Abstract
Screening and diagnostic tests are used to classify people with and without a disease. Diagnostic accuracy measures are used to evaluate the correctness of a classification in clinical research and practice. Although this depends on the uncertainty of measurement, there has been limited research on their relation. The objective of this work was to develop an exploratory tool for the relation between diagnostic accuracy measures and measurement uncertainty, as diagnostic accuracy is fundamental to clinical decision-making, while measurement uncertainty is critical to quality and risk management in laboratory medicine. For this reason, a freely available interactive program was developed for calculating, optimizing, plotting and comparing various diagnostic accuracy measures and the corresponding risk of diagnostic or screening tests measuring a normally distributed measurand, applied at a single point in time in non-diseased and diseased populations. This is done for differing prevalence of the disease, mean and standard deviation of the measurand, diagnostic threshold, standard measurement uncertainty of the tests and expected loss. The application of the program is illustrated with a case study of glucose measurements in diabetic and non-diabetic populations. The program is user-friendly and can be used as an educational and research tool in medical decision-making.
Highlights
An increasing number of in vitro screening and diagnostic tests are extensively used as binary classifiers in medicine, to classify people into the non-overlapping classes of populations with and without a disease, which are categorized as quantitative and qualitative
Diagnostic accuracy measures are used to evaluate the correctness of a classification in clinical research and practice
The objective of this work was to develop an exploratory tool for the relation between diagnostic accuracy measures and measurement uncertainty, as diagnostic accuracy is fundamental to clinical decision-making, while measurement uncertainty is critical to quality and risk management in laboratory medicine
Summary
An increasing number of in vitro screening and diagnostic tests are extensively used as binary classifiers in medicine, to classify people into the non-overlapping classes of populations with and without a disease, which are categorized as quantitative and qualitative. The quantitative and many qualitative screening or diagnostic tests are based on measurements. There is a probability distribution of the measurements in each of the diseased and non-diseased populations. To classify the patients with and without a disease, using a test based on a measurement, a diagnostic threshold or cutoff point is defined. If the measurement is above the threshold, the patient is classified as test-positive; otherwise, the patient is classified as test-negative (Figure 1) or inversely.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
