Dataset Information

Development of a diagnostic test based on multiple continuous biomarkers with an imperfect reference test.

ABSTRACT: Ignoring the fact that the reference test used to establish the discriminative properties of a combination of diagnostic biomarkers is imperfect can lead to a biased estimate of the diagnostic accuracy of the combination. In this paper, we propose a Bayesian latent-class mixture model to select a combination of biomarkers that maximizes the area under the ROC curve (AUC), while taking into account the imperfect nature of the reference test. In particular, a method for specification of the prior for the mixture component parameters is developed that allows controlling the amount of prior information provided for the AUC. The properties of the model are evaluated by using a simulation study and an application to real data from Alzheimer's disease research. In the simulation study, 100 data sets are simulated for sample sizes ranging from 100 to 600 observations, with a varying correlation between biomarkers. The inclusion of an informative as well as a flat prior for the diagnostic accuracy of the reference test is investigated. In the real-data application, the proposed model was compared with the generally used logistic-regression model that ignores the imperfectness of the reference test. Conditional on the selected sample size and prior distributions, the simulation study results indicate satisfactory performance of the model-based estimates. In particular, the obtained average estimates for all parameters are close to the true values. For the real-data application, AUC estimates for the proposed model are substantially higher than those from the 'traditional' logistic-regression model.

SUBMITTER: Garcia Barrado L

PROVIDER: S-EPMC6312185 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Development of a diagnostic test based on multiple continuous biomarkers with an imperfect reference test.

García Barrado Leandro L Coart Els E Burzykowski Tomasz T

Statistics in medicine 20150921 4

Ignoring the fact that the reference test used to establish the discriminative properties of a combination of diagnostic biomarkers is imperfect can lead to a biased estimate of the diagnostic accuracy of the combination. In this paper, we propose a Bayesian latent-class mixture model to select a combination of biomarkers that maximizes the area under the ROC curve (AUC), while taking into account the imperfect nature of the reference test. In particular, a method for specification of the prior ...[more]

PMID: 26388206

Similar Datasets

Project description:BackgroundWe observed that some patients with clinical leptospirosis supported by positive results of rapid tests were negative for leptospirosis on the basis of our diagnostic gold standard, which involves isolation of Leptospira species from blood culture and/or a positive result of a microscopic agglutination test (MAT). We hypothesized that our reference standard was imperfect and used statistical modeling to investigate this hypothesis.MethodsData for 1652 patients with suspected leptospirosis recruited during three observational studies and one randomized control trial that described the application of culture, MAT, immunofluorescence assay (IFA), lateral flow (LF) and/or PCR targeting the 16S rRNA gene were reevaluated using Bayesian latent class models and random-effects meta-analysis.ResultsThe estimated sensitivities of culture alone, MAT alone, and culture plus MAT (for which the result was considered positive if one or both tests had a positive result) were 10.5% (95% credible interval [CrI], 2.7%-27.5%), 49.8% (95% CrI, 37.6%-60.8%), and 55.5% (95% CrI, 42.9%-67.7%), respectively. These low sensitivities were present across all 4 studies. The estimated specificity of MAT alone (and of culture plus MAT) was 98.8% (95% CrI, 92.8%-100.0%). The estimated sensitivities and specificities of PCR (52.7% [95% CrI, 45.2%-60.6%] and 97.2% [95% CrI, 92.0%-99.8%], respectively), lateral flow test (85.6% [95% CrI, 77.5%-93.2%] and 96.2% [95% CrI, 87.7%-99.8%], respectively), and immunofluorescence assay (45.5% [95% CrI, 33.3%-60.9%] and 96.8% [95% CrI, 92.8%-99.8%], respectively) were considerably different from estimates in which culture plus MAT was considered a perfect gold standard test.ConclusionsOur findings show that culture plus MAT is an imperfect gold standard against which to compare alterative tests for the diagnosis of leptospirosis. Rapid point-of-care tests for this infection would bring an important improvement in patient care, but their future evaluation will require careful consideration of the reference test(s) used and the inclusion of appropriate statistical models.

Dataset Information

Development of a diagnostic test based on multiple continuous biomarkers with an imperfect reference test.

Publications

Development of a diagnostic test based on multiple continuous biomarkers with an imperfect reference test.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets