Validation of the Erlangen Score Algorithm for the Prediction of the Development of Dementia due to Alzheimer's Disease in Pre-Dementia Subjects

The German Dementia Competence Network, The US-ADNI

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

Background: In previous studies, a dichotomous stratification of subjects into "cerebrospinal fluid (CSF) normal" and "CSF pathologic" was used to investigate the role of biomarkers in the prediction of progression to dementia in pre-dementia/mild cognitive impairment subjects. With the previously published Erlangen Score Algorithm, we suggested a division of CSF patterns into five groups, covering all possible CSF result combinations based on the presence of pathologic tau and/or amyloid-β CSF values. Objective: This study aimed to validate the Erlangen Score diagnostic algorithm based on the results of biomarkers analyses obtained in different patients cohorts, with different pre-analytical protocols, and with different laboratory analytical platforms. Methods: We evaluated the algorithm in two cohorts of pre-dementia subjects: the US-Alzheimer's Disease Neuroimaging Initiative and the German Dementia Competence Network. Results: In both cohorts, the Erlangen scores were strongly associated with progression to Alzheimer's disease. Neither the scores of the progressors nor the scores of the non-progressors differed significantly between the two projects, in spite of significant differences in the cohorts, laboratory methods, and the samples treatment. Conclusions: Our findings confirm the utility of the Erlangen Score algorithm as a useful tool in the early neurochemical diagnosis of Alzheimer's disease.

Original languageEnglish (US)
Pages (from-to)433-441
Number of pages9
JournalJournal of Alzheimer's Disease
Volume48
Issue number2
DOIs
StatePublished - Sep 9 2015

Keywords

  • Alzheimer's disease
  • biomarkers
  • cerebrospinal fluid
  • clinical neurochemistry
  • results interpretation
  • validation

ASJC Scopus subject areas

  • Neuroscience(all)
  • Clinical Psychology
  • Geriatrics and Gerontology
  • Psychiatry and Mental health

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