In a ROC curve analysis for a cardiac biomarker, the area under the curve (AUC) is 0.92. What does this BEST indicate?

• A The test correctly diagnoses 92% of all patients
• B The sensitivity of the test at the optimal cut-off is 92%
• C The specificity of the test at the optimal cut-off is 92%
• D If a diseased and non-diseased individual are randomly selected, there is a 92% probability the diseased individual scores higher ✓

Explanation

The AUC of a ROC curve represents the probability that a randomly chosen diseased individual will have a higher test score than a randomly chosen non-diseased individual. An AUC of 0.92 denotes excellent discriminatory ability. It is not the same as sensitivity, specificity, or diagnostic accuracy at a single cut-off. An AUC of 0.5 corresponds to chance-level discrimination.

Reference: Park's Textbook of Preventive and Social Medicine, 27th ed.

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