What does positive predictive value measure?

What does positive predictive value measure?

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

Answer: (B)

Positive predictive value measures the probability that a person with a positive test result truly has the disease. It is the proportion of true positives among all positive test results, or TP divided by (TP plus FP). In other words, among everyone who tests positive, how many actually have the disease? This metric depends on how common the disease is in the population (prevalence) as well as the test’s performance characteristics (sensitivity and specificity). When the disease is more prevalent, PPV tends to be higher because positives are more likely to be true positives. When prevalence is low, even a test with good sensitivity and specificity can yield a lower PPV due to more false positives. For contrast, note that a negative predictive value answers how likely a negative result means the person truly does not have the disease, while sensitivity and specificity describe test performance conditional on disease status or non-disease.

Positive predictive value measures the probability that a person with a positive test result truly has the disease. It is the proportion of true positives among all positive test results, or TP divided by (TP plus FP). In other words, among everyone who tests positive, how many actually have the disease?

This metric depends on how common the disease is in the population (prevalence) as well as the test’s performance characteristics (sensitivity and specificity). When the disease is more prevalent, PPV tends to be higher because positives are more likely to be true positives. When prevalence is low, even a test with good sensitivity and specificity can yield a lower PPV due to more false positives.

For contrast, note that a negative predictive value answers how likely a negative result means the person truly does not have the disease, while sensitivity and specificity describe test performance conditional on disease status or non-disease.