What does Positive Predictive Value (PPV) measure?

What does Positive Predictive Value (PPV) measure?

• A. Probability of a disease given a positive test
• B. Probability of a positive test given the disease
• C. Sensitivity of the test
• D. Probability of disease given a negative test

Answer: (A)

PPV tells you the probability that a person actually has the disease given that their test result is positive. It’s calculated as true positives divided by all positive test results, so PPV = TP / (TP + FP). This is the practical meaning of a positive result: among those who test positive, how many truly have the disease? This differs from sensitivity, which is the chance of a positive result among those who have the disease, and from specificity, which is the chance of a negative result among those without the disease. PPV also depends on how common the disease is in the population (prevalence): higher prevalence increases PPV because more positives are true cases, while lower prevalence makes a positive result more likely to be a false positive. A related concept is the probability of disease given a negative test, which is the negative predictive value.

PPV tells you the probability that a person actually has the disease given that their test result is positive. It’s calculated as true positives divided by all positive test results, so PPV = TP / (TP + FP). This is the practical meaning of a positive result: among those who test positive, how many truly have the disease?

This differs from sensitivity, which is the chance of a positive result among those who have the disease, and from specificity, which is the chance of a negative result among those without the disease. PPV also depends on how common the disease is in the population (prevalence): higher prevalence increases PPV because more positives are true cases, while lower prevalence makes a positive result more likely to be a false positive. A related concept is the probability of disease given a negative test, which is the negative predictive value.