A Software Tool for Exploring the Relation between Diagnostic Accuracy and Measurement Uncertainty

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.

A Software Tool for Calculating the Uncertainty of Diagnostic Accuracy Measures

“…The program presented in this work complements our previously published software [11], which explores the effects of measurement uncertainty on diagnostic accuracy measures applied to populations. This program calculates the standard and expanded combined, measurement and sampling uncertainty and the resultant confidence intervals of diagnostic accuracy measures of diagnostic tests, applied to samples of populations, providing 99 different types of plots and three different types of comprehensive tables (Figure 2), many of which are novel.…”

“…The current pandemic of novel corona virus disease 2019 has exposed this unequivocally [3][4][5][6][7]. There has been extensive research on either diagnostic accuracy or uncertainty, however, extremely limited research has been done on both subjects [8][9][10][11].…”

Feasibility study of ResNet‐50 in the distinction of intraoral neural tumors using histopathological images

“…For the test stage evaluation, a comprehensive set of metrics were extracted to provide a nuanced understanding of the model's performance, as like: loss, accuracy, precision, true positive (TP), false positive (FP), true negative (TN), false negative (FN), sensitivity (recall), specificity, F1 score, the area under the receiver operating characteristic (AUROC). 21,22 Moreover, Cohen's kappa coefficient (κ) 23 F I G U R E 1 Methodology. Panel (A) shows the sample retrieving (totaling 30 cases), followed by the WSIs annotation, segmentation, and fragmentation steps.…”

Oral Glucose Tolerance Test 90-Min Values in Prediabetes Detection: Using of Multiple Regression Analyses for Diagnostic Criteria Determination

“…The following indicators were used for determinate the qualitative characteristics of the diagnostic tests: Sensitivity, Specificity, Positive Predictive Value, Negative Predictive Value, Overall Diagnostic Accuracy and Youden Index [16,17].…”