Real world clinical practice of lecanemab at PUMCH dementia cohort: focus on dynamic imaging and biomarker evolution.

P185: Comparison of social function in mild cognitive impairment and mild dementia using the Japanese version of the Social Functioning in Dementia scale (SF-DEM-J)

BackgroundTimely diagnosis of Alzheimer's disease (AD) remains challenging in the United Kingdom and improvements are needed with the introduction of new therapies.ObjectiveTo examine the United Kingdom diagnostic and current treatment journey for people with mild cognitive impairment (MCI) and AD dementia to identify future opportunities for new treatments.MethodsPhysician-reported data were drawn from the Adelphi Real World Dementia Disease Specific Programme™, a cross-sectional survey of physicians treating patients with MCI or AD dementia in the United Kingdom between 2022 and 2024. Analyses were descriptive.ResultsPhysicians (n = 109) reported data for 717 patients with MCI or AD dementia (including 264 with MCI or mild dementia). Overall median (interquartile range) time from symptom onset to first consultation was 26.0 (9.1–52.9) weeks. Time from consultation to diagnosis, for patients not diagnosed at initial consultation, was 15.2 (5.1–21.0) weeks for patients who first consulted and were diagnosed by a general practitioner and 21.9 (12.6–39.0) weeks for those who consulted a general practitioner and were diagnosed by a specialist. Few patients (4.9%) had a biomarker-confirmed diagnosis. Delays due to waiting for specialist referrals and diagnostic tests were reported for 57.6% and 26.9% of patients, respectively. Acetylcholinesterase inhibitors were the most common first-line treatment (82.0%).ConclusionsOur data highlighted delays in AD diagnosis and potential areas for United Kingdom health system improvement. Expediting timely diagnosis through increased public awareness, expanded biomarker use and addressing disparities in services is crucial to maximize access to emerging new therapies.

BackgroundUnderstanding the relationship among changes in Clinical Dementia Rating (CDR), patient outcomes, and probability of progression is crucial for evaluating the long-term benefits of disease-modifying treatments. We examined associations among changes in Alzheimer’s disease (AD) stages and outcomes that are important to patients and their care partners including activities of daily living (ADLs), geriatric depression, neuropsychiatric features, cognitive impairment, and the probabilities of being transitioned to a long-term care facility (i.e., institutionalization). We also estimated the total time spent at each stage and annual transition probabilities in AD.MethodsThe study included participants with unimpaired cognition, mild cognitive impairment (MCI) due to AD, and mild, moderate, and severe AD dementia in the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set (UDS) database. The associations among change in AD stages and change in relevant outcomes were estimated using linear mixed models with random intercepts. The probability of transitioning to long-term care facilities was modeled using generalized estimating equations. The total length of time spent at AD stages and annual transition probabilities were estimated with multistate Markov models.ResultsThe estimated average time spent in each stage was 3.2 years in MCI due to AD and 2.2, 2.0, and 2.8 years for mild, moderate, and severe AD dementia, respectively. The annual probabilities of progressing from MCI to mild, moderate, and severe AD dementia were 20, 4, and 0.7%, respectively. The incremental change to the next stage of participants with unimpaired cognition, MCI, and mild, moderate, and severe AD dementia (to death) was 3.2, 20, 26.6, 31, and 25.3%, respectively. Changes in ADLs, neuropsychiatric features, and cognitive measures were greatest among participants who transitioned from MCI and mild AD dementia to more advanced stages. Participants with MCI and mild and moderate AD dementia had increasing odds of being transitioned to long-term care facilities over time during the follow-up period.ConclusionsThe findings demonstrated that participants with early stages AD (MCI or mild dementia) were associated with the largest changes in clinical scale scores. Early detection, diagnosis, and intervention by disease-modifying therapies are required for delaying AD progression. Additionally, estimates of transition probabilities can inform future studies and health economic modeling.

A-76 Specificity of the Repeatable Battery for the Assessment of Neuropsychological Status Digit Span as a Validity Indicator in Patients with Mild Cognitive Impairment and Dementia

BackgroundSimulation models can extrapolate short‐term treatment effects observed in clinical trials of amyloid‐targeting therapies over longer disease trajectories. Current simulation models include clinically diagnosed AD patients without biomarker confirmation, whereas only biomarker‐confirmed patients are eligible for treatment. We aim to develop a model for the simulation of biomarker‐confirmed AD memory clinic patients natural disease trajectories and evaluate time gained with different hypothetical treatment scenario.MethodWe developed an AD microsimulation model with stages mild cognitive impairment (MCI), mild, moderate, and severe community dementia, institutionalisation, and death. We estimated the model with data from 388 amyloid‐positive MCI and 762 amyloid‐positive dementia patients from the Amsterdam Dementia Cohort. Longitudinal follow‐up information included assessments of mini‐mental state examination (MMSE), time to dementia (n = 219), time to institutionalisation (n = 277) and time to death (n = 262). Two joint models formed the core of the simulation model describing MMSE decline and transition from MCI to dementia, and MMSE decline and the transition from dementia to institutionalisation or death (Figure 1). Community dementia stages were defined by MMSE: >20 (mild), 10‐20 (moderate), and <10 (severe). Model performance was assessed by visually comparing observed and predicted cumulative incidence curves. We performed a microsimulation of the trajectory of 1000 MCI patients (66±7yr, 47%F, MMSE 26±2) to determine the mean time per stage.ResultThe predicted cumulative incidences were similar to the observed cumulative incidences, indicating good model performance (Figure 2). The mean natural time per stage was: 3.4yrs (MCI), 2.6yrs (mild), 1.6yrs (moderate), 1.0yrs (severe community dementia), and 1.7yrs (institution); totalling 10.2yrs from MCI to death. An intervention slowing MMSE decline by 30% during MCI and mild dementia increased MCI duration by 4mths, increased mild dementia duration by 12mths, and delayed institutionalisation by 12mths (Figure 3). An additional direct intervention effect reducing the hazard of transitioning from MCI or mild dementia by 30%, further extended MCI duration by 10mths, while mild dementia duration increased by 10mnths instead of 12mnths.ConclusionWe developed a simulation model to evaluate amyloid‐targeting therapies in MCI and mild dementia. The model can help quantify the effect of different treatment mechanisms and longitudinal consequences of treatment scenarios.

Measuring physical activity (PA) in people with mild cognitive impairment or dementia can be difficult. The aim was to investigate the validity and acceptability of three different PA measurement methods. The mixed-method analysis included 49 participants with mild cognitive impairment or dementia, who completed a daily calendar recording PA, the International Physical Activity Questionnaire, and the Longitudinal Aging Study Amsterdam PA Questionnaire, and those who wore a Misfit Shine accelerometer. The quantitative analysis showed equal completion rates for the International Physical Activity Questionnaire and the accelerometer but a lower completion rate for the calendar. Correlations between outcome measures were moderate or strong. The qualitative analysis indicated that all measures were acceptable, though some participants required help to complete the calendars or fasten the accelerometers. The study supported the validity of these methods for people with mild cognitive impairment and mild dementia. Using accelerometers and completing calendars might increase the motivation to be active for some people.

(Reprinted with permission from American Psychiatric Association, http://psychiatryonline.org/guidelines).

A Clinical Approach to Mild Cognitive Impairment

BackgroundAn Alzheimer's disease (AD) diagnosis made in the earliest symptomatic stages substantially benefits patients and their care partners. However, little is known regarding the clinical, healthcare system-level, and patient-specific barriers that hinder timely diagnosis and treatment.ObjectiveTo explore real-world practices surrounding the diagnostic journey and management of mild cognitive impairment (MCI)/AD dementia patients.MethodsData were drawn from Adelphi Real World Dementia Disease Specific Programme™, a cross-sectional survey of physicians treating MCI/AD dementia patients in France, Germany, Italy, Spain, the United Kingdom, the United States, and Japan between 2022 and 2024.ResultsOverall, 779 physicians reported data on 5551 patients. Physicians indicated current disease severity for 5421 patients; 37.2% had MCI (87.3% with suspected prodromal AD and 12.7% undetermined etiology), 17.2% AD with mild dementia, 31.1% AD with moderate dementia, and 14.5% AD with severe dementia. When not immediately diagnosed, the median time from first consultation to initial diagnosis was 8.9 and 12.6 weeks when patients first consulted and were diagnosed by either a primary care practitioner (PCP) or a specialist, respectively, compared with 21.6 weeks when a PCP referred to a specialist for diagnosis. Diagnostic delays were predominantly due to specialist wait times. Few patients had diagnostic AD biomarker tests (cerebrospinal fluid testing 9.5%, amyloid positron emission tomography 3.7%, AD-blood tests 5.3%).ConclusionsTimely MCI and AD diagnosis is impeded by referral delays and limited use of biomarker testing. Addressing these critical care gaps requires enhanced physician training, reduced wait times and increased biomarker utilization for early management.

BackgroundGERAS‐US is a prospective study characterizing the clinical and economic outcomes of early Alzheimer’s Disease (AD). We describe changes in total societal costs at 3 years post‐baseline in amyloid positive[+] patients with mild cognitive impairment (MCI) and mild dementia (MILD) due to AD.MethodGERAS‐US enrolled patients aged 55 to 85 (N=617) from October 30, 2016, through October 9, 2017. Cognition and function were assessed using Mini Mental State Exam (MMSE) and Cognitive Function Index (CFI), respectively. Mean 30‐day total societal costs (direct and indirect costs using opportunity formulae [Figure 1]) were calculated. Costs are presented as least square (LS) mean (95% confidence interval [CI]) at baseline, 6 months and 36 months for the overall population and stratified by baseline severity (MCI[+] vs MILD[+]) using Mixed Model Repeated Measurement (MMRM). Least square mean (95% CI) changes from 6 months to 36 months, using MMRM, are presented.ResultAt baseline, mean age was 70.3 years (MCI) and 71.7 years (MILD); 52.7% were females. Analyses at 36 months post‐baseline included 308 patients. Mean change from baseline in CFI and MMSE scores demonstrated worsening over 36 months (Table 1). The LS mean estimated total societal costs for MCI and MILD, respectively, were higher at baseline ($2430 and $4063) but remained steady from 6 months ($1977 and $3032) to 36 months ($2007 and $3392) (Figure 2). Direct medical costs did not change over the follow‐up period (6 months to 36 months) for either MILD or MCI patients or for their caregivers. Direct nonmedical costs were significantly higher for MILD but not MCI patients. Indirect nonmedical caregiver costs trended higher for both MCI and MILD cohorts but were not significant (Table 2).ConclusionBoth function and cognition declined significantly over 36 months in this cohort of amyloid[+] patients. Direct medical costs remained steady over the follow‐up period after an initial decline from baseline, possibly due to diagnostic certainty achieved at baseline. The rise in direct nonmedical costs for MILD and the trend toward rising indirect caregiver costs in MCI and MILD patients over 36 months shows the additional economic impact associated with clinical progression in early AD.

Essential tremor (ET) is one of the most common neurological disorders among adults, and it is the most common tremor disorder.[1-8] As in other neurodegenerative diseases, age of onset in ET is chiefly assessed by the patients’ (or occasionally their caregivers’) self-report, which may be of little documentary value. Surprisingly, there have been few data that have examined the accuracy of patients’ reports of age of onset in ET. In ET, dating the onset is not a trivial issue. Indeed, age of onset is a variable of considerable importance. First, late-onset ET could have different biochemical and neuropathological underpinnings from earlier onset ET.[9, 10] Second, as in other neurodegenerative disorders, such as Parkinson’s disease,[11, 12] an association between older age of onset and mild cognitive impairment and dementia has been reported in ET (i.e., ET patients with older age of onset are more likely to have mild cognitive impairment and demented than are ET patients with younger age of onset, and older onset of ET is a risk factor for incident dementia). Third, age of onset is crucial when determining the rate of progression in cross-sectional studies.[9] In this issue of Neuroepidemiology, Louis [13] analyzed the agreement in data on age of onset in 86 patients with ET from a prospective, epidemiological study in New York. Patients with ET cases were assessed at two time points (baseline and follow-up), and data on age of onset were collected each time by self-report. Despite the observation that agreement between the baseline and follow-up reports was high (ρ = 0.85, p 10 years. The results of this study are of special interest. Aside from the fact that only a prior pilot study, conducted by the same group, had addressed this reliability issue in ET,[14] there were no other published data to aid clinicians and researchers. The study had several strengths, including the large sample size, the exhaustive study of the patients and the well thought-out approach to the statistical analyses. The study was not without limitations. Specifically, only 86 of 376 ET patients initially enrolled were followed up. However, these 86 enrollees were similar to the larger group of 376 from which they were drawn in terms of baseline tremor severity, baseline tremor duration and baseline age. Leaving aside issues of strengths and limitations, the study again demonstrates that age of onset, overall, is reliably reported. Yet investigators should approach these self-reports with some degree of caution. Differences in reported age of onset in ET can vary widely, and in up 1/5 of patients may be substantial. Louis [13] has proposed several approaches to supplement self-reported data in future studies. One approach would be to examine hand-writing samples (e.g., signatures, letters) retrospectively, as an objective record of the possible onset and development of tremor. Another one would be to use collateral history from family members. Despite this, the main question is “when does ET really start”. The answer still remains uncertain. Given the heterogeneous nature of ET,[15] this may differ depending on the cause/s of the syndrome. When and where the neuropathological process develops in ET still remains uncertain.

Background and PurposeAlthough the clock drawing test (CDT) is a widely used cognitive screening instrument, there have been inconsistent findings regarding its utility with various scoring systems in patients with mild cognitive impairment (MCI) or dementia. The present study aimed to identify whether patients with MCI or dementia exhibited impairment on the CDT using three different scoring systems, and to determine which scoring system is more useful for detecting MCI and mild dementia.MethodsPatients with amnestic mild cognitive impairment (aMCI), vascular mild cognitive impairment (VaMCI), mild Alzheimer's disease (AD), mild vascular dementia (VaD), and cognitively normal older adults (CN) were included. All participants were administered the CDT, the Korean-Mini Mental State Examination (K-MMSE), and the Clinical Dementia Rating scale. The CDT was scored using the 3-, 5-, and 15-point scoring systems.ResultsOn all three scoring systems, all patient groups demonstrated significantly lower scores than the CN. However, while there were no significant differences among patients with aMCI, VaMCI, and AD, those with VaD exhibited the lowest scores. Area under the Receiver Operating Characteristic curves revealed that the three CDT scoring systems were comparable with the K-MMSE in differentiating aMCI, VaMCI, and VaD from CN. In differentiating AD from CN, however, the CDT using the 15-point scoring system demonstrated the most comparable discriminability with K-MMSE.ConclusionsThe results demonstrated that the CDT is a useful cognitive screening tool that is comparable with the Mini-Mental State Examination, and that simple CDT scoring systems are sufficient for differentiating patients with MCI and mild dementia from CN.

BackgroundConsiderable cognitive research in Alzheimer Disease (AD) has focused on memory as it is often the primary symptom; nevertheless, in A431E PSEN1 mutation carriers in Jalisco, a rapidly language impairment and verbal fluency decrease during the disease is reported (Petersen‐Dumois, et al., 2020) though this deficit is not well‐characterized. The aim of this study was to identify and characterize phonetic‐phonological abnormalities in the spontaneous speech through different stages of A431E PSEN1 mutation‐related AD.MethodEleven symptomatic A431E PSEN1 mutation carriers, with a mean age of 42.54 years (DE = 4.17) participated in the study: five with Mild Cognitive Impairment (MCI), three with Mild Dementia (MiD) and five with Moderate Dementia (MoD). We used three language tasks: trip planning, picture description, and narrative discourse of a risky and happy moment of their lives which were recorded and transcribed. For each participant, we computed the frequency of phonetic‐phonological features: stuttering, unintelligible productions, phonological paraphasias, fillers and pauses (≥2 seconds) and then converted into percentages dividing the number of occurrences of each feature by the number of words used on the speech sample (for pauses, time in seconds). Then, we obtained the percentage mean of each feature per group.ResultWe analyzed a total of 134.65 minutes of speech sample. Regarding verbal fluency, words per minute (means) varied across the groups MCI: 85.55 (SD = 39.34); MiD: 128.56 (SD = 34.14) MoD: 67.80. (SD = 32.71). All phonological features were present, stuttering: MCI: 1.38%; MiD: 3.2%; MoD: 4.05%; unintelligible productions: MCI: .22%; MiD: .64%; MoD: .76%; phonological paraphasias; MCI: 0.002%; MiD: .01% MoD: .01%; fillers: MCI: 2.05%; MiD: .29%; MoD: 2.88%; number of pauses: MCI: .04%; MiD: .05%; MoD: .03%. and pauses average: MCI: 3.42 (SD = .62); MiD: 2.55 (SD = .03) MoD = 3.43. (SD: 1.61).ConclusionWe found that A431E PSEN1 mutation carriers present phonetic‐phonological traits even in the earliest stage (MCI) and for three of them (stuttering, unintelligible productions, and phonological paraphasias) their frequency is greater the more severe the impairment (MoD). Stuttering is their most prominent feature. These disturbances in the spontaneous speech could be a phenotype trait of this ADAD mutation.

Background and PurposeInterpreting the Rey complex figure (RCF) requires a standard RCF scoring system and clinical decision by clinicians. The interpretation of RCF using clinical decision by clinicians might not be accurate in the diagnosing of mild cognitive impairment (MCI) or dementia patients in comparison with the RCF scoring system. For this reason, a machine-learning algorithm was used to demonstrate that scoring RCF using clinical decision is not as accurate as of the RCF scoring system in predicting MCI or mild dementia patients from normal subjects.MethodsThe RCF dataset consisted of 2,232 subjects with formal neuropsychological assessments. The RCF dataset was classified into 2 datasets. The first dataset was to compare normal vs. abnormal and the second dataset was to compare normal vs. MCI vs. mild dementia. Models were trained using a convolutional neural network for machine learning. Receiver operating characteristic curves were used to compare the sensitivity, specificity, and area under the curve (AUC) of models.ResultsThe trained model's accuracy for predicting cognitive states was 96% with the first dataset (normal vs. abnormal) and 88% with the second dataset (normal vs. MCI vs. mild dementia). The model had a sensitivity of 85% for detecting abnormal with an AUC of 0.847 with the first dataset. It had a sensitivity of 78% for detecting MCI or mild dementia with an AUC of 0.778 with the second dataset.ConclusionsBased on this study, the RCF scoring system has the potential to present more accurate criteria than the clinical decision for distinguishing cognitive impairment among patients.

Given considerable variation in diagnostic and therapeutic practice, there is a need for national guidance on the use of neuroimaging, fluid biomarkers, cognitive testing, follow-up and diagnostic terminology in mild cognitive impairment (MCI). MCI is a heterogenous clinical syndrome reflecting a change in cognitive function and deficits on neuropsychological testing but relatively intact activities of daily living. MCI is a risk state for further cognitive and functional decline with 5–15% of people developing dementia per year. However, ~50% remain stable at 5 years and in a minority, symptoms resolve over time. There is considerable debate about whether MCI is a useful clinical diagnosis, or whether the use of the term prevents proper inquiry (by history, examination and investigations) into underlying causes of cognitive symptoms, which can include prodromal neurodegenerative disease, other physical or psychiatric illness, or combinations thereof. Cognitive testing, neuroimaging and fluid biomarkers can improve the sensitivity and specificity of aetiological diagnosis, with growing evidence that these may also help guide prognosis. Diagnostic criteria allow for a diagnosis of Alzheimer’s disease to be made where MCI is accompanied by appropriate biomarker changes, but in practice, such biomarkers are not available in routine clinical practice in the UK. This would change if disease-modifying therapies became available and required a definitive diagnosis but would present major challenges to the National Health Service and similar health systems. Significantly increased investment would be required in training, infrastructure and provision of fluid biomarkers and neuroimaging. Statistical techniques combining markers may provide greater sensitivity and specificity than any single disease marker but their practical usefulness will depend on large-scale studies to ensure ecological validity and that multiple measures, e.g. both cognitive tests and biomarkers, are widely available for clinical use. To perform such large studies, we must increase research participation amongst those with MCI.