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http://hdl.handle.net/1942/19148
Title: | Correcting for the Absence of a Gold Standard Improves Diagnostic Accuracy of Biomarkers in Alzheimer's Disease | Authors: | Coart, Els GARCIA BARRADO, Leandro Duits, Flora H. Scheltens, Philip van der Flier, Wiesje M. Teunissen, Charlotte E. van der Vies, Saskia M. BURZYKOWSKI, Tomasz |
Issue Date: | 2015 | Publisher: | IOS PRESS | Source: | JOURNAL OF ALZHEIMERS DISEASE, 46 (4), p. 889-899 | Abstract: | Background: Studies investigating the diagnostic accuracy of biomarkers for Alzheimer's disease (AD) are typically performed using the clinical diagnosis or amyloid-beta positron emission tomography as the reference test. However, neither can be considered a gold standard or a perfect reference test for AD. Not accounting for errors in the reference test is known to cause bias in the diagnostic accuracy of biomarkers. Objective: To determine the diagnostic accuracy of AD biomarkers while taking the imperfectness of the reference test into account. Methods: To determine the diagnostic accuracy of AD biomarkers and taking the imperfectness of the reference test into account, we have developed a Bayesian method. This method establishes the biomarkers' true value in predicting the AD-pathology status by combining the reference test and the biomarker data with available information on the reliability of the reference test. The new methodology was applied to two clinical datasets to establish the joint accuracy of three cerebrospinal fluid biomarkers (amyloid-beta(1-42), Total tau, and P-tau(181p)) by including the clinical diagnosis as imperfect reference test into the analysis. Results: The area under the receiver-operating-characteristics curve to discriminate between AD and controls, increases from 0.949 (with 95% credible interval [0.935,0.960]) to 0.990 ([0.985,0.995]) and from 0.870 ([0.817,0.912]) to 0.975 ([0.943,0.990]) for the cohorts, respectively. Conclusions: Use of the Bayesian methodology enables an improved estimate of the exact diagnostic value of AD biomarkers and overcomes the lack of a gold standard for AD. Using the new method will increase the diagnostic confidence for early stages of AD. | Notes: | [Coart, Els; Burzykowski, Tomasz] IDDI, B-1340 Louvain La Neuve, Belgium. [Barrado, Leandro Garcia; Burzykowski, Tomasz] Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat I BioSt, Diepenbeek, Belgium. [Duits, Flora H.; Scheltens, Philip; van der Flier, Wiesje M.] Vrije Univ Amsterdam Med Ctr, Alzheimer Ctr, Amsterdam, Netherlands. [Duits, Flora H.; Scheltens, Philip; van der Flier, Wiesje M.] Vrije Univ Amsterdam Med Ctr, Dept Neurol, Amsterdam, Netherlands. [van der Flier, Wiesje M.] Vrije Univ Amsterdam Med Ctr, Dept Epidemiol & Biostat, Amsterdam, Netherlands. [Teunissen, Charlotte E.] Vrije Univ Amsterdam Med Ctr, Dept Clin Chem, Neurochem Lab & Biobank, Amsterdam, Netherlands. [van der Vies, Saskia M.] Vrije Univ Amsterdam Med Ctr, Dept Pathol, Amsterdam, Netherlands. | Keywords: | Alzheimer's disease; Bayesian method; biomarkers; diagnostic test; reference standard;Alzheimer’s disease; Bayesian method; biomarkers; diagnostic test; reference standard | Document URI: | http://hdl.handle.net/1942/19148 | ISSN: | 1387-2877 | e-ISSN: | 1875-8908 | DOI: | 10.3233/JAD-142886 | ISI #: | 000357429300008 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2016 |
Appears in Collections: | Research publications |
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