What does negative predictive value represent?

What does negative predictive value represent?

• A. TN / (TN + FN)
• B. TP / (TP + FP)
• C. TN / (TP + FN)
• D. FN / (TN + FP)

Answer: (A)

Negative predictive value is the probability that someone truly does not have the disease when the test result is negative. In a two-by-two setup, those who test negative include true negatives (correctly identified as disease-free) and false negatives (those who actually have the disease but were missed). So the NPV is the count of true negatives divided by all negatives: TN divided by (TN plus FN). For example, if 100 people test negative and 85 of them truly don’t have the disease while 15 actually do, the NPV is 85/100 = 0.85. This means a negative result is 85% reliable for ruling out disease in this group. NPV tends to be higher in populations with low disease prevalence and lower when the disease is common, because the proportion of false negatives among those testing negative changes with prevalence. This metric is distinct from specificity or positive predictive value, which involve different combinations of true/false positives and negatives.

Negative predictive value is the probability that someone truly does not have the disease when the test result is negative. In a two-by-two setup, those who test negative include true negatives (correctly identified as disease-free) and false negatives (those who actually have the disease but were missed). So the NPV is the count of true negatives divided by all negatives: TN divided by (TN plus FN).

For example, if 100 people test negative and 85 of them truly don’t have the disease while 15 actually do, the NPV is 85/100 = 0.85. This means a negative result is 85% reliable for ruling out disease in this group.

NPV tends to be higher in populations with low disease prevalence and lower when the disease is common, because the proportion of false negatives among those testing negative changes with prevalence. This metric is distinct from specificity or positive predictive value, which involve different combinations of true/false positives and negatives.