In evaluating a new rapid diagnostic test (RDT) for malaria, the ROC curve is plotted. A test with an AUC (Area Under the ROC Curve) of 0.95 compared to one with AUC 0.65 implies:
- A The test with AUC 0.95 has better overall discriminatory ability across all thresholds ✓
- B The test with AUC 0.95 has sensitivity of 95% at all cut-off points
- C A perfect test would have AUC = 0.50
- D The AUC reflects only the specificity of the test
Correct answer: A. The test with AUC 0.95 has better overall discriminatory ability across all thresholds
Explanation
The AUC (c-statistic) of a ROC curve represents the probability that the test correctly distinguishes a diseased from a non-diseased individual, across all possible cut-off thresholds. AUC = 1.0 is a perfect test; AUC = 0.5 is a worthless test (no better than chance, represented by the diagonal line); AUC > 0.9 = excellent; 0.8-0.9 = good; 0.7-0.8 = fair; 0.6-0.7 = poor. The test with AUC 0.95 is an excellent discriminator. AUC does not represent sensitivity at any single point — it summarizes the full sensitivity-specificity trade-off curve.
Reference: Park's Textbook of Preventive and Social Medicine, 27th ed.
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