Abstract
Background:Despite decades of research on the optimization of the diagnosis of Alzheimer’s disease (AD), its biomarker-based diagnosis is being hampered by the lack of comparability of raw biomarker data. In order to overcome this limitation, the Erlangen Score (ES), among other approaches, was set up as a diagnostic-relevant interpretation algorithm.Objective:To validate the ES algorithm in a cohort of neuropathologically confirmed cases with AD (n = 106) and non-AD dementia (n = 57).Methods:Cerebrospinal fluid (CSF) biomarker concentrations of Aβ1-42, T-tau, and P-tau181 were measured with commercially available single analyte ELISA kits. Based on these biomarkers, ES was calculated as previously reported.Results:This algorithm proved to categorize AD in different degrees of likelihood, ranging from neurochemically “normal”, “improbably having AD”, “possibly having AD”, to “probably having AD”, with a diagnostic accuracy of 74% using the neuropathology as a reference.Conclusion:The ability of the ES to overcome the high variability of raw CSF biomarker data may provide a useful diagnostic tool for comparing neurochemical diagnoses between different labs or methods used.
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