Definition: The positive predictive value tells you how likely it is that you actually have a disease if you test positive for it. It is defined as the number of true positives (people who test positive who have the disease) divided by the total number of people who test positive, and it varies with test sensitivity, test specificity, and disease prevalence as you can see in the example below. Because of the dependence on disease prevalence in the community where they work, most doctors cannot simply give you a number for the positive predictive value when you go in for any given test -- even if they know the sensitivity and specificity.
Alternate Spellings: PPV
Examples:
If a chlamydia test has 80% sens. & 80% spec. in a population of 100 with a chlamydia prevalence of 10%:
8/10 true + test +
72/90 true - test -
Out of 26 + tests, 8 are true + and 18 are false +. Therefore the positive predictive value (PPV) would be 31% (8/26). Only 1/3 of people testing + would actually have chlamydia.
On the other hand, if the prevalence of chlamydia was 30%:
24/30 true + test +
56/70 true - test -
And the PPV would be 24/38=63%
What about a test that is 80% sens. and 95% spec. in the 20% population?
16/20 true + will test +
76/80 true - will test -
And the PPV would be 16/20=80%
