Positive Predictive Value (PPV) and Prevalence
Increased prevalence of an outcome will lead to more cases being "picked up"
Positive predictive value (PPV) is the likelihood that a person with a "+" on a diagnostic test actually has the disease state as it is detected using a "gold standard." Another way of defining PPV is how believable a "+" test result is in a given population.
As the prevalence of a disease state in a given population increases, the positive predictive value of a test will increase. This is simply due to the fact that there are more cases or disease states that can be detected.
If you are working with a rare outcome in a given population, be aware that less prevalent outcomes increase the number of false positives detected by a diagnostic test. By definition, lower prevalence dictates that there are not many true positives or "sick" people in a given population. With so few actual cases and more people being tested, the inherent measurement error associated with diagnostic testing will yield more and more false positives.
So, in conclusion, it is very important to know the baseline prevalence of your outcome or disease state in your population of interest when assessing diagnostic tests. Higher prevalence leads to increased PPV and lower prevalence leads to increased false positives.
As the prevalence of a disease state in a given population increases, the positive predictive value of a test will increase. This is simply due to the fact that there are more cases or disease states that can be detected.
If you are working with a rare outcome in a given population, be aware that less prevalent outcomes increase the number of false positives detected by a diagnostic test. By definition, lower prevalence dictates that there are not many true positives or "sick" people in a given population. With so few actual cases and more people being tested, the inherent measurement error associated with diagnostic testing will yield more and more false positives.
So, in conclusion, it is very important to know the baseline prevalence of your outcome or disease state in your population of interest when assessing diagnostic tests. Higher prevalence leads to increased PPV and lower prevalence leads to increased false positives.
