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Incremental Value of CSF Biomarkers in Clinically Diagnosed AD and Non-AD Dementia

Background: Cerebrospinal fluid (CSF) biomarkers are used to diagnose Alzheimer disease (AD), especially in atypical clinical presentations. No consensus currently exists regarding cut-off values. This study aimed, firstly, to define optimal cut-off values for CSF biomarkers, and secondly, to invest...

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Detalles Bibliográficos
Autores principales: Oudart, Jean-Baptiste, Djerada, Zoubir, Nonnonhou, Vignon, Badr, Sarah, Bertholon, Laurie-Anne, Dammak, Anis, Jaidi, Yacine, Novella, Jean-Luc, Pallet, Nicolas, Gillery, Philippe, Mahmoudi, Rachid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7330115/
https://www.ncbi.nlm.nih.gov/pubmed/32670183
http://dx.doi.org/10.3389/fneur.2020.00560
Descripción
Sumario:Background: Cerebrospinal fluid (CSF) biomarkers are used to diagnose Alzheimer disease (AD), especially in atypical clinical presentations. No consensus currently exists regarding cut-off values. This study aimed, firstly, to define optimal cut-off values for CSF biomarkers, and secondly, to investigate the most relevant diagnostic strategy for AD based on CSF biomarker combinations. Methods: A total of 380 patients were prospectively included: 140 with AD, 240 with various neurological diagnoses (non-AD). CSF biomarkers were measured using ELISA. Univariate and multivariate analyses were performed using random forest and logistic regression approaches. Results: Univariate receiver operating curve curves analysis of T-Tau, P-Tau(181), Aβ(42), Aβ(40) concentrations, and Aβ(42)/Aβ(40) ratio levels showed AD cut-off values of ≥355, ≥57, ≤706, ≥10,854, and ≤0.059 ng/L, respectively. Multivariate analysis using random forest and logistic regression found that the algorithm based on P-Tau(181), Aβ(42) concentrations and Aβ(42)/Aβ(40) ratio yielded the best discrimination between AD and non-AD populations. The cross-validation technique of the final model showed a mean accuracy of 0.85 and a mean AUC of 0.89. Conclusion: This study confirms that the Aβ(42)/Aβ(40) ratio was more useful than the Aβ(40) concentration in discriminating AD from non-AD populations in daily practice. These results indicate that the Aβ(42)/Aβ(40) ratio should be assessed in all cases, independently of Aβ(42) concentrations.