A cancer screening programme tests a population of 10,000 using a test with sensitivity 90% and specificity 95%. The disease prevalence is 1% (100 true cases). How many FALSE POSITIVES are expected?

• A 10
• B 100
• C 90
• D 495 ✓

Explanation

True cases = 100; Non-cases (disease-free) = 9,900. Specificity 95% means the test correctly identifies 95% of non-cases as negative; 5% of non-cases will test falsely positive. False Positives = 5% × 9,900 = 495. True Positives = 90% × 100 = 90. This illustrates the critical impact of low prevalence on PPV: even with high specificity, a low-prevalence disease generates many false positives relative to true positives.

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

High-yield for: NEET PGINI-CETNExTFMGEUSMLEPLABMRCP

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