Derivation of cutoffs for the Elecsys® amyloid β (1–42) assay in Alzheimer's disease
An Elecsys® Amyloid β (Aβ [1–42]) immunoassay cutoff for classification of patients with Alzheimer's disease was investigated. Cerebrospinal fluid samples collected from patients with mild-to-moderate Alzheimer's disease were analyzed by Elecsys® immunoassays: (1) Aβ (1–42), (2) total tau,...
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| Published in | Alzheimer's & dementia : diagnosis, assessment & disease monitoring Vol. 10; no. 1; pp. 698 - 705 |
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| Main Authors | , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
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United States
Elsevier Inc
2018
Elsevier Wiley |
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| Abstract | An Elecsys® Amyloid β (Aβ [1–42]) immunoassay cutoff for classification of patients with Alzheimer's disease was investigated.
Cerebrospinal fluid samples collected from patients with mild-to-moderate Alzheimer's disease were analyzed by Elecsys® immunoassays: (1) Aβ (1–42), (2) total tau, and (3) phosphorylated tau. Cutoffs (Aβ [1–42] and ratios with tau) were estimated by method comparison between AlzBio3 (n = 206), mixture modeling (n = 216), and concordance with florbetapir F 18 imaging-based classification (n = 75).
A 1065-pg/mL (95% confidence interval: 985–1153) Elecsys® Aβ (1–42) cutoff provided 94% overall percentage agreement with AlzBio3. Comparable cutoff estimates (95% confidence interval) were derived from mixture modeling (equally weighted: 1017 [949–1205] pg/mL; prevalence weighted: 1172 [1081–1344] pg/mL) and concordance with florbetapir F 18 imaging (visual read: 1198 [998–1591] pg/mL; automated: 1198 [1051–1638] pg/mL).
Based on three approaches, a 1100-pg/mL Elecsys® Aβ (1–42) cutoff is suitable for clinical trials with similar populations and preanalytical handling.
•Biomarkers can facilitate appropriate patient recruitment into clinical trials.•Amyloid beta measurement can aid the identification of amyloid-positive patients.•Similar cutoff estimates were derived by three different approaches. |
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| AbstractList | Abstract Introduction An Elecsys® Amyloid β (Aβ [1–42]) immunoassay cutoff for classification of patients with Alzheimer's disease was investigated. Methods Cerebrospinal fluid samples collected from patients with mild‐to‐moderate Alzheimer's disease were analyzed by Elecsys® immunoassays: (1) Aβ (1–42), (2) total tau, and (3) phosphorylated tau. Cutoffs (Aβ [1–42] and ratios with tau) were estimated by method comparison between AlzBio3 (n = 206), mixture modeling (n = 216), and concordance with florbetapir F 18 imaging‐based classification (n = 75). Results A 1065‐pg/mL (95% confidence interval: 985–1153) Elecsys® Aβ (1–42) cutoff provided 94% overall percentage agreement with AlzBio3. Comparable cutoff estimates (95% confidence interval) were derived from mixture modeling (equally weighted: 1017 [949–1205] pg/mL; prevalence weighted: 1172 [1081–1344] pg/mL) and concordance with florbetapir F 18 imaging (visual read: 1198 [998–1591] pg/mL; automated: 1198 [1051–1638] pg/mL). Discussion Based on three approaches, a 1100‐pg/mL Elecsys® Aβ (1–42) cutoff is suitable for clinical trials with similar populations and preanalytical handling. An Elecsys® Amyloid β (Aβ [1-42]) immunoassay cutoff for classification of patients with Alzheimer's disease was investigated.INTRODUCTIONAn Elecsys® Amyloid β (Aβ [1-42]) immunoassay cutoff for classification of patients with Alzheimer's disease was investigated.Cerebrospinal fluid samples collected from patients with mild-to-moderate Alzheimer's disease were analyzed by Elecsys® immunoassays: (1) Aβ (1-42), (2) total tau, and (3) phosphorylated tau. Cutoffs (Aβ [1-42] and ratios with tau) were estimated by method comparison between AlzBio3 (n = 206), mixture modeling (n = 216), and concordance with florbetapir F 18 imaging-based classification (n = 75).METHODSCerebrospinal fluid samples collected from patients with mild-to-moderate Alzheimer's disease were analyzed by Elecsys® immunoassays: (1) Aβ (1-42), (2) total tau, and (3) phosphorylated tau. Cutoffs (Aβ [1-42] and ratios with tau) were estimated by method comparison between AlzBio3 (n = 206), mixture modeling (n = 216), and concordance with florbetapir F 18 imaging-based classification (n = 75).A 1065-pg/mL (95% confidence interval: 985-1153) Elecsys® Aβ (1-42) cutoff provided 94% overall percentage agreement with AlzBio3. Comparable cutoff estimates (95% confidence interval) were derived from mixture modeling (equally weighted: 1017 [949-1205] pg/mL; prevalence weighted: 1172 [1081-1344] pg/mL) and concordance with florbetapir F 18 imaging (visual read: 1198 [998-1591] pg/mL; automated: 1198 [1051-1638] pg/mL).RESULTSA 1065-pg/mL (95% confidence interval: 985-1153) Elecsys® Aβ (1-42) cutoff provided 94% overall percentage agreement with AlzBio3. Comparable cutoff estimates (95% confidence interval) were derived from mixture modeling (equally weighted: 1017 [949-1205] pg/mL; prevalence weighted: 1172 [1081-1344] pg/mL) and concordance with florbetapir F 18 imaging (visual read: 1198 [998-1591] pg/mL; automated: 1198 [1051-1638] pg/mL).Based on three approaches, a 1100-pg/mL Elecsys® Aβ (1-42) cutoff is suitable for clinical trials with similar populations and preanalytical handling.DISCUSSIONBased on three approaches, a 1100-pg/mL Elecsys® Aβ (1-42) cutoff is suitable for clinical trials with similar populations and preanalytical handling. Biomarkers can facilitate appropriate patient recruitment into clinical trials. Amyloid beta measurement can aid the identification of amyloid‐positive patients. Similar cutoff estimates were derived by three different approaches. • Biomarkers can facilitate appropriate patient recruitment into clinical trials. • Amyloid beta measurement can aid the identification of amyloid-positive patients. • Similar cutoff estimates were derived by three different approaches. Introduction An Elecsys® Amyloid β (Aβ [1–42]) immunoassay cutoff for classification of patients with Alzheimer's disease was investigated. Methods Cerebrospinal fluid samples collected from patients with mild‐to‐moderate Alzheimer's disease were analyzed by Elecsys® immunoassays: (1) Aβ (1–42), (2) total tau, and (3) phosphorylated tau. Cutoffs (Aβ [1–42] and ratios with tau) were estimated by method comparison between AlzBio3 (n = 206), mixture modeling (n = 216), and concordance with florbetapir F 18 imaging‐based classification (n = 75). Results A 1065‐pg/mL (95% confidence interval: 985–1153) Elecsys® Aβ (1–42) cutoff provided 94% overall percentage agreement with AlzBio3. Comparable cutoff estimates (95% confidence interval) were derived from mixture modeling (equally weighted: 1017 [949–1205] pg/mL; prevalence weighted: 1172 [1081–1344] pg/mL) and concordance with florbetapir F 18 imaging (visual read: 1198 [998–1591] pg/mL; automated: 1198 [1051–1638] pg/mL). Discussion Based on three approaches, a 1100‐pg/mL Elecsys® Aβ (1–42) cutoff is suitable for clinical trials with similar populations and preanalytical handling. Highlights Biomarkers can facilitate appropriate patient recruitment into clinical trials. Amyloid beta measurement can aid the identification of amyloid‐positive patients. Similar cutoff estimates were derived by three different approaches. An Elecsys® Amyloid β (Aβ [1–42]) immunoassay cutoff for classification of patients with Alzheimer's disease was investigated. Cerebrospinal fluid samples collected from patients with mild-to-moderate Alzheimer's disease were analyzed by Elecsys® immunoassays: (1) Aβ (1–42), (2) total tau, and (3) phosphorylated tau. Cutoffs (Aβ [1–42] and ratios with tau) were estimated by method comparison between AlzBio3 (n = 206), mixture modeling (n = 216), and concordance with florbetapir F 18 imaging-based classification (n = 75). A 1065-pg/mL (95% confidence interval: 985–1153) Elecsys® Aβ (1–42) cutoff provided 94% overall percentage agreement with AlzBio3. Comparable cutoff estimates (95% confidence interval) were derived from mixture modeling (equally weighted: 1017 [949–1205] pg/mL; prevalence weighted: 1172 [1081–1344] pg/mL) and concordance with florbetapir F 18 imaging (visual read: 1198 [998–1591] pg/mL; automated: 1198 [1051–1638] pg/mL). Based on three approaches, a 1100-pg/mL Elecsys® Aβ (1–42) cutoff is suitable for clinical trials with similar populations and preanalytical handling. •Biomarkers can facilitate appropriate patient recruitment into clinical trials.•Amyloid beta measurement can aid the identification of amyloid-positive patients.•Similar cutoff estimates were derived by three different approaches. An Elecsys® Amyloid β (Aβ [1-42]) immunoassay cutoff for classification of patients with Alzheimer's disease was investigated. Cerebrospinal fluid samples collected from patients with mild-to-moderate Alzheimer's disease were analyzed by Elecsys® immunoassays: (1) Aβ (1-42), (2) total tau, and (3) phosphorylated tau. Cutoffs (Aβ [1-42] and ratios with tau) were estimated by method comparison between AlzBio3 ( = 206), mixture modeling ( = 216), and concordance with florbetapir F 18 imaging-based classification ( = 75). A 1065-pg/mL (95% confidence interval: 985-1153) Elecsys® Aβ (1-42) cutoff provided 94% overall percentage agreement with AlzBio3. Comparable cutoff estimates (95% confidence interval) were derived from mixture modeling (equally weighted: 1017 [949-1205] pg/mL; prevalence weighted: 1172 [1081-1344] pg/mL) and concordance with florbetapir F 18 imaging (visual read: 1198 [998-1591] pg/mL; automated: 1198 [1051-1638] pg/mL). Based on three approaches, a 1100-pg/mL Elecsys® Aβ (1-42) cutoff is suitable for clinical trials with similar populations and preanalytical handling. |
| Author | Figurski, Michal Wahl, Simone Eichenlaub, Udo Andersen, Scott W. Trojanowski, John Q. Lachno, D. Richard Talbot, Jayne A. Fields, Leona Siemers, Eric R. Dean, Robert A. Korecka, Magdalena Pontecorvo, Michael J. Waligorska, Teresa Shaw, Leslie M. Quan, Marian |
| AuthorAffiliation | a Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA e Eli Lilly and Company, Windlesham, Surrey, UK b Roche Diagnostics GmbH, Bavaria, Germany c Roche Diagnostics, Indianapolis, IN, USA g Indiana University School of Medicine, Indianapolis, IN, USA d Clinical Development, Avid Radiopharmaceuticals, Philadelphia, PA, USA f Eli Lilly and Company, Indianapolis, IN, USA |
| AuthorAffiliation_xml | – name: b Roche Diagnostics GmbH, Bavaria, Germany – name: d Clinical Development, Avid Radiopharmaceuticals, Philadelphia, PA, USA – name: g Indiana University School of Medicine, Indianapolis, IN, USA – name: c Roche Diagnostics, Indianapolis, IN, USA – name: e Eli Lilly and Company, Windlesham, Surrey, UK – name: f Eli Lilly and Company, Indianapolis, IN, USA – name: a Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA |
| Author_xml | – sequence: 1 givenname: Leslie M. surname: Shaw fullname: Shaw, Leslie M. email: les.shaw@uphs.upenn.edu organization: Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA – sequence: 2 givenname: Teresa surname: Waligorska fullname: Waligorska, Teresa organization: Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA – sequence: 3 givenname: Leona surname: Fields fullname: Fields, Leona organization: Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA – sequence: 4 givenname: Magdalena surname: Korecka fullname: Korecka, Magdalena organization: Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA – sequence: 5 givenname: Michal surname: Figurski fullname: Figurski, Michal organization: Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA – sequence: 6 givenname: John Q. surname: Trojanowski fullname: Trojanowski, John Q. organization: Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA – sequence: 7 givenname: Udo surname: Eichenlaub fullname: Eichenlaub, Udo organization: Roche Diagnostics GmbH, Bavaria, Germany – sequence: 8 givenname: Simone surname: Wahl fullname: Wahl, Simone organization: Roche Diagnostics GmbH, Bavaria, Germany – sequence: 9 givenname: Marian surname: Quan fullname: Quan, Marian organization: Roche Diagnostics, Indianapolis, IN, USA – sequence: 10 givenname: Michael J. surname: Pontecorvo fullname: Pontecorvo, Michael J. organization: Clinical Development, Avid Radiopharmaceuticals, Philadelphia, PA, USA – sequence: 11 givenname: D. Richard surname: Lachno fullname: Lachno, D. Richard organization: Eli Lilly and Company, Windlesham, Surrey, UK – sequence: 12 givenname: Jayne A. surname: Talbot fullname: Talbot, Jayne A. organization: Eli Lilly and Company, Indianapolis, IN, USA – sequence: 13 givenname: Scott W. surname: Andersen fullname: Andersen, Scott W. organization: Eli Lilly and Company, Indianapolis, IN, USA – sequence: 14 givenname: Eric R. surname: Siemers fullname: Siemers, Eric R. organization: Eli Lilly and Company, Indianapolis, IN, USA – sequence: 15 givenname: Robert A. surname: Dean fullname: Dean, Robert A. organization: Indiana University School of Medicine, Indianapolis, IN, USA |
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| Keywords | Immunoassay Amyloid β Biomarkers Method comparison Cutoff determination Cerebrospinal fluid Alzheimer's disease Patient selection Florbetapir F 18 imaging |
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| Snippet | An Elecsys® Amyloid β (Aβ [1–42]) immunoassay cutoff for classification of patients with Alzheimer's disease was investigated.
Cerebrospinal fluid samples... Introduction An Elecsys® Amyloid β (Aβ [1–42]) immunoassay cutoff for classification of patients with Alzheimer's disease was investigated. Methods... Biomarkers can facilitate appropriate patient recruitment into clinical trials. Amyloid beta measurement can aid the identification of amyloid‐positive... An Elecsys® Amyloid β (Aβ [1-42]) immunoassay cutoff for classification of patients with Alzheimer's disease was investigated. Cerebrospinal fluid samples... An Elecsys® Amyloid β (Aβ [1-42]) immunoassay cutoff for classification of patients with Alzheimer's disease was investigated.INTRODUCTIONAn Elecsys® Amyloid β... • Biomarkers can facilitate appropriate patient recruitment into clinical trials. • Amyloid beta measurement can aid the identification of amyloid-positive... Abstract Introduction An Elecsys® Amyloid β (Aβ [1–42]) immunoassay cutoff for classification of patients with Alzheimer's disease was investigated. Methods... |
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| SubjectTerms | Alzheimer's disease Amyloid β Biomarkers Cerebrospinal fluid CSF Biomarkers Cutoff determination Florbetapir F 18 imaging Immunoassay Method comparison Patient selection |
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| Title | Derivation of cutoffs for the Elecsys® amyloid β (1–42) assay in Alzheimer's disease |
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