What does Positive Predictive Value indicate?

• A. The probability that a person with a positive result truly has the disease.
• B. The probability that a person with a negative result truly does not have the disease.
• C. The proportion of positives that are false positives.
• D. The proportion of negatives that are true negatives.

Answer: (A)

Positive Predictive Value is the probability that a person with a positive test result actually has the disease. It’s calculated as true positives divided by all positive test results (true positives plus false positives). This means PPV depends on the test’s accuracy (sensitivity and specificity) and also on how common the disease is in the population being tested. In settings where the disease is rare, even a good test can yield a lower PPV because a larger share of positives may be false positives. The other statements describe the Negative Predictive Value (the probability that a negative result truly means no disease) and proportions that don’t reflect PPV, so they don’t capture what PPV measures.