The Erlangen Score Algorithm in the diagnosis and prediction of the progression from subjective cognitive decline and mild cognitive impairment to Alzheimer-type dementia.

Abstract

The evaluation of cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease (AD) (β-amyloid, t-tau, p-tau) can be used to estimate the risk of developing dementia in patients at the pre-clinical stages of AD, i.e. subjective cognitive decline (SCD) and mild cognitive impairment (MCI). Erlangen Score Algorithm allows interpretation of CSF biomarker concentrations and is cut-off value independent. The aim of this study was to establish if this algorithm can be applied for routine diagnostic testing in clinical and preclinical subjects and has prognostic value. We analysed 217 patients from the memory clinic with the diagnosis of SCD (n = 31), MCI (n = 104), and AD (n = 82) with clinical follow-up amounting to 14.33 months (SD = 6.82). It was found that the highest Erlangen Score dominated in the AD group and was the rarest in the SCD group. In the group of patients with progression of symptoms during our period of observation, the AD pathology was confirmed in 93.75% of cases. Among the non-progressing subjects (n = 119) the algorithm indicated the risk of developing AD as possible in 40.34% and probable in 15.97% of cases. To conclude, the Erlangen Score Algorithm is auseful tool to determinate the risk of developing AD before the onset of dementia or to confirm the AD diagnosis. It is extremely valuable in preclinical stages of AD for planning purposes and early intervention as well as for future clinical trials.