Work

Using group testing in a two-phase epidemiologic design to identify the effects of a large number of antibody reactions on disease risk

Year: 2022

Type: article

Abstract: BACKGROUND: The role of immunological responses to exposed bacteria on disease incidence is increasingly under investigation. With many bacterial species, and many potential antibody reactions to a particular species, the large number of assays required for this type of discovery can make it prohibitively expensive. We propose a two-phase group testing design to more efficiently screen numerous antibody effects in a case-control setting. METHODS: Phase 1 uses group testing to select antibodies that are differentially expressed between cases and controls. The selected antibodies go on to Phase 2 individual testing. RESULTS: We evaluate the two-phase group testing design through simulations and example data and find that it substantially reduces the number of assays required relative to standard case-control and group testing designs, while maintaining similar statistical properties. CONCLUSION: The proposed two-phase group testing design can dramatically reduce the number of assays required, while providing comparable results to a case-control design.

Source: BMC Medical Research Methodology

DOI: 10.1186/s12874-022-01798-0

Authors: Tanvi Mehta, Yaakov Malinovsky, Christian C. Abnet, Paul S. Albert

Institutions: National Cancer Institute, Division of Cancer Epidemiology and Genetics, University of Maryland, Baltimore County, National Institutes of Health

Language: English

Topic: Statistical Methods in Epidemiology

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,790