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Latest revision as of 13:04, 18 March 2025
Positive Predictive Value (PPV) is a statistical concept widely used in medical testing and diagnostic medicine. It refers to the probability that subjects with a positive screening test truly have the disease. PPV is determined by the sensitivity and specificity of the test, as well as the prevalence of the disease in the population being tested.
Definition[edit]
The Positive Predictive Value (PPV) is defined as the proportion of positive test results that are true positives. This means that PPV is the probability that when the test is positive, the subject really has the disease. It is calculated using the formula:
PPV = (True Positives) / (True Positives + False Positives)
Factors Affecting PPV[edit]
The PPV of a test is not a fixed attribute of the test - it can vary with the prevalence of the disease in the population being tested. If the disease is rare, even a very good test may end up with a low PPV, simply because there are so few true positive results to be had.
Importance in Medical Testing[edit]
In medical testing, the PPV of a test is important because it affects the test's utility in certain populations. For example, a test with a high PPV is useful for confirming a diagnosis in a population where the disease is suspected to be prevalent. On the other hand, a test with a low PPV may be less useful in such a population, because a positive result is less likely to reflect a true positive.
