Loading your page…
Alzheimer's & dementia
By Earnest T, Yang B, Kothapalli D and 2 others.
Few studies have investigated how different Alzheimer's disease biomarker definitions affect predictions of cognitive decline.
Ward brings these articles into the same app as your cards and questions. One free account for Ward, Suture, Osler and Prognia.
We predicted cognitive decline using 42 biomarker definitions spanning amyloid beta, tau, and neurodegeneration in 383 ADNI participants with baseline neuroimaging and longitudinal cognitive assessments. We identified optimal predictors for each pathology and variable type (continuous, binary, non-binary categorical) using nested cross-validation. Models were compared against support vector machines (SVMs) incorporating brain-wide pathology. In a subsample, we compared imaging-based biomarkers with biofluids (cerebrospinal fluid and plasma).
We observed substantial variability in accuracy, even for measures of the same pathology. Tau biomarkers were most accurate, performing comparably to models incorporating all three pathologies. Binarization of biomarkers mostly preserved accuracy, while SVMs trained on brain-wide pathology data generally did not improve performance. Imaging-based biomarkers consistently outperformed biofluid ones.
Imaging-based biomarker definitions are not interchangeable and can influence the assessment of cognitive decline.
Published in Alzheimer's & dementia (Amsterdam, Netherlands). The abstract is shown as published and remains the work of its authors; read the full article at the source.
Prognia lists this article for reference and education. It is not medical advice. Always read the original and follow current guidelines and local protocols before acting on it.
