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[Practical application of receiver operating characteristic curve on laboratory diagnosis].

Shuji Matsuo, Hirotaka Takahashi

Open publisher page 3 citations

Abstract

The receiver operating characteristic (ROC) curve represents characteristics specific to an examination (diagnostic sensitivity and specificity) and is useful for evaluation and comparison of the diagnostic accuracy. However, the ROC curve is not widely used at present. In this symposium, we showed how to draw this curve and its practical utilization, using as examples the diagnosis of the diabetic and impaired glucose tolerance group and the diagnosis of deep-seated fungal infection and acute myocardial infarction. In the ROC curve, true positive is plotted on the vertical axis and false positive on the horizontal axis. This curve is readily drown and visually shows the diagnostic accuracy that can not be clarified by histograms. The advantages of this curve are as follows. 1. Diagnostic accuracy can be compared. 2. The significance of the reference interval in diagnosis can be evaluated. 3. The diagnostic cut-off value can be determined using this curve. 4. Combined with prevalence, the diagnostic probability can be represented quantitatively. The points that require attention are differences in the ROC curve according to selection of subjects (including controls), the time factor (disease stage) and severity (disease condition). By paying attention to these points, the ROC curve can be used as a simple and useful method in laboratory diagnosis. We hope that this curve will be widely used.

About this research paper

What this paper is about

The receiver operating characteristic (ROC) curve represents characteristics specific to an examination (diagnostic sensitivity and specificity) and is useful for evaluation and comparison of the diagnostic accuracy. However, the ROC curve is not widely used at present. In this symposium, we showed how to draw this curve and its practical utilization, using as examples the diagnosis of the diabetic and impaired glucose tolerance group and the diagnosis of deep-seated fungal infection and acute myocardial infarction. In the ROC curve, true positive is plotted on the vertical axis and false positive on the horizontal axis. This curve is readily drown and visually shows the diagnostic accuracy that can not be clarified by histograms. The advantages of this curve are as follows. 1. Diagnostic accuracy can be compared. 2. The significance of the reference interval in diagnosis can be evaluated. 3. The diagnostic cut-off value can be determined using this curve. 4. Combined with prevalence, the diagnostic probability can be represented quantitatively. The points that require attention are differences in the ROC curve according to selection of subjects (including controls), the time factor (disease stage) and severity (disease condition). By paying attention to these points, the ROC curve can be used as a simple and useful method in laboratory diagnosis. We hope that this curve will be widely used.

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Available abstract

The receiver operating characteristic (ROC) curve represents characteristics specific to an examination (diagnostic sensitivity and specificity) and is useful for evaluation and comparison of the diagnostic accuracy. However, the ROC curve is not widely used at present. In this symposium, we showed how to draw this curve and its practical utilization, using as examples the diagnosis of the diabetic and impaired glucose tolerance group and the diagnosis of deep-seated fungal infection and acute myocardial infarction. In the ROC curve, true positive is plotted on the vertical axis and false positive on the horizontal axis. This curve is readily drown and visually shows the diagnostic accuracy that can not be clarified by histograms. The advantages of this curve are as follows. 1. Diagnostic accuracy can be compared. 2. The significance of the reference interval in diagnosis can be evaluated. 3. The diagnostic cut-off value can be determined using this curve. 4. Combined with prevalence, the diagnostic probability can be represented quantitatively. The points that require attention are differences in the ROC curve according to selection of subjects (including controls), the time factor (disease stage) and severity (disease condition). By paying attention to these points, the ROC curve can be used as a simple and useful method in laboratory diagnosis. We hope that this curve will be widely used.

Key concepts: Receiver operating characteristic, Area under the curve, Diagnostic accuracy, Area under curve, Sensitivity (control systems), Medicine, Statistics, Curve fitting

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