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Novel Biomarker-Based Model Can Adequately Predict Dementia

Researchers have developed a novel prediction model that utilizes amyloid deposition, tauopathy, and neurodegeneration biomarkers to accurately predict disease progression in individuals at risk for dementia. 

According to their study’s findings, the researchers report that the newly constructed model, as well as the previously developed demographics model, hippocampal volume model, and cerebrospinal fluid (CSF) biomarkers model, have adequate prognostic performance.


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“The models could aid clinicians in the interpretation of CSF biomarker and hippocampal volume results in individuals with [mild cognitive impairment (MCI)] and help research and clinical settings to prepare for a future of precision medicine in Alzheimer disease,” according to the researchers.

To analyze the models’ prognostic abilities, the researchers assessed for the clinical progression to any type of dementia among 2611 participants from the European Medical Information Framework for Alzheimer's Disease, Alzheimer's Disease Neuroimaging Initiative, Amsterdam Dementia Cohort, and the Swedish BioFINDER study. 

To be included in the analysis, the participants all had to have a baseline diagnosis of MCI and at least 6 months of follow-up, as well as the availability of a baseline Mini-Mental State Examination and magnetic resonance imaging or CSF biomarker assessment.

The researchers first investigated the performance of the demographics, hippocampal volume, and CSF biomarkers risk prediction models by evaluating each across cohorts, incorporating different biomarker measurement methods, and determining prognostic performance. After that, the researchers updated the models by re-estimating parameters with and without center-specific effects. They also evaluated model calibration by comparing observed survival with expected survival.

The novel model (ATN) was developed by combining markers for amyloid deposition, tauopathy, and neurodegeneration and was in line with the National Institute on Aging and Alzheimer's Association research framework.

In all, 1007 (39%) of the participants progressed to dementia. The researchers determined that the validated demographics and hippocampal volume models, as well as the updated CSF biomarkers model, had adequate prognostic performance across cohorts and were well calibrated. However, the newly constructed model (ATN) had the highest performance. 

“We generated risk models that are robust across cohorts, which adds to their potential clinical applicability,” the researchers concluded. “Future research should focus on the clinical utility of the models, particularly if their use affects participants' understanding, emotional wellbeing, and behavior.”

—Colleen Murphy

Reference:

van Maurik IS, Vos SJ, Bos I, et al; Alzheimer’s Disease Neuroimaging Initiative. Biomarker-based prognosis for people with mild cognitive impairment (ABIDE): a modelling study. Lancet Neurol. 2019;18(11):1034-1044. doi:10.1016/S1474-4422(19)30283-2.