A sequential classification rule based on multiple quantitative tests in the absence of a gold standard

Jingyang Zhang; Ying Zhang; Kathryn Chaloner; Jack T Stapleton

doi:10.1002/sim.6780

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A sequential classification rule based on multiple quantitative tests in the absence of a gold standard

Journal article

Open access

Peer reviewed

A sequential classification rule based on multiple quantitative tests in the absence of a gold standard

Jingyang Zhang, Ying Zhang, Kathryn Chaloner and Jack T Stapleton

Statistics in medicine, Vol.35(8), pp.1359-1372

04/15/2016

DOI: 10.1002/sim.6780

PMID: 26522690

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Abstract

In many medical applications, combining information from multiple biomarkers could yield a better diagnosis than any single one on its own. When there is a lack of a gold standard, an algorithm of classifying subjects into the case and non-case status is necessary for combining multiple markers. The aim of this paper is to develop a method to construct a composite test from multiple applicable tests and derive an optimal classification rule under the absence of a gold standard. Rather than combining the tests, we treat the tests as a sequence. This sequential composite test is based on a mixture of two multivariate normal latent models for the distribution of the test results in case and non-case groups, and the optimal classification rule is derived returning the greatest sensitivity at a given specificity. This method is applied to a real-data example and simulation studies have been carried out to assess the statistical properties and predictive accuracy of the proposed composite test. This method is also attainable to implement nonparametrically.

Biostatistics

Multivariate Analysis

Predictive Value of Tests

Flaviviridae Infections - complications

HIV Infections - virology

Humans

Biomarkers - analysis

Enzyme-Linked Immunosorbent Assay - statistics & numerical data

GB virus C

Diagnostic Tests, Routine - standards

Models, Statistical

Diagnostic Tests, Routine - classification

Likelihood Functions

Algorithms

Computer Simulation

HIV Infections - complications

Diagnostic Tests, Routine - statistics & numerical data

Details

Title: Subtitle: A sequential classification rule based on multiple quantitative tests in the absence of a gold standard
Creators: Jingyang Zhang - Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, U.S.A
Ying Zhang - Department of Mathematics, Shanghai Jiao Tong University, Shanghai 200240, China
Kathryn Chaloner - Department of Statistics and Actuarial Sciences, University of Iowa, Iowa City, IA 52242, U.S.A
Jack T Stapleton - Department of Internal Medicine, University of Iowa, Iowa City, IA 52242, U.S.A
Resource Type: Journal article
Publication Details: Statistics in medicine, Vol.35(8), pp.1359-1372
DOI: 10.1002/sim.6780
PMID: 26522690
ISSN: 0277-6715
eISSN: 1097-0258
Grant note: I01 BX000207 / BLRD VA
Language: English
Date published: 04/15/2016
Academic Unit: Microbiology and Immunology; Infectious Diseases; Internal Medicine
Record Identifier: 9984094543902771

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