In the ROC (Receiver Operating Characteristic) curve analysis of a new diagnostic test, the Area Under the Curve (AUC) is 0.92. This indicates:
- A The test correctly classifies 92% of positive cases (sensitivity = 92%)
- B The test has 92% specificity at the optimal cut-off
- C There is a 92% probability that the test will rank a randomly chosen diseased patient higher than a randomly chosen non-diseased patient ✓
- D The test's false positive rate is 8%
Correct answer: C. There is a 92% probability that the test will rank a randomly chosen diseased patient higher than a randomly chosen non-diseased patient
Explanation
The AUC of an ROC curve represents the probability that a randomly selected diseased individual will have a higher test score than a randomly selected non-diseased individual. AUC 0.92 means the test has 92% discriminatory ability. AUC interpretation: 0.5 = no discrimination (random chance); 0.7–0.8 = acceptable; 0.8–0.9 = excellent; >0.9 = outstanding. AUC is independent of any particular cut-off and summarizes the test's overall performance across all possible thresholds.
Reference: Park's Textbook of Preventive and Social Medicine, 27th ed.
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