Mathematics of Diagnostic testing

1. Type prevalence value here Pressing “6-Views” button from the previous window opens this window which 6 plots with 6 default prevalence values of 0.1, 0.25, 0.55, 0.75, 0.95 and 0.99 are taken and plotted against the Sensitivity and Specificity. Type a name for the plot (Tag) in this text box Mathematics of Diagnostic testing Predictive Values, Test Cutoffs and prevalence subsystem Post-Test Predictive Values are complex! Multiple input variables (x and y) selections are available Main VITA Screen Benefits of VITA Future Work Acknowledgements Multiple z-axis output (Utility) functions are available Four-Dimensional Plots can be generated The input value of the 3rd variable can be changed in real time VITA: Visual Interactive Test Analysis Contact Select color by tab Select Curve and labels to be added to the plot Click this button to see the plot Legend for the plot VITA-An Interactive 3-D Visualization System to Enhance Student Understanding of Mathematical Concepts in Medical Decision-making M. Sriram Iyengar, PhDa, John R Svirbelyb, MD, Mirabela Rusu, MSa, Jack W Smith, MD, PhDa aSchool of Health Information Sciences, Univ of Texas, Houston, b TriHealth, Cincinnati • Op Standard File menu • Change the function • To be plotted with • Drop-down menu : • Positive Predictive Value • Negative Predictive Value • Youden Index Standard Plot View tools Options to change The function of the plot and other parameters • Change the values • To be plotted on • X axis: • Sensitivity • Specificity • 1-Specificitiy • Prevalence • On Y axis: • Specificity • 1-Specificitiy • Prevalence Change the 3rd variable’s Value using slider bar here. Note the change in the shape of the plot to the previous one wit h prevalence value of 0.01(default) Options to change The Plot View Relationships between Post-Test Predictive values and Test cutoffs at any disease prevalence can be visualized after input of empirical data in a spreadsheet or comma-separated text file whose rows are test cutoff, sensitivity and specificity open a new “6-views” Plot • VITA is software for interactive 3-D visualization of the intricate non-linear relationships between mathematical quantities important in diagnostic testing. VITA 4.0 focuses on predictive values, sensitivity, specificity, Youden Index, diagnostic test cut off values, and prevalence. • Some basic features of VITA are: • 3-D and 4-D views • Rotation, zooming, color schemes, and similar functions for graph manipulation and display • Display the direct relationships between PPV, NPV and cutoff values for various prevalences. • A diagnostic test may be a biochemical assay (BNP, PSA, other) or other analysis. • If the assay result is greater (or lesser) than a cutoff value then the presence (or absence) of disease is concluded. • To analyze test performance we use various conditional probabilities: Sensitivity = P(Test positive | Disease present ) Specificity = P(Test negative | Disease not present ) False Positive rate = 1 - specificity The ROC curve is the plot of Sensitivity vs. False Positive rate The Area under ROC is a measure of the goodness of the test. • However, the Post-test Predictive Values are often viewed as more useful for diagnostic purposes by clinicians. • Positive Predictive Value (PPV) = P(Disease exists| Test positive) • Negative Predictive Value (NPV) = P(Disease not present | Test negative) open a new “Prediction Values, Cutoff & Prevalence ” Plot Browse button to find the file and Open • Medical Education. Assist instructors explain • Important, complex mathematical concepts in decision-making • Appreciation of on-linearity in predictive values • Variation of test performance / inferences across populations • Research • Determine optimal cutoff-vales for diagnostic tests • Compare tests performance on the basis of predictive values that are more meaningful to diagnosticians The Positive Predictive Value and Negative Predictive Value incorporate disease prevalence (p) and are computed by the following formulas. Here Sensitivity is denoted se, Specificity by sp and prevalence by p. • Enable input of raw test values into Predictive Values-Test cutoff system • Rewrite in a general purpose programming language • Add other input/output variables including Utility measures, likelihood ratios. These are complex, non-linear formulas depending on 3 variables, varying in a four-dimensional hyper-surface. It is very difficult for medical/nursing students, or even experienced clinicians to understand these complex interactions. Yet, it is important to understand these to avoid making serious errors. VITA is a solution M. Sriram Iyengar, m.sriram.iyengar@uth.tmc.edu • Asst Professor, School of Health Information Sciences, University of Texas Health Science Center at Houston • Informatics Research Scientist, Medical Informatics and Health Care Systems, NASA Johnson Space Center, Houston, TX Visit www.medal.org to request an evaluation copy of VITA Grateful thanks to Kathy Johnson-Throop, PhD, NASA Johnson Space Center Adinarayan Kadapa, MD, graduate student, School of Health Information Sciences, Univ. of Texas, Houston.