The effect of uncertainty in patient classification on diagnostic performance estimations.

ABSTRACT: BACKGROUND:The performance of a new diagnostic test is typically evaluated against a comparator which is assumed to correspond closely to some true state of interest. Judgments about the new test's performance are based on the differences between the outputs of the test and comparator. It is commonly assumed that a small amount of uncertainty in the comparator's classifications will negligibly affect the measured performance of a diagnostic test. METHODS:Simulated datasets were generated to represent typical diagnostic scenarios. Comparator noise was introduced in the form of random misclassifications, and the effect on the apparent performance of the diagnostic test was determined. An actual dataset from a clinical trial on a new diagnostic test for sepsis was also analyzed. RESULTS:We de

SUBMITTER: McHugh LC 

PROVIDER: S-EPMC6530857 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature