The positive predictive value of a test depends most on which factor?

• A. Disease prevalence in the tested population
• B. Sensitivity
• C. Specificity
• D. Sample size

Answer: (A)

Positive predictive value is the probability that a person actually has the disease given a positive test result. The factor that most determines this is how common the disease is in the population being tested. When disease prevalence is high, a positive result is more likely to be a true positive; when prevalence is low, many positives are false positives even if the test is reasonably sensitive and specific.

This relationship is captured by the formula PPV = (sensitivity × prevalence) / [ (sensitivity × prevalence) + (1 − specificity) × (1 − prevalence) ]. It shows that prevalence directly shifts the balance between true positives and false positives. Sensitivity and specificity matter, but their impact on PPV is mediated by how common the disease is. Sample size, on the other hand, affects the precision of the PPV estimate rather than the PPV itself.