Estimating cutoff values for diagnostic tests to achieve target specificity using extreme value theory.

Publication date: Feb 08, 2024

Rapidly developing tests for emerging diseases is critical for early disease monitoring. In the early stages of an epidemic, when low prevalences are expected, high specificity tests are desired to avoid numerous false positives. Selecting a cutoff to classify positive and negative test results that has the desired operating characteristics, such as specificity, is challenging for new tests because of limited validation data with known disease status. While there is ample statistical literature on estimating quantiles of a distribution, there is limited evidence on estimating extreme quantiles from limited validation data and the resulting test characteristics in the disease testing context. We propose using extreme value theory to select a cutoff with predetermined specificity by fitting a Pareto distribution to the upper tail of the negative controls. We compared this method to five previously proposed cutoff selection methods in a data analysis and simulation study. We analyzed COVID-19 enzyme linked immunosorbent assay antibody test results from long-term care facilities and skilled nursing staff in Colorado between May and December of 2020. We found the extreme value approach had minimal bias when targeting a specificity of 0. 995. Using the empirical quantile of the negative controls performed well when targeting a specificity of 0. 95. The higher target specificity is preferred for overall test accuracy when prevalence is low, whereas the lower target specificity is preferred when prevalence is higher and resulted in less variable prevalence estimation. While commonly used, the normal based methods showed considerable bias compared to the empirical and extreme value theory-based methods. When determining disease testing cutoffs from small training data samples, we recommend using the extreme value based-methods when targeting a high specificity and the empirical quantile when targeting a lower specificity.

Open Access PDF

Concepts Keywords
Antibody Antibody test
Colorado Cut point
Cutoffs Extreme value theory
December Serology
Predetermined Threshold

Semantics

Type Source Name
disease MESH COVID-19
disease IDO assay
drug DRUGBANK Etoperidone
pathway REACTOME Reproduction
drug DRUGBANK Coenzyme M
disease VO USA
drug DRUGBANK Esomeprazole
drug DRUGBANK Medical air
disease IDO blood
drug DRUGBANK Gold
drug DRUGBANK Ranitidine
drug DRUGBANK Ilex paraguariensis leaf
drug DRUGBANK Ademetionine
disease VO population
disease VO data set
disease MESH emerging infectious diseases
disease MESH measles
pathway KEGG Measles
disease VO vaccination
disease VO vaccine
disease MESH vaccinia
disease IDO host
drug DRUGBANK Water
disease VO time
disease MESH infection
disease IDO algorithm

Original Article

(Visited 1 times, 1 visits today)