Positive Predictive Value
“When evaluating the feasibility or the success of a screening program, one should also consider the positive and negative predictive values. These are also computed from the same 2 x 2 contingency table, but the perspective is entirely different.
- Positive predictive value is the probability that subjects with a positive screening test truly have the disease.
- Negative predictive value is the probability that subjects with a negative screening test truly don’t have the disease.
One way to avoid confusing this with sensitivity and specificity is to imagine that you are a patient and you have just received the results of your screening test (or imagine you are the physician telling a patient about their screening test results. If the test was positive, the patient will want to know the probability that they really have the disease, i.e., how worried should they be?
Conversely, if it is good news, and the screening test was negative, how reassured should the patient be? What is the probability that they are disease free?
Another way that helps me keep this straight is to always orient my contingency table with the gold standard at the top and the true disease status listed in the columns. The illustrations used earlier for sensitivity and specificity emphasized a focus on the numbers in the left column for sensitivity and the right column for specificity. If this orientation is used consistently, the focus for predictive value is on what is going on within each row in the 2 x 2 table, as you will see below.” Read More