Baseline Clinical Dementia Rating Research Articles

Brain Age Is Associated with Cognitive Outcomes of Cholinesterase Inhibitor Treatment in Patients with Mild Cognitive Impairment.

The effect of cholinesterase inhibitor (ChEI) on mild cognitive impairment (MCI) is controversial. Brain age has been shown to predict Alzheimer's disease conversion from MCI. The study aimed to show that brain age is related to cognitive outcomes of ChEI treatment in MCI. Brain MRI, the Clinical Dementia Rating (CDR) and Mini-Mental State Exam (MMSE) scores were retrospectively retrieved from a ChEI treatment database. Patients who presented baseline CDR of 0.5 and received ChEI treatment for at least 2 years were selected. Patients with stationary or improved cognition as verified by the CDR and MMSE were categorized to the ChEI-responsive group, and those with worsened cognition were assigned to the ChEI-unresponsive group. A gray matter brain age model was built with a machine learning algorithm by training T1-weighted MRI data of 362 healthy participants. The model was applied to each patient to compute predicted age difference (PAD), i.e. the difference between brain age and chronological age. The PADs were compared between the two groups. 58 patients were found to fit the ChEI-responsive criteria in the patient data, and 58 matched patients that fit the ChEI-unresponsive criteria were compared. ChEI-unresponsive patients showed significantly larger PAD than ChEI-responsive patients (8.44±8.78 years versus 3.87±9.02 years, p = 0.0067). Gray matter brain age is associated with cognitive outcomes after 2 years of ChEI treatment in patients with the CDR of 0.5. It might facilitate the clinical trials of novel therapeutics for MCI.

Apathy in Lewy body disease and its effects on functional impairment over time.

Apathy strongly affects function in Alzheimer's disease and frontotemporal dementia, however its effect on function in Lewy Body Disease (LBD) has not been well-described. This study aims to (1) examine the prevalence and persistence of apathy in a large, national cohort of well-characterized patients with LBD, and (2) estimate the effect of apathy on function over time. Study included 676 participants with mild cognitive impairment (MCI) or dementia in the National Alzheimer's Coordinating Center Uniform Data Set. Participants were followed for an average of 3.4 ± 1.7 years and consistently had a primary diagnosis of LBD. Apathy was defined by clinician judgment, categorized into four mutually exclusive profiles: (1) never apathetic across all visits, (2) at least one but <50% of visits with apathy (intermittent apathy), (3) ≥50% but not all visits with apathy (persistent apathy), and (4) always apathy across all visits. Dementia severity was measured by baseline Clinical Dementia Rating score. Parkinsonism was defined by the presence of bradykinesia, resting tremor, rigidity, gait, and postural instability. Functional impairment was assessed using the Functional Assessment Questionnaire (FAQ). Baseline characteristics of the sample were: average age = 72.9 ± 6.9, years of education = 15.6 ± 3.4, Mini Mental State Exam (MMSE) = 24.4 ± 5.4, Geriatric Depression Scale (GDS) = 3.8 ± 3.2, FAQ = 12.0 ± 9.1. 78.8% were male and 89% were non-Hispanic white. Prevalence of apathy increased from 54.4% at baseline to 65.5% in year 4. 77% of participants had apathy at some point during follow-up. Independent of cognitive status and parkinsonian features, FAQ was significantly higher in participants with intermittent/persistent and always apathetic than never apathetic. Annual rate of decline in FAQ was faster in participants who were always apathetic than never apathy. In this large national longitudinal cohort of LBD patients with cognitive impairment, apathy was strongly associated with greater functional impairment at baseline and faster rate of decline over time. The magnitude of these effects were clinically important and were observed beyond the effects on function from participants' cognitive status and parkinsonism, highlighting the importance of specifically assessing for apathy in LBD.

A novel approach to measure dyadic patterns of subjective cognitive changes: its association to Alzheimer’s disease biomarkers and ability to predict clinical progression in cognitively normal older adults

AbstractBackgroundDiscrepancy in the dyadic relationship of subjective cognitive change has revealed both increased/heightened awareness and decreased awareness/unawareness in the predementia stages of Alzheimer’s Disease (AD). The dyadic relationship is often calculated using the mean discrepancy between an individual and their study partner’s scores on a memory complaints questionnaire. However, participants may display heightened awareness on some questions and unawareness on others, canceling out each other’s effect and masking subtle changes in either direction. Here, we present a new item‐level methodological approach allowing us to examine individual subtle changes in these two awareness dimensions separately. Moreover, we compared them to AD pathology and investigated their ability to predict clinical progression.MethodA total of 503 ADNI participants (Table.1) with baseline clinical dementia rating (CDR) = 0 and baseline CSF (Aβ1‐42 and t‐tau) were included. A subset (N = 329) had at least two follow‐up CDR time points to compute clinical progression. A traditional score was calculated as the average discrepancy between the partner and participant’s responses on the Everyday Cognition questionnaire, with positive scores indicating heightened awareness and negative scores indicating unawareness. An unawareness (resp., heightened awareness) sub‐score was computed by applying a ceiling (resp., floor) at zero to item‐level differences before averaging. Each measure was compared by AD pathology, adjusted for age and sex. Survival analyses examined the relationship of the new scores with clinical progression.ResultCSF t‐tau, but not Aβ1‐42, was a significant independent predictor of the traditional and unawareness scores in models adjusting for each other. There was no significant interaction between the two (Table.2). Survival analyses showed a one‐point improvement on the unawareness sub‐score associated with an 84% reduction in progression hazard (HR = 0.16, p&lt;0.001), or equivalently. A one‐point decline and 525% increase in progression hazard, with no significant effect for the heightened awareness score.ConclusionDecomposing the traditional awareness score into two sub‐scores, allowed the investigation of the relationship between AD and awareness with more specific, sensitive measures. Of these, the unawareness sub‐score was associated with t‐tau and a strong predictor of clinical progression, providing further support that discordant self‐ and informant‐reported cognitive decline may provide important clinical information.

Anosognosia is associated with increased prevalence and faster development of neuropsychiatric symptoms in Mild Cognitive Impairment

AbstractBackgroundBoth the loss of awareness for cognitive decline (a.k.a anosognosia) and neuropsychiatric symptoms (NPS) are commonly seen in patients with Alzheimer’s disease (AD) dementia, even in the prodromal stages. Anosognosia and NPS may negatively affect caregiver burden and patient’s activities of daily living. Despite the high impact of these symptoms on patients and their caregivers, our knowledge of how they develop across the AD spectrum is limited. Here, we explored the cross‐sectional and longitudinal associations between anosognosia and NPS in individuals with mild cognitive impairment (MCI).MethodWe included 310 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) with a baseline Clinical Dementia Rating global score of 0.5. Everyday Cognition (ECog) questionnaire scores were used to measure complaints from participants and study‐partners at baseline and annually over a mean of 4 years (SD = 3). Anosognosia was defined as the study‐partner having an ECog score ≥2.5/4 and the participant having an ECog score ≤2.5/4 on their baseline measure and their last observation and without having more than 2 consecutive deviating observations during the follow‐up period. The 12 study‐partner‐rated Neuropsychiatric Inventory items determined the presence or absence of specific NPS (see Table 1). The Mini‐Mental State Examination (MMSE), an assessment used to screen for cognitive impairment, was administered annually. Survival analyses were performed to analyze the rate of appearance of NPS over time in individuals with and without anosognosia.ResultSixty participants displayed anosognosia, while 250 did not. At baseline, groups had similar lengths of follow‐up. Participants with anosognosia had lower MMSE scores and a higher proportion of amyloid positivity (see Table 1). At baseline, the frequency of agitation and disinhibition was higher in the anosognosia group. Survival analyses showed earlier onset of all NPS in the anosognosia group (see Figure 1). Specifically, aberrant motor behavior, irritability, disinhibition, apathy, agitation, and hallucinations were highly significant.ConclusionLoss of awareness for cognitive decline is associated with greater frequency and faster onset of NPS over time in participants with MCI. These results support the hypothesis of a potential common underlying neurophysiological process, a finding that needs to be addressed further in future studies.

Assessing Risk of Incident Cognitive Impairment Using Stages of Objective Memory Impairment (SOMI) and Cerebrospinal Fluid

AbstractBackgroundThe asymptomatic period for persons with preclinical Alzheimer’s disease (AD) lasts for several years despite the presence of AD biomarkers. These biomarkers are critical for disease detection and monitoring, but collection is burdensome and costly. Sensitive cognitive measures such as Stages of Objective Memory Impairment (SOMI) may be a low‐cost alternative or adjunctive marker of disease‐progression risk. Here, we used longitudinal data from the Knight Alzheimer’s Disease Research Center to investigate the odds of disease progression associated with baseline SOMI stage and cerebrospinal fluid (CSF) biomarkers of Aβ42/Aβ40 ratio, p‐tau181, and t‐tau.MethodsWe used data from 617 cognitively unimpaired participants with baseline Clinical Dementia Rating (CDR) of 0, CSF measures, and longitudinal Free and Cued Selective Reminding Test (FCSRT) scores used to classify participants into different SOMI stages (Table 1). We examined the association between SOMI stage, CSF biomarkers, and incident cognitive impairment based on time to conversion from CDR of 0 to CDR&gt;0 (incident cognitive impairment) using Cox Models.ResultsParticipants, at enrollment (Table 2), were on average 67.2 (SD = 9.4) years old, 56.6% were female, and had average 7.5 years of follow‐up (range 1‐18). At baseline, 325 (52.7%) were SOMI‐0, 206 (33.4%) were SOMI‐1, 64 (10.4%) were SOMI‐2, and 22 (3.6%) were SOMI‐3 or ‐4 (merged groups). A total of 127 (20.6%) individuals converted to CDR&gt;0. The Cox proportional hazards regression models indicated that in comparison with individuals in SOMI‐0 stage, those in SOMI‐3/4 stage were more than twice as likely to show disease progression (HR=2.43 (95% CI, 1.21‐4.89, p=0.013)) (Table 3). Adding individual CSF biomarkers to the models did not affect the association of SOMI‐3/4 with incident cognitive impairment (p&lt;0.05 for all). In models that included SOMI stages and all CSF biomarkers, SOMI‐3/4 (HR=2.13, 95% CI 1.07‐4.12, p=0.033) Aβ42/Aβ40 (HR=9.76e‐6, 95% CI=2.70e‐10 ‐ 0.35, p=0.031) and t‐tau (HR=1.001, 95% CI=1.000‐1.002, p=0.018), but not p‐tau (p=0.645), showed significant association with incident cognitive impairment.ConclusionsSOMI‐3/4 predicts incident cognitive impairment (change in CDR) independently from CSF AD biomarkers. These results support the utility of SOMI stage as an early marker of incident cognitive impairment.

Sum of boxes of the clinical dementia rating scale highly predicts conversion or reversion in predementia stages.

BackgroundThe clinical dementia rating (CDR) scale is commonly used to diagnose dementia due to Alzheimer’s disease (AD). The sum of boxes of the CDR (CDR-SB) has recently been emphasized and applied to interventional trials for tracing the progression of cognitive impairment (CI) in the early stages of AD. We aimed to study the influence of baseline CDR-SB on disease progression to dementia or reversion to normal cognition (NC).Materials and methodsThe baseline CDR < 1 cohort registered from September 2015 to August 2020 with longitudinal follow-up in the History-based Artificial Intelligence Clinical Dementia Diagnostic System (HAICDDS) database was retrospectively analyzed for the rates of conversion to CDR ≥ 1. A Cox regression model was applied to study the influence of CDR-SB levels on progression, adjusting for age, education, sex, neuropsychological tests, neuropsychiatric symptoms, parkinsonism, and multiple vascular risk factors.ResultsA total of 1,827 participants were analyzed, including 1,258 (68.9%) non-converters, and 569 (31.1%) converters with mean follow-up of 2.1 (range 0.4–5.5) and 1.8 (range 0.3–5.0) years, respectively. Conversion rates increased with increasing CDR-SB scores. Compared to a CDR-SB score of 0, the hazard ratios (HR) for conversion to dementia were 1.51, 1.91, 2.58, 2.13, 3.46, 3.85, 3.19, 5.12, and 5.22 for CDR-SB scores of 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, and ≥4.5, respectively (all p < 0.05 except for CDR-SB score = 0.5). In addition, older age, lower education, lower cognitive performance, and a history of diabetes also increased conversion rates. Furthermore, reversions to NC were 12.5, 5.6, 0.9, and 0% for CDR-SB scores of 0.5, 1.0–2.0, 2.5–3.5 and ≥4.0, respectively (p < 0.001).ConclusionCDR-SB in predementia or very mild dementia (VMD) stages highly predicts progression to dementia or reversion to NC. Therefore, CDR-SB could be a good candidate for tracing the effectiveness of pharmacological and non-pharmacological interventions in populations without dementia.

Independent replication of advanced brain age in mild cognitive impairment and dementia: detection of future cognitive dysfunction

We previously developed a novel machine-learning-based brain age model that was sensitive to amyloid. We aimed to independently validate it and to demonstrate its utility using independent clinical data. We recruited 650 participants from South Korean memory clinics to undergo magnetic resonance imaging and clinical assessments. We employed a pretrained brain age model that used data from an independent set of largely Caucasian individuals (n = 757) who had no or relatively low levels of amyloid as confirmed by positron emission tomography (PET). We investigated the association between brain age residual and cognitive decline. We found that our pretrained brain age model was able to reliably estimate brain age (mean absolute error = 5.68 years, r(650) = 0.47, age range = 49–89 year) in the sample with 71 participants with subjective cognitive decline (SCD), 375 with mild cognitive impairment (MCI), and 204 with dementia. Greater brain age was associated with greater amyloid and worse cognitive function [Odds Ratio, (95% Confidence Interval {CI}): 1.28 (1.06–1.55), p = 0.030 for amyloid PET positivity; 2.52 (1.76–3.61), p < 0.001 for dementia]. Baseline brain age residual was predictive of future cognitive worsening even after adjusting for apolipoprotein E e4 and amyloid status [Hazard Ratio, (95% CI): 1.94 (1.33–2.81), p = 0.001 for total 336 follow-up sample; 2.31 (1.44–3.71), p = 0.001 for 284 subsample with baseline Clinical Dementia Rating ≤ 0.5; 2.40 (1.43–4.03), p = 0.001 for 240 subsample with baseline SCD or MCI]. In independent data set, these results replicate our previous findings using this model, which was able to delineate significant differences in brain age according to the diagnostic stages of dementia as well as amyloid deposition status. Brain age models may offer benefits in discriminating and tracking cognitive impairment in older adults.

Brain Age Difference at Baseline Predicts Clinical Dementia Rating Change in Approximately Two Years.

The Clinical Dementia Rating (CDR) has been widely used to assess dementia severity, but it is limited in predicting dementia progression, thus unable to advise preventive measures to those who are at high risk. Predicted age difference (PAD) was proposed to predict CDR change. All diffusion magnetic resonance imaging and CDR scores were obtained from the OASIS-3 databank. A brain age model was trained by a machine learning algorithm using the imaging data of 258 cognitively healthy adults. Two diffusion indices, i.e., mean diffusivity and fractional anisotropy, over the whole brain white matter were extracted to serve as the features for model training. The validated brain age model was applied to a longitudinal cohort of 217 participants who had CDR = 0 (CDR0), 0.5 (CDR0.5), and 1 (CDR1) at baseline. Participants were grouped according to different baseline CDR and their subsequent CDR in approximately 2 years of follow-up. PAD was compared between different groups with multiple comparison correction. PADs were significantly different among participants with different baseline CDRs. PAD in participants with relatively stable CDR0.5 was significantly smaller than PAD in participants who had CDR0.5 at baseline but converted to CDR1 in the follow-up. Similarly, participants with relatively stable CDR0 had significantly smaller PAD than those who were CDR0 at baseline but converted to CDR0.5 in the follow-up. Our results imply that PAD might be a potential imaging biomarker for predicting CDR outcomes in patients with CDR0 or CDR0.5.

Detecting speech and language changes in early AD via automated analysis of clinical interviews

AbstractBackgroundChanges to speech and language patterns in Alzheimer’s disease (AD) may provide sensitive indicators of cognitive decline that could be automatically and objectively detected with speech analysis technology that incorporates natural language processing. In this study, we sought to determine whether analyses of audio recordings of open‐ended Clinical Dementia Rating (CDR) interviews collected as part of a Phase 2 clinical trial in prodromal‐to‐mild AD could identify speech and language characteristics relevant to clinical status.MethodSpeech recordings from baseline CDR interviews were analyzed for 101 English‐speaking AD participants (58F/43M; 30 prodromal/71 mild; mean age = 69 years, range: 53‐80) in the semorinemab (NCT03289143) Phase 2 Tauriel study. Recordings of the CDR interview were analyzed using the Winterlight speech analysis platform, which generates &gt;500 variables describing acoustic and linguistic features of speech. We computed Pearson correlations between the speech variables and five clinical measures (CDR, ADAS‐Cog, RBANS, MMSE, ADCS‐ADL) to identify specific features related to clinical performance.ResultCDR‐SB scores correlated more strongly with linguistic variables (e.g., types of words used, complexity of language) than acoustic variables. Participants with higher CDR‐SB scores (i.e., greater cognitive/functional impairment), used fewer past tense verbs when describing a recent event, a lower proportion of nouns compared to verbs, and shorter and simpler grammatical clauses (all r’s &gt; 0.3, p’s &lt; 0.05, FDR‐corrected). Similar associations were seen with other clinical assessments, and a subset of linguistic variables demonstrated significant (p &lt; 0.05, uncorrected) correlations with all five clinical measures, including clause length, and use of prepositional phrases.ConclusionThese analyses demonstrate that clinical interviews can be analyzed using objective automatic methods to generate speech variables relevant to clinical outcomes in AD. Individuals with greater cognitive and functional impairment used simpler language and fewer content words when describing a recent experience. Future work will include multivariate analyses of speech markers versus cross‐sectional clinical indices.

Personalized prediction of progression in pre-dementia patients based on individual biomarker profile: A development and validation study.

The prognosis of patients at the pre-dementia stage is difficult to define. The aim of this study is to develop and validate a biomarker-based continuous model for predicting the individual cognitive level at any future moment. In addition to personalized prognosis, such a model could reduce trial sample size requirements by allowing inclusion of a homogenous patient population. Disease-progression modeling of longitudinal cognitive scores of pre-dementia patients (baseline Clinical Dementia Rating ≤ 0.5) was used to derive a biomarker profile that was predictive of patient's cognitive progression along the dementia continuum. The biomarker profile model was developed and validated in the MEMENTO cohort and externally validated in the Alzheimer's Disease Neuroimaging Initiative. Of nine candidate biomarkers in the development analysis, three cerebrospinal fluid and two magnetic resonance imaging measures were selected to form the final biomarker profile. The model-based prognosis of individual future cognitive deficit was shown to significantly improve when incorporating biomarker information on top of cognition and demographic data. In trial power calculations, adjusting the primary analysis for the baseline biomarker profile reduced sample size requirements by ≈10%. Compared to conventional cognitive cut-offs, inclusion criteria based on biomarker-profile cut-offs resulted in up to 28% reduced sample size requirements due to increased homogeneity in progression patterns. The biomarker profile allows prediction of personalized trajectories of future cognitive progression. This enables accurate personalized prognosis in clinical care and better selection of patient populations for clinical trials. A web-based application for prediction of patients' future cognitive progression is available online.

Apolipoprotein E e4 allele is associated with extrapyramidal symptoms in Alzheimer's disease.

BackgroundExtrapyramidal symptoms (EPS) are not uncommon in Alzheimer’s disease (AD). As apolipoprotein E(APOE) e4 allele is a major risk factor for late-onset AD, we intend to examine the association between APOE genotype and the development of EPS in AD.MethodThis study describes two hundred and fifty-five clinically diagnosed AD patients aged 72 to 80 years from 2010 to 2014. We reviewed the medical charts to determine the development of EPS. APOE genotypes were also confirmed.ResultsAPOE e4 allele was detected in 74 patients (29%) and rigidity was among the most common EPS (61%). After adjusting the age, gender, baseline clinical dementia rating, we found AD patients carrying APOE e4 allele are more likely to develop EPS (OR: 4.515, p=0.033).ConclusionThis study demonstrates the higher coexistence of EPS in AD patients with APOE e4 allele. Furthermore, the identification of APOE e4 allele in the development of EPS in AD patients supports the hypothesis that EPS may be partially attributed to AD pathology.

Assessment of executive function declines in presymptomatic and mildly symptomatic familial frontotemporal dementia: NIH-EXAMINER as a potential clinical trial endpoint

IntroductionIdentifying clinical measures that track disease in the earliest stages of frontotemporal lobar degeneration (FTLD) is important for clinical trials. Familial FTLD provides a unique paradigm to study early FTLD. Executive dysfunction is a clinically relevant hallmark of FTLD and may be a marker of disease progression. MethodsNinety-three mutation carriers with no symptoms or minimal/questionable symptoms (MAPT, n = 31; GRN, n = 28; C9orf72, n = 34; Clinical Dementia Rating scale plus NACC FTLD Module < 1) and 78 noncarriers enrolled through Advancing Research and Treatment in Frontotemporal Lobar Degeneration/Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects studies completed the Executive Abilities: Measures and Instruments for Neurobehavioral Evaluation and Research (NIH-EXAMINER) and the UDS neuropsychological battery. Linear mixed-effects models were used to identify group differences in cognition at baseline and longitudinally. We examined associations between cognition, clinical functioning, and magnetic resonance imaging volumes. ResultsNIH-EXAMINER scores detected baseline and differences in slopes between carriers and noncarriers, even in carriers with a baseline Clinical Dementia Rating scale plus NACC FTLD Module = 0. NIH-EXAMINER declines were associated with worsening clinical symptoms and brain volume loss. DiscussionThe NIH-EXAMINER is sensitive to cognitive changes in presymptomatic familial FTLD and is a promising surrogate endpoint.

Cerebral white matter free water: A sensitive biomarker of cognition and function.

To determine whether free water (FW) content, initially developed to correct metrics derived from diffusion tensor imaging and recently found to be strongly associated with vascular risk factors, may constitute a sensitive biomarker of white matter (WM) microstructural differences associated with cognitive performance but remains unknown. Five hundred thirty-six cognitively diverse individuals, aged 77 ± 8 years, received yearly comprehensive clinical evaluations and a baseline MRI examination of whom 224 underwent follow-up MRI. WM microstructural measures, including FW, fractional anisotropy, and mean diffusivity corrected for FW and WM hyperintensity burden were computed within WM voxels of each individual. Baseline and change in MRI metrics were then used as independent variables to explain baseline and change in episodic memory (EM), executive function (EF), and Clinical Dementia Rating (CDR) scores using linear, logistic, and Cox proportional-hazards regressions. Higher baseline FW and WM hyperintensity were associated with lower baseline EM and EF, higher baseline CDR, accelerated EF and EM decline, and higher probability to transition to a more severe CDR stage (p values <0.01). Annual change in FW was also found to be associated with concomitant change in cognitive and functional performance (p values <0.01). This study finds cross-sectional and longitudinal associations between FW content and trajectory of cognitive and functional performance in a large sample of cognitively diverse individuals. It supports the need to investigate the pathophysiologic process that manifests increased FW, potentially leading to more severe WM territory injury and promoting cognitive and functional decline.

Interactive versus additive relationships between regional cortical thinning and amyloid burden in predicting clinical decline in mild AD and MCI individuals.

The biological mechanisms that link Beta-amyloid (Aβ) plaque deposition, neurodegeneration, and clinical decline in Alzheimer's disease (AD) dementia, have not been completely elucidated. Here we studied whether amyloid accumulation and neurodegeneration, independently or interactively, predict clinical decline over time in a group of memory impaired older individuals [diagnosed with either amnestic mild cognitive impairment (MCI), or mild AD dementia]. We found that baseline Aβ-associated cortical thinning across clusters encompassing lateral and medial temporal and parietal cortices was related to higher baseline Clinical Dementia Rating Sum-of-Boxes (CDR-SB). Baseline Aβ-associated cortical thinning also predicted CDR-SB over time. Notably, the association between CDR-SB change and cortical thickness values from the right lateral temporo-parietal cortex and right precuneus was driven by individuals with high Aβ burden. In contrast, the association between cortical thickness in the medial temporal lobe (MTL) and clinical decline was similar for individuals with high or low Aβ burden. Furthermore, amyloid pathology was a stronger predictor for clinical decline than MTL thickness. While this study validates previous findings relating AD biomarkers of neurodegeneration to clinical impairment, here we show that regions outside the MTL may be more vulnerable and specific to AD dementia. Additionally, excluding mild AD individuals revealed that these relationships remained, suggesting that lower cortical thickness values in specific regions, vulnerable to amyloid pathology, predict clinical decline already at the prodromal stage.

SHORT-TERM PREDICTION OF CONVERSION FROM MILD COGNITIVE IMPAIRMENT TO DEMENTIA IN PATIENTS IN THE MEMENTO COHORT, 2011-2016

Limited knowledge is available on models able to combine all potential biomarkers and evaluate their respective role on top of clinical and neuro-psychological examinations to predict conversion from mild cognitive impairment (MCI) to dementia, including of Alzheimer's disease (AD). We used data of the nation-wide Memento cohort, which consecutively recruited 2323 participants in 28 memory clinics for either isolated cognitive complaints MCI, while not demented. In participants with baseline Clinical Dementia Rating (CDR) = 0.5, a short-term clinical prediction model of conversion to dementia was built using primarily socio-demographic characteristics, personal and family medical history, neurological and physical examination (including cardiovascular risk factors), and cognitive performances assessed by an extensive neuropsychological battery. The added values of APOE ε4 carrier status and MRI biomarkers (brain parenchymal fraction, hippocampal volume, white matter lesions) on prediction abilities were then evaluated. All models were adjusted for age and sex. Overall, 1374 participants had a baseline CDR=0.5 (mean age 71 years, 60% women). During a mean 2.8 years of follow-up, 189 individuals became demented (133 Alzheimer's dementia cases) yielding an incidence of 49.5 per 1000 person-years. The best predictive clinical model (C-statistic 0.87, 95% Confidence interval (CI), 0.84 to 0.91) included: visit at clinic motivated by behavioral disorders, lower physical complaints, lower performances at cognitive tests (MMSE, gestural praxis, Copy of Rey-Osterrieth complex figure at 3 minutes, Free and cued total immediate recalls test, time to perform Trail Making Test part A), limitations at Instrumental Activities of Daily Living (IADL), higher score at short physical performance battery. On top of clinical and neuro-psychological examinations, with at least 1 APOE ε4 allele and lower hippocampal volume were associated with significant improvement of predictive performances (c-statistic 0.89, CI 0.86 to 0.92). Internal validation was performed using bootstrap (1000 iterations/samples). Restricting modelling of conversion to AD did not show difference in the nature of the predictive variables. Excellent performance was found with a model based on a set of variables measured routinely at the clinic, able to accurately predict dementia on the short term.

NEUROPSYCHIATRIC SYMPTOMS AND COGNITIVE DECLINE IN COGNITIVELY NORMAL ELDERLY: THE CACHE COUNTY STUDY OF AGING

NPS are well-replicated risk factors for cognitive and functional decline in prodromal Alzheimer's disease (AD) and there is stronge vidence that they have similar effects in cognitively older normal adults. We sought to examine these associations in the Cache County Study of Aging. A population-based sample of all residents > 65 years old in Cache County, Utah (USA) was evaluated with a multi-stage dementia screen and diagnoses adjudicated by a multidisciplinary geriatric specialty team. Participants were included in this analysis if the consensus diagnosis was cognitively normal, based on all available data. Assessments were performed 3–4 times 3–4 years apart. NPS were assessed with the Neuropsychiatric Inventory (NPI) and cognition with Mini-Mental State Exam (MMSE). MMSE trajectories were estimated with mixed-effects models, assessing the effect of baseline NPI domains scores and controlling for age, education, and gender. 470 cognitively normal participants (58% female) had mean(SD) age of 79 (7.8) years, 13.2 (3.0) years education, baseline MMSE of 27.3 (2.4), and baseline Clinical Dementia Rating Sum of Boxes of 0.54 (2.0). Baseline NPI scores were low with only 4.6% reporting depression and 4.0% reporting anxiety. Baseline NPI delusion and irritability scores were significantly associated with poorer cognition (lower MMSE). Similar results were observed if one coded NPI scores dichotomously as 0 vs. > 0. In this cognitively normal population-based sample, delusions and irritability were associated with poorer cognitive and functional outcomes most likely representing both non-AD and AD trajectories. These results will be contrasted and discussed in the context of findings from other large epidemiological cohorts demonstrating NPS-related progression in preclinical AD.

Effects of frequent and long-term exercise on neuropsychiatric symptoms in patients with Alzheimer's disease – Secondary analyses of a randomized, controlled trial (FINALEX)

BackgroundNeuropsychiatric symptoms (NPS) are common in Alzheimer's disease (AD) and are associated with admission to institutional care. Current guidelines recommend non-pharmacological interventions as the first-line treatment for NPS. However, high-quality randomized studies focused on NPS are scarce. The objective here was to examine whether a regular and long-term exercise programme either at home or as a group-based exercise at an adult day care centre has beneficial effects on AD patients’ NPS or permanent institutionalizations. Design, setting, and participantsA randomized, controlled trial with 210 community-dwelling AD patients. InterventionTwo types of intervention comprising (1) group-based exercise in day care centres (GE) and (2) tailored home-based exercise (HE), both twice a week for 12 months, were compared with (3) a control group (CG) receiving usual community care. MeasurementsNPS were measured with the Neuropsychiatric Inventory (NPI) at baseline and 6 months, and depression with the Cornell Scale for Depression in Dementia (CSDD) at baseline and 12 months. Data on institutionalizations were retrieved from central registers. ResultsNo significant differences between the groups were detected in NPI at 6 months or in CSDD at 12 months when analyses were adjusted for age, sex, baseline Clinical Dementia Rating, and Functional Independence Measure. There was no difference in admissions to permanent institutional care between the groups. ConclusionsRegular, long-term exercise intervention did not decrease NPS in patients with AD.

PC-FACS

PC-FACS

The Progression of Alzheimer's Disease Can Be Assessed with a Short Version of the CERAD Neuropsychological Battery: The Kuopio ALSOVA Study

Background/Aims: Measuring and predicting Alzheimer's disease (AD) progression is important in order to adjust treatment and allocate care resources. We aimed to identify a combination of subtests from the Consortium to Establish a Registry for Alzheimer's Disease Neuropsychological Battery (CERAD-NB) that best correlated with AD progression in follow-up as well as to predict AD progression. Method: A total of 236 participants with very mild [Clinical Dementia Rating (CDR) = 0.5] or mild AD (CDR = 1.0) at baseline were followed up for 3 years. The CERAD-NB and Mini-Mental State Examination (MMSE) were used to assess cognition, and the CDR scale sum of boxes (CDR-sb) was employed to evaluate AD progression. Generalized estimating equations were used to develop models to predict and follow up disease progression. Results: Performance declined on all CERAD-NB subtests. The ability of the separate subtests to distinguish between groups (baseline CDR = 0.5 or 1.0) diminished during follow-up. The best combination of subtests that explained 62% of CDR-sb variance in follow-up included verbal fluency, constructional praxis, the clock drawing test, and the MMSE. Baseline values of the same combination predicted 37% of the CDR-sb change. Conclusion: A short version of the CERAD-NB subtests provides a promising and time-efficient alternative for measuring cognitive deterioration during AD follow-up. Although the initial signs of AD include memory difficulties, it may be useful to assess non-memory tasks in follow-up.

The SIST-M

We have previously established the reliability and cross-sectional validity of the SIST-M (Structured Interview and Scoring Tool-Massachusetts Alzheimer's Disease Research Center), a shortened version of an instrument shown to predict progression to Alzheimer disease (AD), even among persons with very mild cognitive impairment (vMCI). To test the predictive validity of the SIST-M. Participants were 342 community-dwelling, nondemented older adults in a longitudinal study. Baseline Clinical Dementia Rating (CDR) ratings were determined by either (1) clinician interviews or (2) a previously developed computer algorithm based on 60 questions (of a possible 131) extracted from clinician interviews. We developed age+sex+education-adjusted Cox proportional hazards models using CDR-sum-of-boxes (CDR-SB) as the predictor, where CDR-SB was determined by either a clinician interview or an algorithm; models were run for the full sample (n = 342) and among those jointly classified as vMCI using clinician-based and algorithm-based CDR ratings (n = 156). We directly compared predictive accuracy using time-dependent receiver operating characteristic (ROC) curves. AD hazard ratios (HRs) were similar for clinician-based and algorithm-based CDR-SB: for a 1-point increment in CDR-SB, the respective HRs [95% confidence interval (CI)] were 3.1 (2.5, 3.9) and 2.8 (2.2, 3.5); among those with vMCI, the respective HRs (95% CI) were 2.2 (1.6, 3.2) and 2.1 (1.5, 3.0). Similarly high predictive accuracy was achieved: the concordance probability (weighted average of the area-under-the-ROC curves) over follow-up was 0.78 versus 0.76 using clinician-based versus algorithm-based CDR-SB. CDR scores based on items from this shortened interview had high predictive ability for AD-comparable to that using a lengthy clinical interview.