In diagnostic testing, which statement best reflects sensitivity?

In diagnostic testing, which statement best reflects sensitivity?

• A. A negative result on a highly sensitive test rules in the disease.
• B. A negative result on a highly sensitive test is effective for ruling out the disease.
• C. A positive result on a test with high sensitivity rules in the disease.
• D. Sensitivity measures the probability of a false negative.

Answer: (B)

Sensitivity tells us how good a test is at identifying people who actually have the disease; a highly sensitive test has very few false negatives. Because of that, a negative result on a test with high sensitivity is strong evidence that the disease is not present, so it’s effective for ruling out the condition. Why the other ideas don’t fit: a negative result does not rule in the disease even with high sensitivity—that would require extremely high specificity. A positive result on a test with high sensitivity isn’t guaranteed to indicate disease because sensitivity doesn’t address false positives; specificity does. Sensitivity is not the probability of a false negative itself; it’s the complement of the false negative rate (false negatives are 1 minus sensitivity).

Sensitivity tells us how good a test is at identifying people who actually have the disease; a highly sensitive test has very few false negatives. Because of that, a negative result on a test with high sensitivity is strong evidence that the disease is not present, so it’s effective for ruling out the condition.

Why the other ideas don’t fit: a negative result does not rule in the disease even with high sensitivity—that would require extremely high specificity. A positive result on a test with high sensitivity isn’t guaranteed to indicate disease because sensitivity doesn’t address false positives; specificity does. Sensitivity is not the probability of a false negative itself; it’s the complement of the false negative rate (false negatives are 1 minus sensitivity).