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Decision tree-based classification as a support to diagnosis in the Alzheimer's disease continuum using cerebrospinal fluid biomarkers: insights from automated analysis

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Autor(es):
Costa, Alana ; Pais, Marcos ; Loureiro, Julia ; Stella, Florindo ; Radanovic, Marcia ; Gattaz, Wagner ; Forlenza, Orestes ; Talib, Leda
Número total de Autores: 8
Tipo de documento: Artigo Científico
Fonte: Revista Brasileira de Psiquiatria; v. 44, n. 4, p. 8-pg., 2022-07-01.
Resumo

Objective: Cerebrospinal fluid (CSF) biomarkers add accuracy to the diagnostic workup of cognitive impairment by illustrating Alzheimer's disease (AD) pathology. However, there are no universally accepted cutoff values for the interpretation of AD biomarkers. The aim of this study is to determine the viability of a decision-tree method to analyse CSF biomarkers of AD as a support for clinical diagnosis. Methods: A decision-tree method (automated classification analysis) was applied to concentrations of AD biomarkers in CSF as a support for clinical diagnosis in older adults with or without cognitive impairment in a Brazilian cohort. In brief, 272 older adults (68 with AD, 122 with mild cognitive impairment [MCI], and 82 healthy controls) were assessed for CSF concentrations of A beta(1-42), total-tau, and phosphorylated-tau using multiplexed Luminex assays; biomarker values were used to generate decision-tree algorithms (classification and regression tree) in the R statistical software environment. Results: The best decision tree model had an accuracy of 74.65% to differentiate the three groups. Cluster analysis supported the combination of CSF biomarkers to differentiate AD and MCI vs. controls, suggesting the best cutoff values for each clinical condition. Conclusion: Automated analyses of AD biomarkers provide valuable information to support the clinical diagnosis of MCI and AD in research settings. (AU)

Processo FAPESP: 17/26291-2 - Marcadores periféricos de metabolismo de membrana: caracterização de indivíduos com alto risco para psicose
Beneficiário:Alana Caroline Costa
Modalidade de apoio: Bolsas no Brasil - Doutorado
Processo FAPESP: 14/50873-3 - INCT 2014: Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN)
Beneficiário:Wagner Farid Gattaz
Modalidade de apoio: Auxílio à Pesquisa - Temático