scholarly journals Cognitive Practice Effects Delay Diagnosis; Implications for Clinical Trials

2020 ◽  
Author(s):  
Mark Sanderson-Cimino ◽  
Jeremy A. Elman ◽  
Xin M. Tu ◽  
Alden L. Gross ◽  
Matthew S. Panizzon ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Practice Effect ◽  
Cognitive Testing ◽  
Practice Effects ◽  
Criterion Validation ◽  
Novel Method ◽  
Adjusted Scores

AbstractObjectivePractice effects on cognitive tests obscure decline, thereby delaying detection of mild cognitive impairment (MCI). This reduces opportunities for slowing Alzheimer’s disease progression and can hinder clinical trials. Using a novel method, we assessed the ability of practice-effect-adjusted diagnoses to detect MCI earlier, and tested the validity of these diagnoses based on AD biomarkers.MethodsOf 889 Alzheimer’s Disease Neuroimaging Initiative participants who were cognitively normal (CN) at baseline, 722 returned at 1-year-follow-up (mean age=74.9±6.8). Practice effects were calculated by comparing returnee scores at follow-up to demographically-matched individuals who had only taken the tests once, with an additional adjustment for attrition effects. Practice effects for each test were subtracted from follow-up scores. The lower scores put additional individuals below the impairment threshold for MCI. CSF amyloid-beta, phosphorylated tau, and total tau were measured at baseline and used for criterion validation.ResultsPractice-effect-adjusted scores increased MCI incidence by 26% (p<.001). Adjustment increased proportions of amyloid-positive MCI cases (+20%) and reduced proportions of amyloid-positive CNs (−6%) (ps<.007). With the increased MCI base rate, adjustment for practice effects would reduce the sample size needed for detecting significant drug treatment effects by an average of 21%, which we demonstrate would result in multi-million-dollar savings in a clinical trial.InterpretationAdjusting for practice effects on cognitive testing leads to earlier detection of MCI. When MCI is an outcome, this reduces recruitment needed for clinical trials, study duration, staff and participant burden, and can dramatically lower costs. Importantly, biomarker evidence also indicates improved diagnostic accuracy.

scholarly journals SHORT-TERM PRACTICE EFFECTS AND AMYLOID DEPOSITION: PROVIDING INFORMATION ABOVE AND BEYOND BASELINE COGNITION

2017 ◽  
pp. 1-6
Author(s):  
K. Duff ◽  
D.B. Hammers ◽  
B.C.A. Dalley ◽  
K.R. Suhrie ◽  
T.J. Atkinson ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Test Scores ◽  
Amyloid Deposition ◽  
Cognitive Testing ◽  
Practice Effects ◽  
Cognitive Test ◽  
Cognitive Tests ◽  
Short Term

Background: Practice effects, which are improvements in cognitive test scores due to repeated exposure to testing materials, may provide information about Alzheimer’s disease pathology, which could be useful for clinical trials enrichment. Objectives: The current study sought to add to the limited literature on short-term practice effects on cognitive tests and their relationship to amyloid deposition on neuroimaging. Participants: Twenty-seven, non-demented older adults (9 cognitively intact, 18 with mild cognitive impairment) received amyloid imaging with 18F-Flutemetamol, and two cognitive testing sessions across one week to determine practice effects. Results: A composite measure of 18F-Flutemetamol uptake correlated significantly with all seven cognitive tests scores on the baseline battery (r’s = -0.61 – 0.59, all p’s<0.05), with higher uptake indicating poorer cognition. Practice effects significantly added to the relationship (above and beyond the baseline associations) with 18F-Flutemetamol uptake on 4 of the 7 cognitive test scores (partial r’s = -0.45 – 0.44, p’s<0.05), with higher uptake indicating poorer practice effects. The odds ratio of being “amyloid positive” was 13.5 times higher in individuals with low practice effects compared to high practice effects. Conclusions: Short-term practice effects over one week may be predictive of progressive dementia and serve as an affordable screening tool to enrich samples for preventative clinical trials in Alzheimer’s disease.

Longitudinal Changes in Individual BrainAGE in Healthy Aging, Mild Cognitive Impairment, and Alzheimer’s Disease

GeroPsych ◽  
2012 ◽  
Vol 25 (4) ◽  
pp. 235-245 ◽  
Author(s):  
Katja Franke ◽  
Christian Gaser
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Healthy Aging ◽  
Brain Aging ◽  
Elderly Subjects ◽  
Additional Increase ◽  
Longitudinal Changes ◽  
Novel Method ◽  
The Brain

We recently proposed a novel method that aggregates the multidimensional aging pattern across the brain to a single value. This method proved to provide stable and reliable estimates of brain aging – even across different scanners. While investigating longitudinal changes in BrainAGE in about 400 elderly subjects, we discovered that patients with Alzheimer’s disease and subjects who had converted to AD within 3 years showed accelerated brain atrophy by +6 years at baseline. An additional increase in BrainAGE accumulated to a score of about +9 years during follow-up. Accelerated brain aging was related to prospective cognitive decline and disease severity. In conclusion, the BrainAGE framework indicates discrepancies in brain aging and could thus serve as an indicator for cognitive functioning in the future.

scholarly journals Monthly At-Home Computerized Cognitive Testing to Detect Diminished Practice Effects in Preclinical Alzheimer's Disease

2022 ◽  
Vol 13 ◽  
Author(s):  
Roos J. Jutten ◽  
Dorene M. Rentz ◽  
Jessie F. Fu ◽  
Danielle V. Mayblyum ◽  
Rebecca E. Amariglio ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Pet Imaging ◽  
Cognitive Testing ◽  
Practice Effects ◽  
Aging Brain ◽  
Amyloid Burden ◽  
Preclinical Ad ◽  
At Home

Introduction: We investigated whether monthly assessments of a computerized cognitive composite (C3) could aid in the detection of differences in practice effects (PE) in clinically unimpaired (CU) older adults, and whether diminished PE were associated with Alzheimer's disease (AD) biomarkers and annual cognitive decline.Materials and Methods:N = 114 CU participants (age 77.6 ± 5.0, 61% female, MMSE 29 ± 1.2) from the Harvard Aging Brain Study completed the self-administered C3 monthly, at-home, on an iPad for one year. At baseline, participants underwent in-clinic Preclinical Alzheimer's Cognitive Composite-5 (PACC5) testing, and a subsample (n = 72, age = 77.8 ± 4.9, 59% female, MMSE 29 ± 1.3) had 1-year follow-up in-clinic PACC5 testing available. Participants had undergone PIB-PET imaging (0.99 ± 1.6 years before at-home baseline) and Flortaucipir PET imaging (n = 105, 0.62 ± 1.1 years before at-home baseline). Linear mixed models were used to investigate change over months on the C3 adjusting for age, sex, and years of education, and to extract individual covariate-adjusted slopes over the first 3 months. We investigated the association of 3-month C3 slopes with global amyloid burden and tau deposition in eight predefined regions of interest, and conducted Receiver Operating Characteristic analyses to examine how accurately 3-month C3 slopes could identify individuals that showed &gt;0.10 SD annual decline on the PACC-5.Results: Overall, individuals improved on all C3 measures over 12 months (β = 0.23, 95% CI [0.21–0.25], p &lt; 0.001), but improvement over the first 3 months was greatest (β = 0.68, 95% CI [0.59–0.77], p &lt; 0.001), suggesting stronger PE over initial repeated exposures. However, lower PE over 3 months were associated with more global amyloid burden (r = −0.20, 95% CI [−0.38 – −0.01], p = 0.049) and tau deposition in the entorhinal cortex (r = −0.38, 95% CI [−0.54 – −0.19], p &lt; 0.001) and inferior-temporal lobe (r = −0.23, 95% CI [−0.41 – −0.02], p = 0.03). 3-month C3 slopes exhibited good discriminative ability to identify PACC-5 decliners (AUC 0.91, 95% CI [0.84–0.98]), which was better than baseline C3 (p &lt; 0.001) and baseline PACC-5 scores (p = 0.02).Conclusion: While PE are commonly observed among CU adults, diminished PE over monthly cognitive testing are associated with greater AD biomarker burden and cognitive decline. Our findings imply that unsupervised computerized testing using monthly retest paradigms can provide rapid detection of diminished PE indicative of future cognitive decline in preclinical AD.

scholarly journals Automatic Prediction of Cognitive and Functional Decline Can Significantly Decrease the Number of Subjects Required for Clinical Trials in Early Alzheimer’s Disease

2021 ◽  
pp. 1-8
Author(s):  
Neda Shafiee ◽  
Mahsa Dadar ◽  
Simon Ducharme ◽  
D. Louis Collins ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Cognitive Decline ◽  
Functional Decline ◽  
Amyloid Β ◽  
Cognitive Test ◽  
Disease Heterogeneity ◽  
Early Alzheimer’S Disease

Background: While both cognitive and magnetic resonance imaging (MRI) data has been used to predict progression in Alzheimer’s disease, heterogeneity between patients makes it challenging to predict the rate of cognitive and functional decline for individual subjects. Objective: To investigate prognostic power of MRI-based biomarkers of medial temporal lobe atrophy and macroscopic tissue change to predict cognitive decline in individual patients in clinical trials of early Alzheimer’s disease. Methods: Data used in this study included 312 patients with mild cognitive impairment from the ADNI dataset with baseline MRI, cerebrospinal fluid amyloid-β, cognitive test scores, and a minimum of two-year follow-up information available. We built a prognostic model using baseline cognitive scores and MRI-based features to determine which subjects remain stable and which functionally decline over 2 and 3-year follow-up periods. Results: Combining both sets of features yields 77%accuracy (81%sensitivity and 75%specificity) to predict cognitive decline at 2 years (74%accuracy at 3 years with 75%sensitivity and 73%specificity). When used to select trial participants, this tool yields a 3.8-fold decrease in the required sample size for a 2-year study (2.8-fold decrease for a 3-year study) for a hypothesized 25%treatment effect to reduce cognitive decline. Conclusion: When used in clinical trials for cohort enrichment, this tool could accelerate development of new treatments by significantly increasing statistical power to detect differences in cognitive decline between arms. In addition, detection of future decline can help clinicians improve patient management strategies that will slow or delay symptom progression.

scholarly journals THE TRIAL-READY COHORT FOR PRECLINICAL AND PRODROMAL ALZHEIMER’S DISEASE (TRC-PAD): EXPERIENCE FROM THE FIRST 3 YEARS

2020 ◽  
pp. 1-8
Author(s):  
S. Walter ◽  
O.G. Langford ◽  
T.B. Clanton ◽  
G.A. Jimenez-Maggiora ◽  
R. Raman ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
High Risk ◽  
Digit Symbol Substitution Test ◽  
Data Set ◽  
Adult Intelligence Scale ◽  
Risk Algorithm ◽  
Prodromal Alzheimer’S Disease

BACKGROUND: The Trial-Ready Cohort for Preclinical and Prodromal Alzheimer’s disease (TRC-PAD) aims to accelerate enrollment for Alzheimer’s disease (AD) clinical trials by remotely identifying and tracking individuals who are at high risk for developing symptoms of AD, and referring these individuals to in-person cognitive and biomarker evaluation with the purpose of engaging them in clinical trials. A risk algorithm using statistical modeling to predict brain amyloidosis will be refined as TRC-PAD advances with a maturing data set. Objectives: To provide a summary of the steps taken to build this Trial-Ready cohort (TRC) and share results of the first 3 years of enrollment into the program. Design: Participants are remotely enrolled in the Alzheimer Prevention Trials (APT) Webstudy with quarterly assessments, and through an algorithm identified as potentially at high risk, referred to clinical sites for biomarker confirmation, and enrolled into the TRC. Setting: Both an online study and in-clinic non-interventional cohort study. Participants: APT Webstudy participants are aged 50 or older, with an interest in participation in AD therapeutic trials. TRC participants must have a study partner, stable medical condition, and elevated brain amyloid, as measured by amyloid positron emission tomography or cerebrospinal fluid analysis. Additional risk assessments include apolipoprotein E genotyping. Measurements: In the APT Webstudy, participants complete the Cognitive Function Index and Cogstate Brief Battery. The TRC includes the Preclinical Alzheimer’s Cognitive Composite, comprised of the Free and Cued Selective Reminding Test, the Delayed Paragraph Recall score on the Logical Memory IIa test from the Wechsler Memory Scale, the Digit-Symbol Substitution test from the Wechsler Adult Intelligence Scale-Revised, and the Mini Mental State Examination total score (1). Results: During the first 3 years of this program, the APT Webstudy has 30,650 consented participants, with 23 sites approved for in person screening, 112 participants have been referred for in-clinic screening visits with eighteen enrolled to the TRC. The majority of participants consented to APT Webstudy have a family history of AD (62%), identify as Caucasian (92.5%), have over twelve years of formal education (85%), and are women (73%). Follow up rates for the first quarterly assessment were 38.2% with 29.5% completing the follow up Cogstate Battery. Conclusions: After successfully designing and implementing this program, the study team’s priority is to improve diversity of participants both in the APT Webstudy and TRC, to continue enrollment into the TRC to our target of 2,000, and to improve longitudinal retention, while beginning the process of referring TRC participants into clinical trials.

scholarly journals Development of Novel Measures for Alzheimer’s Disease Prevention Trials (NoMAD)

2021 ◽  
Author(s):  
Sophie A. Bell ◽  
Hannah R. Cohen ◽  
Seonjoo Lee ◽  
Hyun Kim ◽  
Adam Ciarleglio ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Psychometric Properties ◽  
Brain Mri ◽  
Assessment Scale ◽  
Practice Effects ◽  
Disease Assessment ◽  
Cognitive Changes ◽  
Functional Changes

ABSTRACTIntroductionAssessment of cognition and everyday function is essential in clinical trials for Alzheimer’s disease (AD). Two novel measures of cognition (No Practice Effects (NPE) cognitive battery and Miami Computerized Functional Assessment Scale (CFAS)) were designed to have robust psychometric properties and reduced practice and ceiling effects. This study aims to evaluate if the NPE and CFAS demonstrate stronger psychometric properties and reduced practice effects compared with established measures, including the Preclinical Alzheimer Cognitive Composite (PACC), Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), and Functional Activities Questionnaire (FAQ).MethodsThis parallel group, four-site study will randomize 320 cognitively intact adults aged 60 to 85 years to novel or well-established measures of cognition and function. All participants will receive assessments at baseline (week 0), week 12, and week 52, as well as a brain MRI scan and Apolipoprotein E genetic test at study entry. Analyses will determine psychometric properties of the NPE and CFAS, compare the sensitivity of measures to AD risk markers, and identify cognitive domains within the NPE.DiscussionPractice effects have been a major limitation of Alzheimer’s disease clinical trials that typically assess cognitive changes over serial assessments. Detection of functional impairment in cognitively normal individuals with biomarkers for Alzheimer’s disease requires instruments sensitive to very subtle functional changes. This study is intended to support the validation of two new composite measures, the NPE battery and the CFAS, which may advance clinical testing of interventions for individuals across the spectrum of early stage Alzheimer’s disease.Trial RegistrationNCT03900273

Elucidating the risk factors for progression from amyloid-negative amnestic mild cognitive impairment to dementia

2020 ◽  
Vol 17 ◽  
Author(s):  
Hyung-Ji Kim ◽  
Jae-Hong Lee ◽  
E-nae Cheong ◽  
Sung-Eun Chung ◽  
Sungyang Jo ◽  
...  
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Amnestic Mild Cognitive Impairment ◽  
Amyloid Pet ◽  
Clinical Progression ◽  
Amnestic Mci

Background: Amyloid PET allows for the assessment of amyloid β status in the brain, distinguishing true Alzheimer’s disease from Alzheimer’s disease-mimicking conditions. Around 15–20% of patients with clinically probable Alzheimer’s disease have been found to have no significant Alzheimer’s pathology on amyloid PET. However, a limited number of studies had been conducted this subpopulation in terms of clinical progression. Objective: We investigated the risk factors that could affect the progression to dementia in patients with amyloid-negative amnestic mild cognitive impairment (MCI). Methods: This study was a single-institutional, retrospective cohort study of patients over the age of 50 with amyloidnegative amnestic MCI who visited the memory clinic of Asan Medical Center with a follow-up period of more than 36 months. All participants underwent brain magnetic resonance imaging (MRI), detailed neuropsychological testing, and fluorine-18[F18]-florbetaben amyloid PET. Results: During the follow-up period, 39 of 107 patients progressed to dementia from amnestic MCI. In comparison with the stationary group, the progressed group had a more severe impairment in verbal and visual episodic memory function and hippocampal atrophy, which showed an Alzheimer’s disease-like pattern despite the lack of evidence for significant Alzheimer’s disease pathology. Voxel-based morphometric MRI analysis revealed that the progressed group had a reduced gray matter volume in the bilateral cerebellar cortices, right temporal cortex, and bilateral insular cortices. Conclusion: Considering the lack of evidence of amyloid pathology, clinical progression of these subpopulation may be caused by other neuropathologies such as TDP-43, abnormal tau or alpha synuclein that lead to neurodegeneration independent of amyloid-driven pathway. Further prospective studies incorporating biomarkers of Alzheimer’s diseasemimicking dementia are warranted.

A Biomarker Combining Imaging and Neuropsychological Assessment for Tracking Early Alzheimer's Disease in Clinical Trials

2018 ◽  
Vol 15 (5) ◽  
pp. 429-442 ◽  
Author(s):  
Nishant Verma ◽  
S. Natasha Beretvas ◽  
Belen Pascual ◽  
Joseph C. Masdeu ◽  
Mia K. Markey ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Cognitive Impairment ◽  
Latent Variable ◽  
Brain Regions ◽  
Disease Assessment ◽  
Latent Variable Analysis ◽  
The Relationship ◽  
Selection Of

Background: Combining optimized cognitive (Alzheimer's Disease Assessment Scale- Cognitive subscale, ADAS-Cog) and atrophy markers of Alzheimer's disease for tracking progression in clinical trials may provide greater sensitivity than currently used methods, which have yielded negative results in multiple recent trials. Furthermore, it is critical to clarify the relationship among the subcomponents yielded by cognitive and imaging testing, to address the symptomatic and anatomical variability of Alzheimer's disease. Method: Using latent variable analysis, we thoroughly investigated the relationship between cognitive impairment, as assessed on the ADAS-Cog, and cerebral atrophy. A biomarker was developed for Alzheimer's clinical trials that combines cognitive and atrophy markers. Results: Atrophy within specific brain regions was found to be closely related with impairment in cognitive domains of memory, language, and praxis. The proposed biomarker showed significantly better sensitivity in tracking progression of cognitive impairment than the ADAS-Cog in simulated trials and a real world problem. The biomarker also improved the selection of MCI patients (78.8±4.9% specificity at 80% sensitivity) that will evolve to Alzheimer's disease for clinical trials. Conclusion: The proposed biomarker provides a boost to the efficacy of clinical trials focused in the mild cognitive impairment (MCI) stage by significantly improving the sensitivity to detect treatment effects and improving the selection of MCI patients that will evolve to Alzheimer’s disease.

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