Effects of disease severity distribution on the performance of quantitative diagnostic methods and proposal of a novel 'V-plot' methodology to display accuracy values. Issue 1 (20th January 2018)

• Record Type: Journal Article
• Authors: Petraco, Ricardo; Dehbi, Hakim-Moulay; Howard, James P; Shun-Shin, Matthew J; Sen, Sayan; Nijjer, Sukhjinder S; Mayet, Jamil; Davies, Justin E; Francis, Darrel P
• Is Part Of: Open heart. Volume 5:Issue 1(2018)
• Publication Date: 2018-01-20
• Subjects: diagnostic accuracy -- diagnostic tests -- study sample; Cardiology -- Periodicals; Heart -- Diseases -- Periodicals; Heart -- Diseases -- Patients -- Periodicals; 616.12005
• DOI: 10.1136/openhrt-2017-000663
• Languages: English
• ISSNs: 2398-595X

Abstract

Abstract : Background: Diagnostic accuracy is widely accepted by researchers and clinicians as an optimal expression of a test's performance. The aim of this study was to evaluate the effects of disease severity distribution on values of diagnostic accuracy as well as propose a sample-independent methodology to calculate and display accuracy of diagnostic tests. Methods and findings: We evaluated the diagnostic relationship between two hypothetical methods to measure serum cholesterol (Cholrapid and Cholgold ) by generating samples with statistical software and (1) keeping the numerical relationship between methods unchanged and (2) changing the distribution of cholesterol values. Metrics of categorical agreement were calculated (accuracy, sensitivity and specificity). Finally, a novel methodology to display and calculate accuracy values was presented (the V-plot of accuracies). Conclusion: No single value of diagnostic accuracy can be used to describe the relationship between tests, as accuracy is a metric heavily affected by the underlying sample distribution. Our novel proposed methodology, the V-plot of accuracies, can be used as a sample-independent measure of a test performance against a reference gold standard.