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http://hdl.handle.net/1942/24329
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DC Field | Value | Language |
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dc.contributor.author | GARCIA BARRADO, Leandro | - |
dc.contributor.author | Coart, Els | - |
dc.contributor.author | BURZYKOWSKI, Tomasz | - |
dc.date.accessioned | 2017-08-31T08:38:20Z | - |
dc.date.available | 2017-08-31T08:38:20Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | BIOMETRICS, 73(2), p. 646-655 | - |
dc.identifier.issn | 0006-341X | - |
dc.identifier.uri | http://hdl.handle.net/1942/24329 | - |
dc.description.abstract | Estimating biomarker-index accuracy when only imperfect reference-test information is available is usually performed under the assumption of conditional independence between the biomarker and imperfect reference-test values. We propose to define a latent normally-distributed tolerance-variable underlying the observed dichotomous imperfect reference-test results. Subsequently, we construct a Bayesian latent-class model based on the joint multivariate normal distribution of the latent tolerance and biomarker values, conditional on latent true disease status, which allows accounting for conditional dependence. The accuracy of the continuous biomarker-index is quantified by the AUC of the optimal linear biomarker-combination. Model performance is evaluated by using a simulation study and two sets of data of Alzheimer's disease patients (one from the memory-clinic-based Amsterdam Dementia Cohort and one from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database). Simulation results indicate adequate model performance and bias in estimates of the diagnostic-accuracy measures when the assumption of conditional independence is used when, in fact, it is incorrect. In the considered case studies, conditional dependence between some of the biomarkers and the imperfect reference-test is detected. However, making the conditional independence assumption does not lead to any marked differences in the estimates of diagnostic accuracy. | - |
dc.description.sponsorship | This Research has been conducted with the financial support of the Walloon Government under the European ERA-NET EUROTRANS-BIO framework (Project B4AD, Agreement no. 1017106) It was conducted in collaboration with International Drug Development Institute (Louvain-la-Neuve, Belgium), PamGene International (Den Bosch, The Netherlands) and the VU University Medical Center and the Alzheimer Center (Amsterdam, The Netherlands). Research of the VUmc Alzheimer Center and the Department of Pathology is part of the Neurodegeneration research program of the Neuroscience Campus Amsterdam. The VUmc Alzheimer Center is supported by Alzheimer Nederland and Stichting VUmc fonds. The VUmc clinical database structure was developed with funding from Stichting Dioraphte. The computational resources and services used in the current work were provided by the Hercules Foundation and the Flemish Government-department EWI. Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (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: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf. Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Alzheimer's Association; Alzheimer's Drug Discovery Foundation; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is Rev December 5, 2013 coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. | - |
dc.language.iso | en | - |
dc.publisher | WILEY | - |
dc.rights | © 2016, The International Biometric Society | - |
dc.subject.other | Alzheimer's disease; Bayesian Estimation; Biomarker; Conditional dependence; Imperfect reference-test | - |
dc.subject.other | Alzheimer's disease; Bayesian Estimation; biomarker; conditional dependence; iImperfect reference-test | - |
dc.title | Estimation of diagnostic accuracy of a combination of continuous biomarkers allowing for conditional dependence between the biomarkers and the imperfect reference-test | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 655 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 646 | - |
dc.identifier.volume | 73 | - |
local.format.pages | 10 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | [Barrado, Leandro Garcia; Burzykowski, Tomasz] Hasselt Univ, I BioStat, B-3590 Diepenbeek, Belgium. [Coart, Els; Burzykowski, Tomasz] IDDI, Ave Prov 30, B-1340 Louvain La Neuve, Belgium. | - |
local.publisher.place | HOBOKEN | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.identifier.doi | 10.1111/biom.12583 | - |
dc.identifier.isi | 000403478400027 | - |
item.validation | ecoom 2018 | - |
item.accessRights | Open Access | - |
item.fullcitation | GARCIA BARRADO, Leandro; Coart, Els & BURZYKOWSKI, Tomasz (2017) Estimation of diagnostic accuracy of a combination of continuous biomarkers allowing for conditional dependence between the biomarkers and the imperfect reference-test. In: BIOMETRICS, 73(2), p. 646-655. | - |
item.fulltext | With Fulltext | - |
item.contributor | GARCIA BARRADO, Leandro | - |
item.contributor | Coart, Els | - |
item.contributor | BURZYKOWSKI, Tomasz | - |
crisitem.journal.issn | 0006-341X | - |
crisitem.journal.eissn | 1541-0420 | - |
Appears in Collections: | Research publications |
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Barrado_et_al-2016-Biometrics.pdf Restricted Access | Published version | 227.95 kB | Adobe PDF | View/Open Request a copy |
mmmm.pdf | Peer-reviewed author version | 240.07 kB | Adobe PDF | View/Open |
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