What happens to Positive Predictive Value when disease prevalence decreases?

• A. PPV decreases.
• B. PPV increases.
• C. PPV remains the same.
• D. PPV becomes equal to NPV.

Answer: (A)

Positive Predictive Value, the chance that someone really has the disease given a positive test, depends on how common the disease is in the group being tested. If the disease becomes rarer but the test’s accuracy stays the same, the number of true positives among those who test positive drops relative to the number of false positives, so the proportion of positives that are true positives goes down.

A simple way to see this is that PPV is determined by how many true positives there are compared with all positives: as prevalence falls, true positives shrink, while the false positives (driven by the test’s false positive rate) don’t shrink in the same way, making PPV smaller. For example, with reasonable test accuracy, having 10% disease in the population might yield a PPV around two-thirds, but dropping prevalence to 1% can drop PPV to around 15%—even though the test performance hasn’t changed. So, PPV decreases when disease prevalence decreases.