Positive and negative predictive values

Positive Predictive Value (PPV)

Positive predictive value (PPV) is a measure of the accuracy of a diagnostic test for a disease. It is defined as the proportion of people who test positive for the disease who actually have the disease. In other words, it is the probability that a positive test result is correct or the probability that individuals with positive test results truly have the disease.

Formula: PPV = $\frac{\text{True Positives}}{\text{True Positives}+\text{False Positives}}$

High PPV means that a positive test result is likely to be accurate, minimizing the risk of false positives. It is particularly important in situations where the consequences of a false positive are significant, such as invasive follow-up procedures.

Negative Predictive Value (NPV)

Negative predictive value (NPV) is a measure of the accuracy of a diagnostic test for a disease. It is defined as the proportion of people who test negative for the disease who actually do not have the disease. In other words, it is the probability that a negative test result is correct or the probability that individuals with negative test results truly do not have the disease.

Formula: NPV = $\frac{\text{True Negatives}}{\text{True Negatives}+\text{False Negatives}}$

High NPV ensures...