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Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
Published on: August 9, 2024
ROC curves for the initial assessment of new diagnostic tests
Y T Van der Schouw1, A L Verbeek, J H Ruijs
1Department of Medical Informatics and Epidemiology, University of Nijmegen, The Netherlands.
Abstract:
New diagnostic tests are mainly evaluated by determining the sensitivity and specificity of the test. These test characteristics were originally meant to be used in making diagnoses. For evaluative purposes their usefulness is weakened by their susceptibility to selection and their dependence on the cut-off points that are used for test positivity. The plotting of a receiver operating characteristic (ROC) curve might be a solution to these problems. Furthermore, the ROC curve yields a measure for the diagnostic power of the test expressed in one number instead of two, namely the area under the curve (AUC). Finally, the ROC curve and its AUC permit easy comparison of different tests and the performance of different interpreters of one test. The construction and use of ROC curves are described and illustrated with data of a case-referent investigation into the relationship between iron status parameters and the presence of acute myocardial infarction. The AUCs of ferritin and serum iron, 0.61 and 0.68 respectively, are too low to suggest meaningful usefulness in clinical practice.
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