Diagnostic and screening tests - positive predictive value

Definition

Positive predictive value is the proportion of people with a positive test result who actually have the disease - unlike sensitivity and specificity, PPV is directly dependent on disease prevalence in the tested population, meaning the same test's PPV varies substantially depending on the pre-test probability of disease in the population being tested
The clinically most directly relevant statistic to a patient asking "given my positive result, what's the chance I actually have this disease" - though frequently confused with or conflated against sensitivity/specificity by clinicians and patients alike

Because PPV depends on prevalence, the same test applied to a low-prevalence population produces a lower PPV (more of the positive results are false positives, since even a low false-positive rate applied to a large truly-negative population generates many false positives relative to the smaller number of true positives) than when applied to a high-prevalence population - this is why screening test-positive results in a low-risk population require confirmatory testing before treatment

Calculated as true positives divided by (true positives plus false positives) in the specific tested population - this calculation is sample/population-specific, unlike sensitivity/specificity which are properties of the test itself
Estimating PPV for an individual patient requires accounting for their specific pre-test probability (based on risk factors, clinical presentation), not just the general population prevalence

A positive screening test result in a low pre-test-probability patient/population should prompt confirmatory testing rather than immediate treatment, given the potentially low PPV in this context
Understanding that PPV changes with the population being tested (unlike sensitivity/specificity) is essential to correctly counselling a patient about what their specific positive result actually means for them
Prevalence-dependence of PPV (the defining, frequently tested distinction from sensitivity/specificity), low-prevalence population screening and reduced PPV, confirmatory testing rationale after a positive screen

The same diagnostic test can have a very different positive predictive value depending on the prevalence of disease in the population being tested - applying a screening test to a low-prevalence population produces a lower PPV (more false positives relative to true positives) than applying the identical test to a high-prevalence population, which is why screening programme design must carefully consider the target population's baseline risk

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