Which statement best describes predictive values in relation to prevalence and test characteristics?

• A. Predictive values are determined solely by the test's sensitivity.
• B. Predictive values are fixed and do not vary with prevalence.
• C. Predictive values are highly affected by disease prevalence and specificity, and to a lesser extent by sensitivity.
• D. Predictive values depend only on the sample size.

Answer: (C)

Predictive values tell us how likely it is that someone actually has or does not have a disease based on their test result. They aren’t fixed; they change with how common the disease is in the population (prevalence) and with the test’s characteristics. A positive result is more trustworthy (higher predictive value) when the disease is more prevalent and when the test is highly specific, which minimizes false positives. A negative result is more trustworthy when the test is highly sensitive, which minimizes false negatives, and when the disease is less prevalent. Taken together, predictive values are strongly driven by prevalence and specificity, with sensitivity also playing a role but typically to a lesser extent for the overall predictive values. This is why that statement best describes how predictive values behave in relation to prevalence and test characteristics.