An easy way to understand PPV is to dissect the name. In Positive Predictive Value, we are looking at how good a positive test is at predicting that a person actually has a disease.
Positive predictive value refers to the percentage of patients with a positive test for a disease who actually have the disease.
For example, if the PPV of a test for breast cancer is 80%, it means 80% of patient who tested positive actually had breast cancer.
Among patients who test positive, the PPV measures how likely it is that the person actually has the disease. That is, PPV is the probability of their result being due to disease. In other words, PPV is the probability of having a condition, given a positive test. PPV depends on the prevalence of the disease in the population and the sensitivity/specificity of the test. E.g. an overly sensitive test that gives many false positives will have a lower PPV. Also, the higher the prevalence, the greater the PPV will be. Mathematically, the PPV is the number of true positives divided by the number of people with a positive test. PPV = A / ( A + B)