A screening test with sensitivity 85% and specificity 90% is applied in a population with a disease prevalence of 2%. What will happen to the PPV if the test is applied in a high-risk population with a prevalence of 20%?

• A PPV will decrease because more people are tested
• B PPV will remain unchanged as it depends only on sensitivity and specificity
• C Specificity will decrease to maintain constant PPV
• D PPV will increase because higher prevalence increases the proportion of true positives among all positives ✓

Explanation

PPV (Positive Predictive Value) is heavily dependent on disease prevalence. Bayes' theorem: PPV = (sensitivity × prevalence) / [(sensitivity × prevalence) + (1 − specificity) × (1 − prevalence)]. At 2% prevalence, PPV ≈ 15%; at 20% prevalence, PPV ≈ 68%. Higher prevalence means a greater proportion of positive test results are true positives, dramatically increasing PPV. NPV decreases as prevalence increases. Sensitivity and specificity are intrinsic test properties independent of prevalence.

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

High-yield for: NEET PGINI-CETNExTFMGEUSMLEPLABMRCP

Written and medically reviewed by the StethoPrep medical team.