Receiver operating characteristic curve: overview and practical use for clinicians

By F. Nahm. Korean Journal of Anesthesiology, 2022

1,318 citations recorded by the source corpus.

Using diagnostic testing to determine the presence or absence of a disease is essential in clinical practice. In many cases, test results are obtained as continuous values and require a process of conversion and interpretation and into a dichotomous form to determine the presence of a disease. The primary method used for this process is the receiver operating characteristic (ROC) curve. The ROC curve is used to assess the overall diagnostic performance of a test and to compare the performance of two or more diagnostic tests. It is also used to select an optimal cut-off value for determining the presence or absence of a disease. Although clinicians who do not have expertise in statistics do not need to understand both the complex mathematical equation and the analytic process of ROC curves, understanding the core concepts of the ROC curve analysis is a prerequisite for the proper use and interpretation of the ROC curve. This review describes the basic concepts for the correct use and interpretation of the ROC curve, including parametric/nonparametric ROC curves, the meaning of the area under the ROC curve (AUC), the partial AUC, methods for selecting the best cut-off value, and the statistical software to use for ROC curve analyses.

Subfields: Epidemiology, Health Information Management, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/a515e73e0c4b7b2cf1692d72f7ad5acbc3552c7a

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Citations in the corpus

Receiver operating characteristic curve analysis in diagnostic accuracy studies: A guide to interpreting the area under the curve value (2023, background): “[5] ] While the ROC curve and the resultant area under the curve (AUC) offer a concise summary of the index test’s diagnostic utility, clinicians may encounter challenges in interpreting these values.”
ROC Analysis of Biomarker Combinations in Fragile X Syndrome-Specific Clinical Trials: Evaluating Treatment Efficacy via Exploratory Biomarkers (2025, unknown): “In circumstances where there is a large range of variability in baseline values, with some individuals showing minimal impairment that overlaps with improved scores with treatment for those with lower baseline values, the classi ﬁ er technique may underperform.”