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

ABSTRACT:

Background

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.

Methods

We propose using extreme value theory to select a cutoff with pre

SUBMITTER: Pugh S 

PROVIDER: S-EPMC10851584 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature