CSF biomarkers cutoffs: The importance of coincident neuropathological diseases

Department of Pathology and Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, CNDR, University of Pennsylvania School of Medicine, 3rd Floor Maloney Building, 3600 Spruce Street, Philadelphia, PA 19104, USA.
Acta Neuropathologica (Impact Factor: 10.76). 04/2012; 124(1):23-35. DOI: 10.1007/s00401-012-0983-7
Source: PubMed


The effects of applying clinical versus neuropathological diagnosis and the inclusion of cases with coincident neuropathological diagnoses have not been assessed specifically when studying cerebrospinal fluid (CSF) biomarker classification cutoffs for patients with neurodegenerative diseases that cause dementia. Thus, 142 neuropathologically diagnosed neurodegenerative dementia patients [71 Alzheimer's disease (AD), 29 frontotemporal lobar degeneration (FTLD), 3 amyotrophic lateral sclerosis, 7 dementia with Lewy bodies, 32 of which cases also had coincident diagnoses] were studied. 96 % had enzyme-linked immunosorbant assay (ELISA) CSF data and 77 % had Luminex CSF data, with 43 and 46 controls for comparison, respectively. Aβ(42), total, and phosphorylated tau(181) were measured. Clinical and neuropathological diagnoses showed an 81.4 % overall agreement. Both assays showed high sensitivity and specificity to classify AD subjects against FTLD subjects and controls, and moderate sensitivity and specificity for classifying FTLD subjects against controls. However, among the cases with neuropathological diagnoses of AD plus another pathology (26.8 % of the sample), 69.4 % (ELISA) and 96.4 % (Luminex) were classified as AD according to their biomarker profiles. Use of clinical diagnosis instead of neuropathological diagnosis led to a 14-17 % underestimation of the biomarker accuracy. These results show that while CSF Aβ and tau assays are useful for diagnosis of AD and neurodegenerative diseases even at MCI stages, CSF diagnostic analyte panels that establish a positive diagnosis of Lewy body disease and FTLD are also needed, and must be established based on neuropathological rather than clinical diagnoses.

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    • "When the biomarker and the reference test are dependent, the diagnostic accuracy of the biomarker can be either underestimated or overestimated, depending on the strength of the association [8] [9]. Recently, Toledo et al. [10] demonstrated that using the clinical diagnosis as a perfect reference leads to an underestimation of cerebrospinal fluid (CSF) AD biomarker sensitivity and specificity values and shifts the cut-offs compared to using the autopsy confirmed diagnosis as reference test. "
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    ABSTRACT: 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. To determine the diagnostic accuracy of AD biomarkers while taking the imperfectness of the reference test into account. 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-β1-42, Total tau, and P-tau181) by including the clinical diagnosis as imperfect reference test into the analysis. 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. 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.
    Journal of Alzheimer's disease: JAD 04/2015; 46(4). DOI:10.3233/JAD-142886 · 4.15 Impact Factor
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    • "Aβ deposition can be measured using PET tracers (Clark et al., 2012a; Ikonomovic et al., 2008) which correlate with decrease in Aβ 1–42 in CSF (Fagan et al., 2009; Toledo et al., 2011). Both measures show a high accuracy for predicting AD neuropathology (Clark et al., 2012a; Shaw et al., 2009; Silverman et al., 2001; Toledo et al., 2012). CSF concentrations have shown promise in predicting conversion from MCI to AD (Hampel et al., 2010a, 2010b; Schuff et al., 2009; Shaw et al., 2009). "
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    Clinical neuroimaging 12/2014; 4:164–173. DOI:10.1016/j.nicl.2013.11.010 · 2.53 Impact Factor
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    • "years old) from the University of Pennsylvania Alzheimer's Disease Center Core (ADCC) were analyzed by the assay. Cases and control subjects were clinically evaluated as described [17] [18] [19]. All of the CSF samples were collected using standardized methodology [17] "
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    Journal of Alzheimer's disease: JAD 03/2014; 41(2). DOI:10.3233/JAD-132489 · 4.15 Impact Factor
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