Participant and study partner prediction and identification of cognitive impairment in preclinical Alzheimer’s disease: study partner vs. participant accuracy

Abstract Background Preclinical Alzheimer’s disease (AD) clinical trials require participants to enroll with a study partner, a person who can attend visits and report changes in the participant’s cognitive ability. Whether study partners, compared to participants themselves, provide added information about participant cognition in preclinical AD trials is an open question. We tested the hypothesis that study partners provide meaningful information related to participant cognition cross-sectionally and longitudinally, and assessed whether amyloid status modified observed effects. Methods We assessed participant and study partner Everyday Cognition (ECog) scores and participant Alzheimer’s Disease Assessment Scale 13-item cognitive subscale (ADAS13) data from 335 cognitively normal participant-partner dyads in the AD Neuroimaging Initiative. We used random forest and linear mixed effects (LME) models to predict ADAS13 scores as a function of participant and/or study partner ECog scores over time. LME models were adjusted for potential confounding factors, including APOE4 status, amyloid status, baseline age, years of education, and sex. Random forest models were split into the above factors, as well as race/ethnicity and other available neuropsychological battery test scores. Results In random forest models predicting ADAS13 12 months from baseline, we observed no difference in the estimated mean variable importance (eMVI) associated with baseline study partner ECog compared to the baseline participant ECog (eMVI = 0.15, 95%CB 0.13, 0.16 for partner; eMVI = 0.15, 95%CB 0.14, 0.16 for participant). In models predicting ADAS13 48 months after baseline, the eMVI associated with baseline study partner ECog was slightly lower than that associated with baseline participant ECog (eMVI = 0.21, 95%CB 0.20, 0.22 for partner; eMVI = 0.24, 95%CB 0.22, 0.25 for participant). In cross-sectional models, study partner eMVI was twice as large as participant eMVI at 12 months (eMVI = 0.20, 95%CB 0.19, 0.21 for partner; eMVI = 0.09, 95%CB 0.09, 0.10 for participant) and three times as large at 48 months (eMVI = 0.38, 95%CB 0.36, 0.39 for partner; eMVI = 0.13, 95%CB 0.12, 0.14 for participant). We did not observe qualitative differences by amyloid status. Conclusions While baseline participant reports reasonably predict subsequent cognitive change, informants perform better at cross-sectionally recognizing cognitive status as observation time grows. The study partner requirement may be essential to ensure trial data integrity, especially in longer trials.

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Disease progression modelling from preclinical Alzheimer’s disease (AD) to AD dementia

Scientific Reports ◽

10.1038/s41598-021-83585-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Soo Hyun Cho ◽

Sookyoung Woo ◽

Changsoo Kim ◽

Hee Jin Kim ◽

Hyemin Jang ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Disease Progression ◽

Disease Assessment ◽

Time Interval ◽

Disease Course ◽

Preclinical Alzheimer’S Disease ◽

Apoe Ε4 ◽

Preclinical Ad ◽

Cognitive Subscale

AbstractTo characterize the course of Alzheimer’s disease (AD) over a longer time interval, we aimed to construct a disease course model for the entire span of the disease using two separate cohorts ranging from preclinical AD to AD dementia. We modelled the progression course of 436 patients with AD continuum and investigated the effects of apolipoprotein E ε4 (APOE ε4) and sex on disease progression. To develop a model of progression from preclinical AD to AD dementia, we estimated Alzheimer’s Disease Assessment Scale-Cognitive Subscale 13 (ADAS-cog 13) scores. When calculated as the median of ADAS-cog 13 scores for each cohort, the estimated time from preclinical AD to MCI due to AD was 7.8 years and preclinical AD to AD dementia was 15.2 years. ADAS-cog 13 scores deteriorated most rapidly in women APOE ε4 carriers and most slowly in men APOE ε4 non-carriers (p < 0.001). Our results suggest that disease progression modelling from preclinical AD to AD dementia may help clinicians to estimate where patients are in the disease course and provide information on variation in the disease course by sex and APOE ε4 status.

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Recruitment and Retention of Participant and Study Partner Dyads in Two Multinational Alzheimer’s Disease Registration Trials

10.21203/rs.3.rs-100842/v1 ◽

2020 ◽

Author(s):

Olivia M Bernstein ◽

Joshua D. Grill ◽

Daniel L. Gillen

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Random Forest ◽

Random Forest Model ◽

P Value ◽

Confounding Factors ◽

Forest Model ◽

Partner Type ◽

Study Partner ◽

The Relationship

Abstract Background: Early study exit is detrimental to statistical power and increases the risk for bias in Alzheimer’s disease clinical trials. Previous analyses in early phase academic trials demonstrated associations between rates of trial incompletion and participants’ study partner type, with participants enrolling with non-spouse study partners being at greater risk.Methods: We conducted secondary analyses of two multinational phase III trials of semagacestat, an oral gamma secretase inhibitor, for mild-to-moderate AD dementia. Cox’s proportional hazards regression model was used to estimate the relationship between study partner type and the risk of early exit from the trial after adjustment for a priori identified potential confounding factors. Additionally, we used a random forest model to identify top predictors of dropout.Results: Among participants with spousal, adult child, and other study partners, respectively, 35%, 38%, and 36% dropped out or died prior to protocol-defined study completion, respectively. In unadjusted models, the risk of trial incompletion differed by study partner type (unadjusted p-value=0.027 for test of differences by partner type), but in models adjusting for potential confounding factors the differences were not statistically significant (p-value=0.928). In exploratory modeling, participant age was identified as the primary characteristic to explain the relationship between study partner type and the risk of failing to complete the trial. Participant age was also the strongest predictor of trial incompletion in the random forest model.Conclusions: After adjustment for age, no qualitative differences in the risk of incompletion were observed when comparing participants with different study partner types in these trials. Differences between our findings and the findings of previous studies may be explained by differences in trial phase, size, geographic regions, or the composition of academic and non-academic sites.

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P2-243: A PROCEDURE FOR IDENTIFYING ITEMS CAPTURING COGNITIVE CHANGE ACROSS TIME: AN ILLUSTRATION USING THE ALZHEIMER'S DISEASE ASSESSMENT SCALE-COGNITIVE (ADAS-COG)

Alzheimer s & Dementia ◽

10.1016/j.jalz.2014.05.920 ◽

2014 ◽

Vol 10 ◽

pp. P565-P565

Author(s):

N.M. Dowling ◽

Daniel Bolt

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Change ◽

Assessment Scale ◽

Disease Assessment

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Plasma Glutathione Levels Decreased with Cognitive Decline among People with Mild Cognitive Impairment (MCI): A Two-Year Prospective Study

Antioxidants ◽

10.3390/antiox10111839 ◽

2021 ◽

Vol 10 (11) ◽

pp. 1839

Author(s):

Chieh-Hsin Lin ◽

Hsien-Yuan Lane

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Cognitive Function ◽

Prospective Study ◽

Cognitive Decline ◽

Cognitive Change ◽

Disease Assessment ◽

Healthy Individuals

Glutathione (GSH) is a major endogenous antioxidant. Several studies have shown GSH redox imbalance and altered GSH levels in Alzheimer’s disease (AD) patients. Early detection is crucial for the outcome of AD. However, whether GSH can serve as a biomarker during the very early-phase of AD, such as mild cognitive impairment (MCI), remains unknown. The current prospective study aimed to examine the longitudinal change in plasma GSH concentration and its influence on cognitive decline in MCI. Overall, 49 patients with MCI and 16 healthy individuals were recruited. Plasma GSH levels and cognitive function, measured by the Mini-Mental Status Examination (MMSE) and Alzheimer’s disease assessment scale-cognitive subscale (ADAS-cog), were monitored every 6 months. We employed multiple regressions to examine the role of GSH level in cognitive decline in the 2 years period. The MCI patients showed significant decline in plasma GSH levels and cognitive function from baseline to endpoint (month 24). In comparison, the healthy individuals’ GSH concentration and cognitive function did not change significantly. Further, both GSH level at baseline and GSH level change from baseline to endpoint significantly influenced cognitive decline among the MCI patients. To our knowledge, this is the first study to demonstrate that both plasma GSH levels and cognitive function declined 2 years later among the MCI patients in a prospective manner. If replicated by future studies, blood GSH concentration may be regarded as a biomarker for monitoring cognitive change in MCI.

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Longitudinal Trajectories of Cognitive Change in Preclinical Alzheimer's Disease: A Growth Mixture Modeling Analysis

Cortex ◽

10.1016/s0010-9452(08)70682-8 ◽

2007 ◽

Vol 43 (7) ◽

pp. 826-834 ◽

Cited By ~ 52

Author(s):

Brent J. Small ◽

Lars Bäckman

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Growth Mixture Modeling ◽

Cognitive Change ◽

Mixture Modeling ◽

Preclinical Alzheimer’S Disease ◽

Longitudinal Trajectories ◽

Growth Mixture ◽

Modeling Analysis

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The Alzheimer's Disease Assessment Scale

International Psychogeriatrics ◽

10.1017/s1041610296002578 ◽

1996 ◽

Vol 8 (2) ◽

pp. 195-203 ◽

Cited By ~ 34

Author(s):

Richard C. Mohs

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Longitudinal Data ◽

Memory Loss ◽

Cognitive Change ◽

Rate Of Change ◽

Assessment Scale ◽

Disease Assessment ◽

Treatment Trials ◽

Over Time

This article reviews longitudinal data collected from patients with Alzheimer's disease (AD) that are relevant to the design and interpretation of clinical treatment trials. Longitudinal data from patients tested with the Alzheimer's Disease Assessment Scale demonstrate that cognitive symptoms, including memory loss, dysphasia, and dyspraxia, worsen relentlessly over time with the rate of change depending upon baseline dementia severity. Noncognitive symptoms, such as agitation, depressed mood, and psychosis, are episodic, do not necessarily worsen over time, and tend not to be highly correlated with one another. The reliability of cognitive change measures increases with follow-up duration so that the likelihood of detecting drug effects on the rate of cognitive deterioration is greater with longer treatment trials. Functional measures of activities of daily living are difficult to standardize for AD patients but are important for determining the overall clinical and economic impact of AD treatments.

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P4-116: A novel measure of cognitive change in preclinical Alzheimer's disease and its physiological correlates in normal and MCI elderly

Alzheimer s & Dementia ◽

10.1016/j.jalz.2015.06.1822 ◽

2015 ◽

Vol 11 (7S_Part_17) ◽

pp. P822-P822 ◽

Cited By ~ 3

Author(s):

Rosie E. Curiel ◽

David Loewenstein ◽

Elizabeth Crocco ◽

Maria Greig-Custo ◽

Rosemarie Rodriquez ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Change ◽

Preclinical Alzheimer’S Disease

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Recruitment and retention of participant and study partner dyads in two multinational Alzheimer’s disease registration trials

Alzheimer s Research & Therapy ◽

10.1186/s13195-020-00762-8 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Olivia M. Bernstein ◽

Joshua D. Grill ◽

Daniel L. Gillen

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Random Forest ◽

Random Forest Model ◽

Phase Iii ◽

Confounding Factors ◽

Forest Model ◽

Partner Type ◽

Study Partner ◽

The Relationship

Abstract Background Early study exit is detrimental to statistical power and increases the risk for bias in Alzheimer’s disease clinical trials. Previous analyses in early phase academic trials demonstrated associations between rates of trial incompletion and participants’ study partner type, with participants enrolling with non-spouse study partners being at greater risk. Methods We conducted secondary analyses of two multinational phase III trials of semagacestat, an oral gamma secretase inhibitor, for mild-to-moderate AD dementia. Cox’s proportional hazards regression model was used to estimate the relationship between study partner type and the risk of early exit from the trial after adjustment for a priori identified potential confounding factors. Additionally, we used a random forest model to identify top predictors of dropout. Results Among participants with spousal, adult child, and other study partners, respectively, 35%, 38%, and 36% dropped out or died prior to protocol-defined study completion, respectively. In unadjusted models, the risk of trial incompletion differed by study partner type (unadjusted p value = 0.027 for test of differences by partner type), but in models adjusting for potential confounding factors, the differences were not statistically significant (p value = 0.928). In exploratory modeling, participant age was identified as the primary characteristic to explain the relationship between study partner type and the risk of failing to complete the trial. Participant age was also the strongest predictor of trial incompletion in the random forest model. Conclusions After adjustment for age, no differences in the risk of incompletion were observed when comparing participants with different study partner types in these trials. Differences between our findings and the findings of previous studies may be explained by differences in trial phase, size, geographic regions, or the composition of academic and non-academic sites.

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Regional atrophy and cognitive decline depend on definition of subjective cognitive decline

10.1101/2021.04.21.21255752 ◽

2021 ◽

Author(s):

Cassandra Morrison ◽

Mahsa Dadar ◽

Neda Shafiee ◽

Sylvia Villeneuve ◽

D. Louis Collins ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Older Adults ◽

Alzheimer's Disease ◽

Cognitive Decline ◽

Cognitive Change ◽

Disease Assessment ◽

Subjective Cognitive Decline ◽

Cognitively Normal ◽

Increased Risk ◽

Definition Of

AbstractBackgroundPeople with subjective cognitive decline (SCD) may be at increased risk for Alzheimer’s disease (AD). However, not all studies have observed this increased risk. Inconsistencies may be related to different methods used to define SCD. The current project examined whether four methods of defining SCD (applied to the same sample) results in different patterns of atrophy and future cognitive decline between cognitively normal older adults with (SCD+) and without SCD (SCD-).MethodsMRI scans and questionnaire data for 273 cognitively normal older adults from Alzheimer’s Disease Neuroimaging Initiative were examined. To operationalize SCD we used four common methods: Cognitive Change Index (CCI), Everyday Cognition Scale (ECog), ECog + Worry, and Worry only. A previously validated MRI analysis method (SNIPE) was used to measure hippocampal volume and grading. Deformation-based morphometry was performed to examine volume at regions known to be vulnerable to AD. Logistic regressions were completed to determine whether diagnostic method was associated with volume differences between SCD- and SCD+. Linear mixed effects models were performed to examine the relationship between the definitions of SCD and future cognitive decline.ResultsResults varied between the four methods of defining SCD. Left hippocampal grading was lower in SCD+ than SCD-when using the CCI (p=.041) and Worry (p=.021) definitions. The right (p=.008) and left (p=.003) superior temporal regions were smaller in SCD+ than SCD-, but only with the ECog. SCD+ was associated with greater future cognitive decline measured by Alzheimer’s Disease Assessment Scale, but only with the CCI definition. In contrast, only the ECog definition of SCD was associated with future decline on the Montreal Cognitive Assessment.ConclusionThe current findings suggest that the various methods used to differentiate between SCD- and SCD+ influence whether volume differences and findings of cognitive decline are observed between groups in this retrospective analysis.

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