Correcting for the Absence of a Gold Standard Improves Diagnostic Accuracy of Biomarkers in Alzheimer’s Disease

Article type: Research Article

Authors: Coart, Els^{a; *} | Barrado, Leandro García^b | Duits, Flora H.^c | Scheltens, Philip^c | van der Flier, Wiesje M.^{c; d} | Teunissen, Charlotte E.^e | van der Vies, Saskia M.^f | Burzykowski, Tomasz^{a; b} | for the Alzheimer’s Disease Neuroimaging Initiative

Affiliations: [a] International Drug Development Institute (IDDI), Louvain-la-Neuve, Belgium | [b] Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BioStat), Hasselt University, Diepenbeek, Belgium | [c] Alzheimer Center & Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands | [d] Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands | [e] Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands | [f] Department of Pathology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands

Correspondence: [*] Correspondence to: Els Coart, International Drug Development Institute (IDDI), Avenue Provinciale 30, 1340 Louvain-la-Neuve, Belgium. Tel.: +32 10 61 44 44; Fax: +32 10 61 88 88; [email protected]

Note: [ 1 ] Part of the data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (http://adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: https://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf.

Abstract: Background: Studies investigating the diagnostic accuracy of biomarkers for Alzheimer’s disease (AD) are typically performed using the clinical diagnosis or amyloid-β 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-β 1 - 42, Total tau, and P-tau181p) 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.

Keywords: Alzheimer’s disease, Bayesian method, biomarkers, diagnostic test, reference standard

DOI: 10.3233/JAD-142886

Journal: Journal of Alzheimer's Disease, vol. 46, no. 4, pp. 889-899, 2015