0.94), fewer comorbidities (OR 0.77, 95% CI 0.66-0.90), and a stronger social network (OR 1.72, 95% CI 1.01-2.93). Conclusions/Implications: Lower age, AD dementia type, fewer comorbidities, and a good social network appear to be associated with slow cognitive and functional decline. These factors may help to improve the counseling of patients and caregivers and to optimize the planning of care in dementia.