Which measure is useful for choosing a test and interpreting results at the population level, and is related to the predictive value of a test?

• A. Prevalence
• B. Incidence
• C. Sensitivity
• D. Specificity

Answer: (A)

Prevalence is the proportion of individuals in a population who have the disease at a given time. This population-level measure is key for selecting a test and interpreting results because it sets the prior probability of disease and directly influences predictive values. Predictive values depend on how common the disease is: when prevalence is higher, the positive predictive value tends to be higher (a positive result is more likely a true positive), while in low-prevalence settings the positive result is more likely a false positive. Conversely, negative predictive value tends to be higher when prevalence is low. Sensitivity and specificity describe how a test performs independent of how common the disease is, and incidence measures new cases over time, so they don’t directly capture population-level predictive value.