A cervical cancer screening test has sensitivity 70% and specificity 80% in a population with 5% prevalence of cervical cancer. The Positive Predictive Value (PPV) of this test is approximately:

• A About 35%
• B About 70%
• C About 45%
• D About 16% ✓

Explanation

Using Bayes theorem with prevalence 5% (0.05): True Positives = 0.70 × 0.05 = 0.035; False Positives = (1-0.80) × 0.95 = 0.20 × 0.95 = 0.19; PPV = TP/(TP+FP) = 0.035/(0.035+0.19) = 0.035/0.225 ≈ 15.6% ≈ 16%. This demonstrates that even with reasonable sensitivity and specificity, PPV is low when disease prevalence is low — the fundamental reason why screening is best targeted at high-prevalence populations. Sensitivity and specificity are intrinsic test properties, while PPV and NPV depend on prevalence.

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

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