TY - JOUR
T1 - A Pragmatic, Data-Driven Method to Determine Cutoffs for CSF Biomarkers of Alzheimer Disease Based on Validation Against PET Imaging
AU - Alzheimer's Disease Neuroimaging Initiative
AU - Dumurgier, Julien
AU - Sabia, S. verine
AU - Zetterberg, Henrik
AU - Teunissen, Charlotte E.
AU - Hanseeuw, Bernard
AU - Orellana, Adelina
AU - Schraen, Susanna
AU - Gabelle, Audrey
AU - Boada, Mercè
AU - Lebouvier, Thibaud
AU - Willemse, Eline A. J.
AU - Cognat, Emmanuel
AU - Ruiz, Agustin
AU - Hourregue, Claire
AU - Lilamand, Matthieu
AU - Bouaziz-Amar, Elodie
AU - Laplanche, Jean-Louis
AU - Lehmann, Sylvain
AU - Pasquier, Florence
AU - Scheltens, Philip
AU - Blennow, Kaj
AU - Singh-Manoux, Archana
AU - Paquet, Claire
N1 - Funding Information: The Article Processing Charge was funded by the authors. Funding Information: H. Zetterberg is a Wallenberg Scholar supported by grants from the Swedish Research Council (#2018-02532), the European Research Council (#681712), Swedish State Support for Clinical Research (#ALFGBG-720931), the Alzheimer Drug Discovery Foundation (ADDF), USA (#201809-2016862), and the UK Dementia Research Institute atUCL. K. Blennow is supported by the Swedish Research Council (#2017-00915), the Alzheimer Drug Discovery Foundation (ADDF), USA (#RDAPB-201809-2016615), the Swedish Alzheimer Foundation (#AF-742881), Hjärnfonden, Sweden (#FO2017-0243), the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-715986), and the European Union Joint Program for NeurodegenerativeDisorders (JPND2019-466-236). A. Singh-Manoux is supported by grants from the National Institute on Aging, NIH (R01AG056477, RF1AG06255). Publisher Copyright: © American Academy of Neurology.
PY - 2022/8/16
Y1 - 2022/8/16
N2 - BACKGROUND AND OBJECTIVES: To elaborate a new algorithm to establish a standardized method to define cutoffs for CSF biomarkers of Alzheimer disease (AD) by validating the algorithm against CSF classification derived from PET imaging. METHODS: Low and high levels of CSF phosphorylated tau were first identified to establish optimal cutoffs for CSF β-amyloid (Aβ) peptide biomarkers. These Aβ cutoffs were then used to determine cutoffs for CSF tau and phosphorylated tau markers. We compared this algorithm to a reference method, based on tau and amyloid PET imaging status (ADNI study), and then applied the algorithm to 10 large clinical cohorts of patients. RESULTS: A total of 6,922 patients with CSF biomarker data were included (mean [SD] age: 70.6 [8.5] years, 51.0% women). In the ADNI study population (n = 497), the agreement between classification based on our algorithm and the one based on amyloid/tau PET imaging was high, with Cohen's kappa coefficient between 0.87 and 0.99. Applying the algorithm to 10 large cohorts of patients (n = 6,425), the proportion of persons with AD ranged from 25.9% to 43.5%. DISCUSSION: The proposed novel, pragmatic method to determine CSF biomarker cutoffs for AD does not require assessment of other biomarkers or assumptions concerning the clinical diagnosis of patients. Use of this standardized algorithm is likely to reduce heterogeneity in AD classification.
AB - BACKGROUND AND OBJECTIVES: To elaborate a new algorithm to establish a standardized method to define cutoffs for CSF biomarkers of Alzheimer disease (AD) by validating the algorithm against CSF classification derived from PET imaging. METHODS: Low and high levels of CSF phosphorylated tau were first identified to establish optimal cutoffs for CSF β-amyloid (Aβ) peptide biomarkers. These Aβ cutoffs were then used to determine cutoffs for CSF tau and phosphorylated tau markers. We compared this algorithm to a reference method, based on tau and amyloid PET imaging status (ADNI study), and then applied the algorithm to 10 large clinical cohorts of patients. RESULTS: A total of 6,922 patients with CSF biomarker data were included (mean [SD] age: 70.6 [8.5] years, 51.0% women). In the ADNI study population (n = 497), the agreement between classification based on our algorithm and the one based on amyloid/tau PET imaging was high, with Cohen's kappa coefficient between 0.87 and 0.99. Applying the algorithm to 10 large cohorts of patients (n = 6,425), the proportion of persons with AD ranged from 25.9% to 43.5%. DISCUSSION: The proposed novel, pragmatic method to determine CSF biomarker cutoffs for AD does not require assessment of other biomarkers or assumptions concerning the clinical diagnosis of patients. Use of this standardized algorithm is likely to reduce heterogeneity in AD classification.
UR - http://www.scopus.com/inward/record.url?scp=85136035653&partnerID=8YFLogxK
U2 - https://doi.org/10.1212/WNL.0000000000200735
DO - https://doi.org/10.1212/WNL.0000000000200735
M3 - Article
C2 - 35970577
SN - 0028-3878
VL - 99
SP - e669-e678
JO - Neurology
JF - Neurology
IS - 7
ER -