Does the neuropsychiatric inventory predict progression from mild cognitive impairment to dementia? A systematic review and meta-analysis

Difference of Cerebrospinal Fluid Biomarkers and Neuropsychiatric Symptoms Profiles among Normal Cognition, Mild Cognitive Impairment, and Dementia Patient

The delineation of biomarkers and neuropsychiatric symptoms across normal cognition, mild cognitive impairment (MCI), and dementia stages holds significant promise for early diagnosis and intervention strategies. This research investigates the association of neuropsychiatric symptoms, evaluated via the Neuropsychiatric Inventory (NPI), with cerebrospinal fluid (CSF) biomarkers (Amyloid-β42, P-tau, T-tau) across a spectrum of cognitive states to enhance diagnostic accuracy and treatment approaches. Drawing from the National Alzheimer's Coordinating Center's Uniform Data Set Version 3, comprising 977 individuals with normal cognition, 270 with MCI, and 649 with dementia. To assess neuropsychiatric symptoms, we employed the NPI to understand the behavioral and psychological symptoms associated with each cognitive category. For the analysis of CSF biomarkers, we measured levels of Amyloid-β42, P-tau, and T-tau using the enzyme-linked immunosorbent assay (ELISA) and Luminex multiplex xMAP assay protocols. These biomarkers are critical in understanding the pathophysiological underpinnings of Alzheimer's disease and its progression, with specific patterns indicative of disease stage and severity. This study cohort consists of 1896 participants, which is composed of 977 individuals with normal cognition, 270 with MCI, and 649 with dementia. Dementia is characterized by significantly higher NPI scores, which are largely reflective of mood-related symptoms (p < 0.001). In terms of biomarkers, normal cognition shows median Amyloid-β at 656.0 pg/mL, MCI at 300.6 pg/mL, and dementia at 298.8 pg/mL (p < 0.001). Median P-tau levels are 36.00 pg/mL in normal cognition, 49.12 pg/mL in MCI, and 58.29 pg/mL in dementia (p < 0.001). Median T-tau levels are 241.0 pg/mL in normal cognition, 140.6 pg/mL in MCI, and 298.3 pg/mL in dementia (p < 0.001). Furthermore, the T-tau/Aβ-42 ratio increases progressively from 0.058 in the normal cognition group to 0.144 in the MCI group, and to 0.209 in the dementia group (p < 0.001). Similarly, the P-tau/Aβ-42 ratio also escalates from 0.305 in individuals with normal cognition to 0.560 in MCI, and to 0.941 in dementia (p < 0.001). The notable disparities in NPI and CSF biomarkers among normal, MCI and Alzheimer's patients underscore their diagnostic potential. Their combined assessment could greatly improve early detection and precise diagnosis of MCI and dementia, facilitating more effective and timely treatment strategies.

Neuropsychiatric Symptoms Predict Faster Cognitive Decline in Dementia Collaborative Care Than Antipsychotic Use

Background

To compare short-term cognitive outcomes among groups with and without neuropsychiatric symptoms (NPSs) or antipsychotic prescription and to determine which disease status or treatment modality is associated with relatively faster cognitive decline.

Methods

We retrospectively analyzed a prospective cohort of patients diagnosed with dementia and mild cognitive impairment. All participants were evaluated using the Cognitive Abilities Screening Instrument (CASI) during their initial clinical assessments and at the annual follow-up. The dependent variable was annual delta CASI. Multivariate linear regression analysis was used to assess the degree of association between NPS, antipsychotic use, and cognitive decline after adjusting for confounding factors. Neuropsychiatric symptoms were examined individually to determine their predictive value for cognitive decline.

Results

A total of 407 (N = 407) patients were included in the study. NPSs, rather than antipsychotic use, led to faster cognitive decline. A higher baseline NPI total score predicted a significantly faster decline in CASI scores (1-year delta CASI = -0.22, 95% CI = -0.38~ -0.05, p = 0.010). Specific items (delusions, agitation, depression, anxiety, euphoria, and apathy) in the NPS significantly increased cognitive decline.

Conclusion

Certain neuropsychiatric symptoms, rather than antipsychotic use, lead to faster cognitive decline in a dementia collaborative care model. Checking for and providing appropriate interventions for NPS in people with dementia and their caregivers are highlighted.

Mild Behavioral Impairment and Cerebrovascular Profiles Are Associated with Early Cognitive Impairment in a Community-Based Southeast Asian Cohort

Background

Mild behavioral impairment (MBI) is one of the earliest observable changes when a person experiences cognitive decline and could be an early manifestation of underlying Alzheimer's disease neuropathology. Limited attention has been given to investigating the clinical applicability of behavioral biomarkers for detection of prodromal dementia.

Objective

This study compared the prevalence of self-reported MBI and vascular risk factors in Southeast Asian adults to identify early indicators of cognitive impairment and dementia.

Methods

This cohort study utilized baseline data from the Biomarkers and Cognition Study, Singapore (BIOCIS). 607 participants were recruited and classified into three groups: cognitively normal (CN), subjective cognitive decline (SCD), and mild cognitive impairment (MCI). Group comparisons of cognitive-behavioral, neuroimaging, and blood biomarkers data were applied using univariate analyses. Multivariate logistic regression analyses were conducted to investigate the association between cerebrovascular disease, vascular profiles, and cognitive impairment.

Results

SCD had significantly higher depression scores and poorer quality of life (QOL) compared to CN. MCI had significantly higher depression scores; total MBI symptoms, MBI-interest, MBI-mood, and MBI-beliefs; poorer sleep quality; and poorer QOL compared to CN. Higher Staals scores, glucose levels, and systolic blood pressure were significantly associated with MCI classification. Fasting glucose levels were significantly correlated with depression, anxiety, MBI-social, and poorer sleep quality.

Conclusions

The results reflect current research that behavioral changes are among the first symptoms noticeable to the person themselves as they begin to experience cognitive decline. Self-reported questionnaires may aid in early diagnoses of prodromal dementia. Behavioral changes and diabetes could be potential targets for preventative healthcare for dementia.

Predictors for quality of life in older adults: network analysis on cognitive and neuropsychiatric symptoms

BACKGROUND

Quality of life (QoL) of older adults has become a pivotal concern of the public and health system. Previous studies found that both cognitive decline and neuropsychiatric symptoms (NPS) can affect QoL in older adults. However, it remains unclear how these symptoms are related to each other and impact on QoL. Our aim is to investigate the complex network relationship between cognitive and NPS symptoms in older adults, and to further explore their association with QoL.

METHODS

A cross-sectional study was conducted in a sample of 389 older individuals with complaints of memory decline. The instruments included the Neuropsychiatric Inventory, the Mini Mental State Examination, and the 36-item Short Form Health Survey. Data was analyzed using network analysis and mediation analysis.

RESULTS

We found that attention and agitation were the variables with the highest centrality in cognitive and NPS symptoms, respectively. In an exploratory mediation analysis, agitation was significantly associated with poor attention (β = -0.214, P < 0.001) and reduced QoL (β = -0.137, P = 0.005). The indirect effect of agitation on the QoL through attention was significant (95% confidence interval (CI) [-0.119, -0.035]). Furthermore, attention served as a mediator between agitation and QoL, accounting for 35.09% of the total effect.

CONCLUSIONS

By elucidating the NPS-cognition-QoL relationship, the current study provides insights for developing rehabilitation programs among older adults to ensure their QoL.

Preliminary Validation Study of the French-Quebec Version of the Mild Behavioral Impairment Checklist

BACKGROUND

Alzheimer disease dementia may be preceded by cognitive stages during which behavioral and psychological changes can occur. More precisely, behavioral symptoms may be observed during the subjective cognitive decline (SCD) or the mild cognitive impairment (MCI) stages; these symptoms can be measured using the Mild Behavioral Impairment Checklist (MBI-C).

OBJECTIVE

To validate the French-Quebec version of the MBI-C in individuals ages 60-85 years.

METHOD

The sample included 60 participants (20 MCI, 20 SCD, 20 cognitively healthy) and their informants. To assess the discriminant validity of the MBI-C, a Kruskal-Wallis analysis with a multiple comparisons test was performed on the MBI-C Total score. To determine convergent validity, Spearman correlations were calculated between the MBI-C subscales and a set of validation tools. Finally, test-retest reliability was assessed with Spearman correlations of MBI-C scores between two test sessions.

RESULTS

All of the analyses indicated satisfactory psychometric properties for the French-Quebec version of the MBI-C.

CONCLUSION

This validation study reveals that the MBI-C can be used successfully in dementia risk assessments. From now on, the use of a validated MBI-C will be possible in the French-Quebec population.

An Exploration of Subgroups of Neuropsychiatric Symptoms in Mild Cognitive Impairment and Their Risks of Conversion to Dementia or Death

OBJECTIVE

To explore the heterogeneity of neuropsychiatric symptom (NPS) complexes in individuals with mild cognitive impairment (MCI) and assess the relative risks of converting to dementia or dying.

DESIGN

Latent class analysis using 7,971 participants with MCI.

SETTING

Participants in the Uniform Data Set (UDS) from 39 NIH Alzheimer's Disease Centers.

PARTICIPANTS

Persons with a diagnosis of MCI at initial visit from each center and with either a Mini-Mental State Examination (MMSE) score of 22 or greater or an equivalent education-adjusted Montreal Cognitive Assessment (MoCA) score of 16 or greater.

MEASUREMENTS

Neuropsychiatric Inventory Questionnaire (NPI-Q) administered at initial visit.

RESULTS

In addition to a subgroup with mild or no NPS (relative frequency, 50%), three empirically-based subgroups of NPS were identified: 1) an "affect" or "negative mood" subgroup (27%) with depression, anxiety, apathy, nighttime disturbance, and change in appetite; 2) a "hyperactive" subgroup (14%) with agitation, irritability, and disinhibition; and 3) a "psychotic with additional severe NPS" subgroup (9%) with the highest risk of delusions and hallucinations, as well as highest risk of all other NPS. Each of these three subgroups had significantly higher risk of converting to dementia than the "mild NPS" class, with the "psychotic with additional severe NPS" subgroup possessing a 64% greater risk. The subgroups did not differ in their risks of death without dementia.

CONCLUSION

Our findings of three NPS subgroups in MCI characterized by affect, hyperactive, or psychotic features are largely consistent with a previous 3-factor model of NPS found in a demented population. The consistency of these findings across studies and samples, coupled with our results on the associated risks of converting to dementia, suggests that the NPS structure is robust, and warrants further consideration in classification models of MCI.

A novelty detection approach to effectively predict conversion from mild cognitive impairment to Alzheimer’s disease

Accurately recognising patients with progressive mild cognitive impairment (pMCI) who will develop Alzheimer’s disease (AD) in subsequent years is very important, as early identification of those patients will enable interventions to potentially reduce the number of those transitioning from MCI to AD. Most studies in this area have concentrated on high-dimensional neuroimaging data with supervised binary/multi-class classification algorithms. However, neuroimaging data is more costly to obtain than non-imaging, and healthcare datasets are normally imbalanced which may reduce classification performance and reliability. To address these challenges, we proposed a new strategy that employs unsupervised novelty detection (ND) techniques to predict pMCI from the AD neuroimaging initiative non-imaging data. ND algorithms, including the k-nearest neighbours (kNN), k-means, Gaussian mixture model (GMM), isolation forest (IF) and extreme learning machine (ELM), were employed and compared with supervised binary support vector machine (SVM) and random forest (RF). We introduced optimisation with nested cross-validation and focused on maximising the adjusted F measure to ensure maximum generalisation of the proposed system by minimising false negative rates. Our extensive experimental results show that ND algorithms (0.727 ± 0.029 kNN, 0.7179 ± 0.0523 GMM, 0.7276 ± 0.0281 ELM) obtained comparable performance to supervised binary SVM (0.7359 ± 0.0451) with 20% stable MCI misclassification tolerance and were significantly better than RF (0.4771 ± 0.0167). Moreover, we found that the non-invasive, readily obtainable, and cost-effective cognitive and functional assessment was the most efficient predictor for predicting the pMCI within 2 years with ND techniques. Importantly, we presented an accessible and cost-effective approach to pMCI prediction, which does not require labelled data.

Evaluation of a Telephone Version for the Montreal Cognitive Assessment: Establishing a Cutoff for Normative Data From a Cross-Sectional Study

OBJECTIVE

Compare a telephone version and full version of the Montreal Cognitive Assessment (MoCA).

METHODS

Cross-sectional analysis of a prospective study. A 20-point telephone version of MoCA (Tele-MoCA) was compared to the Full-MoCA and Mini Mental State Examination.

RESULTS

Total of 140 participants enrolled. Mean scores for language were significantly lower with Tele-MoCA than with Full-MoCA (P = .003). Mean Tele-MoCA scores were significantly higher for participants with over 12 years of education (P < .001). Cutoff score of 17 for the Tele-MoCA yielded good specificity (82.2%) and negative predictive value (84.4%), while sensitivity was low (18.2%).

CONCLUSIONS

Remote screening of cognition with a 20-point Tele-MoCA is as specific for defining normal cognition as the Full-MoCA. This study shows that telephone evaluation is adequate for virtual cognitive screening. Our sample did not allow accurate assessment of sensitivity for Tele-MoCA in detecting MCI or dementia. Further studies with representative populations are needed to establish sensitivity.

Neuropsychiatric Symptoms Mediated the Relationship Between Odor Identification and Cognition in Alzheimer's Disease Spectrum: A Structural Equation Model Analysis

Background: Odor identification dysfunction is an early predictor of the development of Alzheimer's disease (AD), but neuropsychiatric symptoms (NPS), which are common in AD and mild cognitive impairment (MCI), are also associated with odor identification dysfunction. Whether NPS affect the specificity of using odor identification dysfunction to predict cognitive decline in AD and MCI remains unclear.

Methods: Patients (233 with MCI and 45 with AD) and 45 healthy controls (HCs) underwent assessments of odor identification (Sniffin' Sticks), NPS (Neuropsychiatric Inventory-12), and cognitive function (global cognition, memory, language, executive function, visual-spatial skill, and attention). Structural equation modeling (SEM) with bootstrapping estimation was conducted to explore the relationships between odor identification, NPS, and cognition.

Results: Patients with NPS showed significantly worse performance in odor identification and cognition than patients without NPS and HCs. The SEM showed odor identification to be positively associated with cognition, and cognition had special indirect effects on odor identification through affective and psychosis symptoms (two factors extracted from Neuropsychiatric Inventory-12). Additionally, affective and psychosis symptoms partially mediated the effect of cognition on odor identification.

Conclusion: Neuropsychiatric symptoms are associated with odor identification dysfunction in patients with AD and MCI. Studies exploring the relationship between odor identification dysfunction and cognitive decline in patients with AD and MCI should include an assessment of affective and psychosis symptoms, and adjust their confounding effects.

Anxiety symptoms and mild cognitive impairment among community-dwelling older adults from low- and middle-income countries

AIM

Anxiety may be a risk factor for mild cognitive impairment (MCI) but there is a scarcity of data on this association especially from low- and middle-income countries (LMICs). Thus, we investigated the association between anxiety and MCI among older adults residing in six LMICs (China, Ghana, India, Mexico, Russia, South Africa), and the mediational effect of sleep problems in this association.

METHODS

Cross-sectional, community-based, nationally representative data from the WHO Study on global AGEing and adult health (SAGE) were analyzed. The definition of MCI was based on the National Institute on Ageing-Alzheimer's Association criteria. Multivariable logistic regression analysis, meta-analysis, and mediation analysis were conducted to assess associations.

RESULTS

The final sample included 32,715 individuals aged ≥50 years with preservation in functional abilities [mean (standard deviation) age 62.1 (15.6) years; 48.3% males]. Country-wise analysis showed a positive association between anxiety and MCI in all countries (OR 1.35-14.33). The pooled estimate based on meta-analysis with random effects was OR=2.27 (95%CI=1.35-3.83). Sleep problems explained 41.1% of this association.

CONCLUSIONS

Older adults with anxiety had higher odds for MCI in LMICs. Future studies should examine whether preventing anxiety or addressing anxiety among individuals with MCI can lead to lower risk for dementia onset in LMICs, while the role of sleep problems in this association should be investigated in detail.

Benzodiazepines and antidepressants: Effects on cognitive and functional decline in Alzheimer's disease and Lewy body dementia

OBJECTIVES

We aim to study the effects of the prescription of benzodiazepines and antidepressants on cognitive and functional decline in older adults living with Alzheimer's disease (AD) and Lewy body dementia (LBD) over a 5-year follow-up.

METHODS

This is a longitudinal analysis of a Norwegian cohort study entitled "The Dementia Study of Western Norway" (DemVest). We included 196 patients newly diagnosed with AD (n = 111) and LBD (n = 85), followed annually for 5 years. Three prescription groups were defined: only benzodiazepines (BZD), only antidepressants (ADep), and the combination of benzodiazepines and antidepressants (BZD-ADep). Linear mixed-effects models were conducted to analyze the effect of the defined groups on the outcomes. The outcomes were functional decline, measured by the Rapid Disability Rating Scale-2, and cognition measured with the Mini-Mental State Examination.

RESULTS

Prescription of the combination of benzodiazepines and antidepressants in LBD was associated with faster functional decline. In AD, the prescription of BZD and BZD-ADep was associated with greater functional deterioration. ADep alone did not show positive or negative significant associations with the studied outcomes.

CONCLUSIONS

BZD and especially the combination of BZD and ADep are associated with functional decline in AD and LBD and should be used cautiously.

Neuropsychiatric profiles and conversion to dementia in mild cognitive impairment, a latent class analysis

Neuropsychiatric symptoms (NPS) have been recently addressed as risk factors of conversion to Alzheimer's disease (AD) and other dementia types in patients diagnosed with Mild Cognitive Impairment (MCI). Our aim was to determine profiles based on the prominent NPS in MCI patients and to explore the predictive value of these profiles on conversion to specific types of dementia. A total of 2137 MCI patients monitored in a memory clinic were included in the study. Four NPS profiles emerged (classes), which were defined by preeminent symptoms: Irritability, Apathy, Anxiety/Depression and Asymptomatic. Irritability and Apathy were predictors of conversion to dementia (HR = 1.43 and 1.56, respectively). Anxiety/depression class showed no risk effect of conversion when compared to Asymptomatic class. Irritability class appeared as the most discriminant neuropsychiatric condition to identify non-AD converters (i.e., frontotemporal dementia, vascular dementia, Parkinson's disease and dementia with Lewy Bodies). The findings revealed that consistent subgroups of MCI patients could be identified among comorbid basal NPS. The preeminent NPS showed to behave differentially on conversion to dementia, beyond AD. Therefore, NPS should be used as early diagnosis facilitators, and should also guide clinicians to detect patients with different illness trajectories in the progression of MCI.

Prevalence of mild behavioural impairment: a systematic review and meta-analysis

AIM

Mild behavioural impairment (MBI) is a neurobehavioural syndrome characterized by emergent neuropsychiatric symptoms in later life. There has been no systematic review or meta-analysis on the prevalence of MBI. The main aim of the study is to calculate the pooled prevalence of MBI.

METHODS

A search of the literature on MBI in mild cognitive impairment (MCI), cognitively normal (CN), and subjective cognitive impairment (SCI) and CN but at risk (CN-AR) subjects published between 1 January 2003 and 28 September 2020 was conducted. Meta-analysis using a random effects model was performed to determine the pooled estimate of the prevalence of MBI. Meta-regression was performed to identify factors contributing to the variance of prevalence rate. A systematic review was also performed to study the impact of MBI in cognitive outcomes and its correlation to the pathology and genetics of Alzheimer's disease.

RESULTS

Eleven studies conducted among 15 689 subjects underwent meta-analysis, revealing the pooled prevalence of MBI to be 33.5% (95% confidence interval (CI): 22.6%-46.6%). Seven studies conducted among 1358 MCI subjects underwent meta-analysis, revealing the pooled prevalence to be 45.5% (95%CI: 36.1%-55.3%). Four studies conducted among 13 153 CN subjects underwent meta-analysis, revealing the pooled prevalence to be 17.0% (95%CI: 7.2%-34.9%). Five studies conducted among 1158 SCI or CN-AR subjects underwent meta-analysis, revealing the pooled prevalence to be 35.8% (95%CI: 21.4%-53.2%). A systematic review of 13 studies showed that MBI has a significant impact on cognitive deterioration and is associated with the pathology and genetics of Alzheimer's disease.

CONCLUSIONS

In MCI, CN, and SCI and CN-AR subjects, MBI is common. Our finding is potentially useful in planning future clinical trials.

Neuropsychiatric Symptoms by Cognitive Status for Mexican-Americans Aged 85 and Older

Few studies have investigated the relationship between neuropsychiatric symptoms (NPS) and cognitive status among older Mexican-American adults. Our objective was to describe the NPS of Mexican-Americans 85 years and older according to cognitive status. Data came from Wave 9 (conducted in 2016) of the Hispanic Established Populations for the Epidemiological Study of the Elderly. The final sample consisted of 381 care recipients ≥85 years. The 12-item Neuropsychiatric Inventory was administered to measure NPS among care recipients. Cognitive impairment was defined as a score of ≤18 on the Mini Mental State Exam or by clinical diagnosis of dementia as reported by the caregiver. Logistic regression models were used to estimate the average marginal effect (range = -1 to 1) of cognitive impairment on NPS, controlling for care-recipient characteristics. Overall, 259 (68.0%) participants had one or more NPS. Approximately 87% of care recipients with cognitive impairment had at least one NPS compared to 55.8% of those without cognitive impairment (p < .01). The predicted probability of having one or more NPS was 0.25% points (95% CI = 0.14-0.35) higher for participants with cognitive impairment than those without. NPS are present in the majority of very old Mexican American adults, particularly in those with cognitive impairment.

Predementia constructs: Mild cognitive impairment or mild neurocognitive disorder? A narrative review

BACKGROUND

Predementia is a heuristic umbrella concept to classify older adults with cognitive impairment who do not suffer dementia. Many diagnostic entities have been proposed to address this concept, but most of them have not had widespread acceptance.

AIMS

To review clinical definitions, epidemiologic data (prevalence, incidence) and rate of conversion to dementia of the main predementia constructs, with special interest in the two most frequently used: mild cognitive impairment (MCI) and minor neurocognitive disorder (miNCD).

METHODS

We have selected in three databases (MEDLINE, Web of Science and Google scholar) the references from inception to 31 December 2019 of relevant reviews, population and community-based surveys, and clinical series with >500 participants and >3 years follow-up as the best source of evidence.

MAIN RESULTS

The history of predementia constructs shows that MCI is the most referred entity. It is widely recognized as a clinical syndrome harbinger of dementia of several etiologies, mainly MCI due to Alzheimer's disease. The operational definition of MCI has shortcomings: vagueness of its requirement of "preserved independence in functional abilities" and others. The recent miNCD construct presents analogous difficulties. Current data indicate that it is a stricter predementia condition, with lower prevalence than MCI, less sensitivity to cognitive decline and, possibly, higher conversion rate to dementia.

CONCLUSIONS

MCI is a widely employed research and clinical entity. Preliminary data indicate that the clinical use of miNCD instead of MCI requires more scientific evidence. Both approaches have common limitations that need to be addressed.

Alterations of Brain Networks in Alzheimer's Disease and Mild Cognitive Impairment: A Resting State fMRI Study Based on a Population-specific Brain Template

This study aimed to investigate the alterations in brain networks in patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) based on a population-specific brain template. Previous studies on AD brain networks using graph theory rarely adopted brain templates specific for certain ethnicities. In this study, patients were divided into 3 groups: AD (n = 24), MCI (n = 27), and healthy controls (HCs, n = 33), and all of the subjects are Chinese. Functional brain networks were constructed for each group based on a Chinese brain template using resting-state functional magnetic resonance imaging (rs-fMRI) data; several graph metrics were calculated. Graph metrics with significant differences after false discovery rate (FDR) correction were analyzed with respect to correlations with four neuropsychological test scores: Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Activities of Daily Living (ADL), and Clinical Dementia Rating (CDR), which assessed the subjects' cognitive functions and ability to engage in ADL. Graph metrics including assortativity coefficient, nodal degree centrality, nodal clustering coefficient, nodal efficiency, and nodal local efficiency of the frontal gyrus and cerebellum were significantly altered in AD and MCI compared with HC. Several graph metrics were significantly correlated with cognitive function and the ability to engage in daily activities. The findings suggest that altered graph metrics in the frontal gyrus may reflect brain plasticity, and that patients with MCI may have unique graph metric alterations in the cerebellum. Future graph analysis studies on functional brain networks in AD and MCI based on population-specific brain atlases for particular ethnicities may prove valuable.

Memantine, Donepezil, or Combination Therapy-What is the best therapy for Alzheimer's Disease? A Network Meta-Analysis

INTRODUCTION

Alzheimer's disease (AD) is a degenerative brain disease that progresses over time, heavily burdening patients, families, and aging societies worldwide. Memantine and donepezil are frequently used in its treatment, both as monotherapy and in combination. This multiple treatment comparison meta-analysis assessed the efficacy of these regimens and placebo in the management of AD.

METHODS

We searched PubMed, Embase, the Cochrane Library, and Wanfang Med Online and China National Knowledge Infrastructure for English and Chinese publications from the first records to 17 April 2020. Two investigators scanned articles for placebo-controlled trials of memantine and donepezil alone and in combination. We extracted data on the following outcomes: cognition, global assessment, daily activities, neuropsychiatric symptoms, adverse events, and the acceptability and cost of these treatment regimens.

RESULTS

Of 936 records screened, we included 54 trials in this analysis. The combination therapy was more effective in improving cognition (mean difference (MD)-5.01, 95% credible interval (95% Crl) -10.73 to 0.86 in the Alzheimer's Disease Assessment Scale-Cognitive Subscale; MD 9.61, 95% Crl 2.29 to 16.97 in the Severe Impairment Battery), global assessment (MD -2.88, 95% Crl -6.04 to 0.40), daily activities (MD 13.06, 95% Crl -34.04 to 58.92), and neuropsychiatric symptoms (MD -6.84, 95% Crl -10.62 to -2.82) compared with placebo. Memantine was more acceptable than placebo (MD 0.93, 95% Crl 0.69 to 1.22).

CONCLUSIONS

Memantine plus donepezil showed superior outcomes for cognition, global assessment, daily activities, and neuropsychiatric symptoms, but lower acceptability than monotherapy and placebo. Combination therapy may be more cost-effective, because memantine slows the progression of AD.