Define sensitivity and specificity and describe interpretation for a test with 90% sensitivity and 85% specificity.

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Multiple Choice

Define sensitivity and specificity and describe interpretation for a test with 90% sensitivity and 85% specificity.

The key idea is how sensitivity and specificity describe a test’s ability to identify disease and non-disease correctly. Sensitivity is the proportion of true positive cases that the test correctly flags, calculated as TP divided by (TP plus FN). This tells you how good the test is at finding people who actually have the disease. If sensitivity is 90%, about 90 out of 100 people with the disease will test positive, while about 10 will be missed (false negatives). Specificity is the proportion of true negative cases that the test correctly flags, calculated as TN divided by (TN plus FP). This tells you how good the test is at ruling out disease in people who don’t have it. If specificity is 85%, about 85 out of 100 disease-free individuals will test negative, while about 15 will test positive (false positives). So, a test with 90% sensitivity and 85% specificity will miss some true cases (about 10%) and produce some false positives (about 15% among those without disease). The definitions used here match the standard formulas: sensitivity = TP/(TP+FN) and specificity = TN/(TN+FP).

The key idea is how sensitivity and specificity describe a test’s ability to identify disease and non-disease correctly. Sensitivity is the proportion of true positive cases that the test correctly flags, calculated as TP divided by (TP plus FN). This tells you how good the test is at finding people who actually have the disease. If sensitivity is 90%, about 90 out of 100 people with the disease will test positive, while about 10 will be missed (false negatives).

Specificity is the proportion of true negative cases that the test correctly flags, calculated as TN divided by (TN plus FP). This tells you how good the test is at ruling out disease in people who don’t have it. If specificity is 85%, about 85 out of 100 disease-free individuals will test negative, while about 15 will test positive (false positives).

So, a test with 90% sensitivity and 85% specificity will miss some true cases (about 10%) and produce some false positives (about 15% among those without disease). The definitions used here match the standard formulas: sensitivity = TP/(TP+FN) and specificity = TN/(TN+FP).

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