Sensitivity and specificity

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These are statistical terms that are often confused. These terms can be illustrated by way of an example:

At a particular hospital a MIBG scanner is used to detect phaeochromocytomas. A positive scan was reported in 38 cases. An audit showed:

true positive (TP) 10, true negative (TN) 25,

false positive (FP) 0, false negative (FN) 3

patients with phaeochromocytoma TP (person with a phaeochromocytoma and positive test)

patients with phaeochromocytoma FN (person with a phaeochromocytoma and negative test)

patients without phaeochromocytoma FP (person without a phaeochromocytoma with a positive test)

patients without a phaeochromocytoma TN (person without a phaeochromoytoma with a negative test)







i.e. proportion of people with a phaeochromocytoma who are corectly identified by the screening test = 77%



i.e. proportion of people without phaeochromocytoma who have had a negative test result = 100%



positive predictive value = 100xTP/(TP+FP) = 100 x 10/(10+0) = 100%

i.e. the proportion of screening tests that are correct.

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phaeochromocytoma present	phaeochromyctoma absent
test result positive TP = 10	test result positive FP = 0
test result negative FN = 3	test result negative TN = 25

Sensitivity and specificity

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