What does an area under the curve (AUC) of 0.9381 indicate?

From the Guidelines

The area under the curve (AUC) of 0.9381 indicates excellent diagnostic or predictive performance of a test or model, with strong discriminatory power and approximately 94% accuracy in distinguishing between positive and negative outcomes. This value, which ranges from 0 to 1, represents the probability that a randomly selected positive case will have a higher test value than a randomly selected negative case 1. An AUC of 0.9381 is considered very high, showing that the test or model has strong discriminatory power with minimal overlap between the distributions of test results for positive and negative cases, resulting in few false positives or false negatives when using this test or model.

Key Points

• The AUC value of 0.9381 is very high, indicating excellent diagnostic performance
• This value represents a high probability of correctly distinguishing between positive and negative cases
• The test or model has strong discriminatory power, with approximately 94% accuracy
• Minimal overlap between the distributions of test results for positive and negative cases results in few false positives or false negatives

In practical terms, this means the test or model is highly reliable for clinical decision-making or risk assessment, as seen in studies such as 1, which reported high diagnostic AUC values for various tests. For context, an AUC of 0.5 represents a test no better than random chance, while values above 0.9 are considered outstanding, as discussed in 1.

Comparison to Other Studies

• The AUC value of 0.9381 is comparable to other high-performing tests, such as those reported in 1 and 1
• The strong discriminatory power and high accuracy of the test or model make it a valuable tool for clinical decision-making and risk assessment
• The results of this study are consistent with other research in the field, which highlights the importance of using high-performing tests and models in clinical practice.

From the Research

Area Under the Curve (AUC) Interpretation

• The area under the curve (AUC) is a summary measure of the receiver operating characteristic (ROC) curve, indicating the overall performance of a diagnostic test in terms of its accuracy at various diagnostic thresholds used to discriminate cases and non-cases of disease 2.
• An AUC value of 0.9381 indicates that the test has a high accuracy in distinguishing between diseased and non-diseased individuals, with a value of 1.0 indicating perfect discrimination and a value of 0.5 indicating that the test is no better than chance 3.
• AUC values above 0.80 are generally considered clinically useful, while values below 0.80 are considered of limited clinical utility 3.
• The interpretation of AUC values should consider the 95% confidence interval, which reflects the uncertainty around the AUC value, with a narrow confidence interval indicating that the AUC value is likely accurate, and a wide confidence interval indicating that the AUC value is less reliable 3, 4.

Comparison of AUC Values

• Comparing AUC values between different tests can be challenging, especially if an empirical truncation process is used, and the partial AUC measure lacks a useful symmetry property enjoyed by the full AUC 2.
• The use of the full AUC is generally preferred over the partial AUC, as it provides a more comprehensive measure of the test's performance 2.
• Different methods for constructing confidence intervals for the AUC have been proposed, including non-parametric and parametric approaches, with the choice of method depending on the specific study design and data characteristics 4.