Cited by 375Clinical Laboratory Practices and Quality ControlAlzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

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Technical performance of a novel, fully automated electrochemiluminescence immunoassay for the quantitation of β‐amyloid (1–42) in human cerebrospinal fluid

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Bittner, Tobias, Zetterberg, Henrik, Teunissen, Charlotte E., Ostlund, Richard E., Militello, Michael, Andreasson, Ulf, Hubeek, Isabelle, Gibson, David, Chu, David C., Eichenlaub, Udo, Heiss, Peter, Kobold, Uwe, Leinenbach, Andreas, Madin, Kairat, Manuilova, Ekaterina, Rabe, Christina, Blennow, Kaj·2016·Alzheimer's & Dementia

DOI 10.1016/j.jalz.2015.09.009

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Abstract

INTRODUCTION: Available assays for quantitation of the Alzheimer's disease (AD) biomarker amyloid-beta 1-42 (Aβ [1-42]) in cerebrospinal fluid demonstrate significant variability and lack of standardization to reference measurement procedures (RMPs). We report analytical performance data for the novel Elecsys β-amyloid (1-42) assay (Roche Diagnostics). METHODS: Lot-to-lot comparability was tested using method comparison. Performance parameters were measured according to Clinical & Laboratory Standards Institute (CLSI) guidelines. The assay was standardized to a Joint Committee for Traceability in Laboratory Medicine (JCTLM) approved RMP. RESULTS: Limit of quantitation was <11.28 pg/mL, and the assay was linear throughout the measuring range (200-1700 pg/mL). Excellent lot-to-lot comparability was observed (correlation coefficients [Pearson's r] >0.995; bias in medical decision area <2%). Repeatability coefficients of variation (CVs) were 1.0%-1.6%, intermediate CVs were 1.9%-4.0%, and intermodule CVs were 1.1%-3.9%. Estimated total reproducibility was 2.0%-5.1%. Correlation with the RMP was good (Pearson's r, 0.93). DISCUSSION: The Elecsys β-amyloid (1-42) assay has high analytical performance that may improve biomarker-based AD diagnosis.

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Alzheimer disease in the United States (2010–2050) estimated using the 2010 census
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Two Phase 3 Trials of Bapineuzumab in Mild-to-Moderate Alzheimer's Disease
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Self-citation
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Phase 3 Trials of Solanezumab for Mild-to-Moderate Alzheimer's Disease
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A New Biometrical Procedure for Testing the Equality of Measurements from Two Different Analytical Methods. Application of linear regression procedures for method comparison studies in Clinical Chemistry, Part I
Passing, H., & Bablok, W. (1983) · cclm · doi:10.1515/cclm.1983.21.11.709 · Cited by 1,513
Cerebrospinal Fluid Levels ofβ-Amyloid 1-42, but Not of Tau, Are Fully Changed Already 5 to 10 Years Before the Onset of Alzheimer Dementia
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Clinical Pharmacokinetics of Metformin
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Show all 37 references

Research works printed but not linked: 8

Clinical Laboratory and Standards Institute (CLSI), 2012, Evaluation of detection capability for clinical laboratory measurement procedures: Approved guideline—Second edition. CLSI Document EP17–A2
Clinical Laboratory and Standards Institute (CLSI), 2003, Evaluation of the linearity of quantitative measurement procedures: A statistical approach; approved guideline. CLSI Document EP06‐A
Clinical Laboratory and Standards Institute (CLSI), 2013, Measurement procedure comparison and bias estimation using patient samples; approved guideline—Third edition. CLSI Document EP09–A3
Clinical Laboratory and Standards Institute (CLSI), 2005, Interference testing in clinical chemistry; approved guideline—Second edition. CLSI Document EP7–A2
Clinical Laboratory and Standards Institute (CLSI), 2008, Immunoassay interference by endogenous antibodies; approved guideline. CLSI Document I/LA30‐A
Clinical Laboratory and Standards Institute (CLSI), 2014, Evaluation of precision of quantitative measurement procedures; approved guideline—Third edition. CLSI Document EP05–A3
Clinical Laboratory and Standards Institute (CLSI), 2014, User verification of performance for precision and trueness; approved guideline—Second edition. CLSI Document EP15–A2
Scheltens P, 2014, Baseline patient characteristics from the phase 3 SCarlet RoAD trial, a study of gantenerumab in patients with prodromal AD, J Prev Alzheimers Dis, 1, 231

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Bittner, T., Tonietto, M., Klein, G., Belusov, A., Illiano, V., Voyle, N., Delmar, P., Scelsi, M. A., Gobbi, S., Silvestri, E., et al. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.14414 · Cited by 23
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Frisoni, G. B., & Hansson, O. (2016) · The Lancet Neurology · doi:10.1016/s1474-4422(16)30040-0 · Cited by 14
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Xiong, C., Luo, J. R., Agboola, F., Li, Y., Albert, M., Johnson, S. C., Koscik, R. L., Masters, C. L., Soldan, A., Villemagne, V. L., et al. (2019) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2019.06.4955 · Cited by 13
Effect of APOE ε4 genotype on amyloid‐β, glucose metabolism, and gray matter volume in cognitively normal individuals and amnestic mild cognitive impairment
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Authors: Bittner, T., Zetterberg, H., Teunissen, C. E., Ostlund, R. E., Militello, M., Andreasson, U., Hubeek, I., Gibson, D., Chu, D. C., Eichenlaub, U., Heiss, P., Kobold, U., Leinenbach, A., Madin, K., Manuilova, E., Rabe, C., & Blennow, K.
Affiliations: Roche Diagnostics GmbH Penzberg Germany
UCL Queen Square Institute of Neurology (GB)
Amsterdam UMC Location Vrije Universiteit Amsterdam (NL)
Washington University in St. Louis (US)
Covance (United States) (US)
Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology The Sahlgrenska Academy at University of Gothenburg Mölndal Sweden
University of Gothenburg (SE)
Corresponding author: Blennow, Kaj
ORCID: Bittner, Tobias
Zetterberg, Henrik
Teunissen, Charlotte E.
Kobold, Uwe
Blennow, Kaj
Venue: Alzheimer's & Dementia
Publisher: Wiley
Published: 2015-11-07
Volume: 12
Issue: 5
Pages: 517-526
ISSN: 1552-5260 (ISSN-L)
1552-5279
DOI: 10.1016/j.jalz.2015.09.009
OpenAlex: W2111951761
Cited by: 374
References: 37
Citations by year: 2026: 27 · 2025: 41 · 2024: 49 · 2023: 29 · 2022: 35 · 2021: 52 · 2020: 41 · 2019: 39 · 2018: 33 · 2017: 15 · 2016: 11
FWCI: 14.49
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by-nc-nd
creativecommons.org/licenses/by-nc-nd/4.0/ (vor)
Locations: Alzheimer s & Dementia (publishedVersion, cc-by-nc-nd)
PubMed (publishedVersion)
Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
Digital Commons@Becker (Washington University School of Medicine) (submittedVersion, cc-by-nc-nd)
Pure Amsterdam UMC (submittedVersion, other-oa)
Data Archiving and Networked Services (DANS) (submittedVersion)
Funders: Roche Diagnostics GmbH
Torsten Söderberg Foundation
Topics: Health Sciences › Health Professions › Medical Laboratory Technology › Clinical Laboratory Practices and Quality Control
Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
Keywords: amyloid-beta 42, cerebrospinal fluid
MeSH terms: Alzheimer Disease, Humans, Immunoassay, Peptide Fragments, Reference Standards, Reproducibility of Results, Biomarkers, Amyloid beta-Peptides, Luminescence

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Technical performance of a novel, fully automated electrochemiluminescence immunoassay for the quantitation of β‐amyloid (1–42) in human cerebrospinal fluid

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