Which statement correctly describes how prevalence affects PPV?

Which statement correctly describes how prevalence affects PPV?

• A. PPV is independent of prevalence.
• B. PPV rises when prevalence is high; falls when prevalence is low.
• C. PPV equals sensitivity.
• D. PPV equals NPV.

Answer: (B)

The key idea is that PPV depends on how common the disease is in the population. Positive predictive value is the probability that a person who tests positive actually has the disease. If the test’s sensitivity and specificity stay the same, increasing disease prevalence makes a positive result more likely to come from someone with the disease, so PPV goes up. Conversely, when prevalence is low, many positives come from people without the disease, so PPV goes down. A helpful way to see this is the formula: PPV = (sensitivity × prevalence) / [(sensitivity × prevalence) + (1 − specificity) × (1 − prevalence)]. As prevalence increases, the numerator grows relative to the denominator in a way that raises the ratio, and as prevalence decreases, the ratio falls. That’s why PPV rises with higher prevalence and falls with lower prevalence. This is why statements claiming PPV is independent of prevalence aren’t correct, and why PPV is not equal to sensitivity or to NPV.

The key idea is that PPV depends on how common the disease is in the population. Positive predictive value is the probability that a person who tests positive actually has the disease. If the test’s sensitivity and specificity stay the same, increasing disease prevalence makes a positive result more likely to come from someone with the disease, so PPV goes up. Conversely, when prevalence is low, many positives come from people without the disease, so PPV goes down.

A helpful way to see this is the formula: PPV = (sensitivity × prevalence) / [(sensitivity × prevalence) + (1 − specificity) × (1 − prevalence)]. As prevalence increases, the numerator grows relative to the denominator in a way that raises the ratio, and as prevalence decreases, the ratio falls. That’s why PPV rises with higher prevalence and falls with lower prevalence.

This is why statements claiming PPV is independent of prevalence aren’t correct, and why PPV is not equal to sensitivity or to NPV.