How Accurately Do Patients and Their Care Partners Report Results of Amyloid-β PET Scans for Alzheimer’s Disease Assessment?

James, Hailey J.; Houtven, Courtney Harold Van; Lippmann, Steven; Burke, James R.; Shepherd‐Banigan, Megan; Bélanger, Emmanuelle; Wetle, Terrie; Plassman, Brenda L.

doi:10.3233/jad-190922

Cited by 19 publications

(21 citation statements)

References 24 publications

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“… 93 Recently, James et al. 98 examined the level of concordance of SCC between dyads of persons with MCI or dementia and their study/care partners as predictors of amyloid positivity. Accuracy in classifying amyloid positivity was above 80% for self‐ and study partner dyads, similar to blood‐based biomarkers; 99 a separate cohort, evaluating self‐reported SCC alone, did not predict amyloid positivity.…”

Section: Associations Between Dyad‐reported Scc and Ad Biomarkersmentioning

confidence: 99%

The role of dyadic cognitive report and subjective cognitive decline in early ADRD clinical research and trials: Current knowledge, gaps, and recommendations

Nosheny

Amariglio

Sikkes

et al. 2022

A&D Transl Res & Clin Interv

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Efficient identification of cognitive decline and Alzheimer's disease (AD) risk in early stages of the AD disease continuum is a critical unmet need. Subjective cognitive decline is increasingly recognized as an early symptomatic stage of AD. Dyadic cognitive report, including subjective cognitive complaints (SCC) from a participant and an informant/study partner who knows the participant well, represents an accurate, reliable, and efficient source of data for assessing risk. However, the separate and combined contributions of self‐ and study partner report, and the dynamic relationship between the two, remains unclear. The Subjective Cognitive Decline Professional Interest Area within the Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment convened a working group focused on dyadic patterns of subjective report. Group members identified aspects of dyadic‐report information important to the AD research field, gaps in knowledge, and recommendations. By reviewing existing data on this topic, we found evidence that dyadic measures are associated with objective measures of cognition and provide unique information in preclinical and prodromal AD about disease stage and progression and AD biomarker status. External factors including dyad (participant–study partner pair) relationship and sociocultural factors contribute to these associations. We recommend greater dyad report use in research settings to identify AD risk. Priority areas for future research include (1) elucidation of the contributions of demographic and sociocultural factors, dyad type, and dyad relationship to dyad report; (2) exploration of agreement and discordance between self‐ and study partner report across the AD syndromic and disease continuum; (3) identification of domains (e.g., memory, executive function, neuropsychiatric) that predict AD risk outcomes and differentiate cognitive impairment due to AD from other impairment; (4) development of best practices for study partner engagement; (5) exploration of study partner report as AD clinical trial endpoints; (6) continued development, validation, and optimization, of study partner report instruments tailored to the goals of the research and population.

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Section: Associations Between Dyad‐reported Scc and Ad Biomarkersmentioning

confidence: 99%

The role of dyadic cognitive report and subjective cognitive decline in early ADRD clinical research and trials: Current knowledge, gaps, and recommendations

Nosheny

Amariglio

Sikkes

et al. 2022

A&D Transl Res & Clin Interv

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“…Table 1 presents the characteristics describing the random sample of 200 dyads analyzed in this study. As is the case for the larger CARE IDEAS study, 22 this sample of scan recipients was primarily male, while the care partners were primarily female. Scan recipients and care partners were almost entirely white, non‐Hispanic, and married, and were highly educated.…”

Section: Resultsmentioning

confidence: 81%

“Now at least we have something to call it”: Patient and care partner experiences receiving an amyloid PET scan

Gadbois

Bélanger

Shield

et al. 2022

J American Geriatrics Society

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Background The primary objective of this paper was to examine perspectives and experiences of individuals with cognitive impairment who received an amyloid PET scan and their care partners, with regard to the process, logistics, and decision‐making associated with receiving an amyloid PET scan and its results. Methods Structured telephone interviews were conducted with 200 randomly sampled scan recipient/care partner dyads from the CARE IDEAS study. The audio‐recorded, transcribed responses were analyzed using an inductive qualitative content analytic approach. Results Participating individuals and care partners described their experiences in seeking a diagnosis for memory issues, including decision‐making and logistics involved with receiving an amyloid PET scan. Participants discussed the factors contributing to their decision to seek a diagnosis for their memory issues and their hopes and expectations in completing the scan. Participants also described the trajectory of this process, and although some described relatively straightforward trajectories, others described problems associated with identifying appropriate providers and coordinating care across numerous providers to obtain a diagnosis for their memory issues. Participants described an additional challenge of physicians attributing cognitive decline to normal aging, rather than signs of a neurodegenerative disorder. Conclusions Findings shed light on the barriers and delays that individuals and care partners experience in connecting with physicians and obtaining a comprehensive evaluation for cognitive problems. Results from this study have implications for physicians who provide care to older adults, and specifically highlight the need for greater care coordination and clearer communication with and systems of referral for patients.

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“…The OVBM framework can be used for various tasks such as speech segmentation and transcription -in this paper we demonstrate it in the individualized and explainable diagnostic of Alzheimer's Dementia (AD) patients, where, as shown in Table 1 we achieve above state-of-the-art accuracy of 93.8% [4] and using only raw audio as input, while extracting, for each subject a saliency map with the relative disease progression of 16 biomarkers. Even with expensive CT scans, to date experts can not create consistent biomarkers [5,6,7] even when including emotional biomarkers, unlike our approach which automatically develops them from free speech. Experts point at this lack of biomarkers as the reason why no new drug has been introduced in the last 16 years despite AD [8] being the sixth leading cause of death in the United States [9], and one of the leading unavoidable causes for loss of healthy life.…”

Section: Authormentioning

confidence: 99%

Longitudinal Speech Biomarkers for Automated Alzheimer's Detection

Laguarta

Hueto

Rajasekaran

et al. 2020

Preprint

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Background: We introduce a novel speech processing framework, the MIT CBMM Open Voice Brain Model (OVBM), combining implementations of the 4 modules of intelligence: The brain OS chunks and overlaps audio samples and transfers CNN features from the sensory stream and cognitive core creating a multi-modal graph neural network of symbolic compositional models for the target task.Methods: Our approach consists of pre-training models to extract acoustic features from selected biomarkers and then leverage transfer learning to combine the biomarker feature extractors into a graph neural network to provide an explainable diagnsotic for Alzheimer's Dementia (AD) using speech recordings.Results: We apply OVBM to the automated diagnostic of Alzheimer's Dementia patients, achieving above state-of-the-art accuracy of 93.8% using only raw audio, while extracting a personalized subject saliency map to track relative disease progression of 16 explainable biomarkers.Conclusion: By using independent biomarker models, OVBM lets health experts explore biomarker features and whether there are common biomarkers features between AD and other diseases like COVID-19. We present a novel lungs and respiratory tract biomarker created using 200.000+ cough samples to pre-train a model discriminating English from Catalan coughs. Transfer Learning is subsequently used to transfer features from this model with various other biomarker OVBM models. This strategy yielded consistent improvements in ADdetection, no matter the combination used. This cough dataset sets a new benchmark as largest audio health dataset with 30.000+ subjects participating in April 2020, demonstrating for the rst time cough cultural bias.

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How Accurately Do Patients and Their Care Partners Report Results of Amyloid-β PET Scans for Alzheimer’s Disease Assessment?

Cited by 19 publications

References 24 publications

The role of dyadic cognitive report and subjective cognitive decline in early ADRD clinical research and trials: Current knowledge, gaps, and recommendations

The role of dyadic cognitive report and subjective cognitive decline in early ADRD clinical research and trials: Current knowledge, gaps, and recommendations

“Now at least we have something to call it”: Patient and care partner experiences receiving an amyloid PET scan

Longitudinal Speech Biomarkers for Automated Alzheimer's Detection

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