Which metric indicates the probability of a positive test result among those with the disease?

• A. Specificity
• B. Negative Predictive Value
• C. Sensitivity
• D. Positive Predictive Value

Answer: (C)

Sensitivity is the true positive rate, the probability of a positive test result given that the person has the disease. It answers the question: if someone actually has the disease, how likely is the test to detect it? It’s calculated as TP divided by (TP plus FN). This is focused on those who truly have the disease, and a test with high sensitivity minimizes false negatives, which is crucial in screening to avoid missing cases. In contrast, specificity looks at the probability of a negative result among those without disease, while predictive values (positive or negative) depend on disease prevalence and answer different practical questions (e.g., what does a positive test mean for an individual’s disease status). For example, if 100 people have the disease and the test has 90% sensitivity, about 90 will test positive and about 10 will be missed (false negatives).