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Sensitivity and specificity

Last reviewed dd mmm yyyy. Last edited dd mmm yyyy

Authoring team

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

where:

  • 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)





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 = 100xTP /(TP+FN) = 100 x 10(10 + 3) = 77%
    • i.e. proportion of people with a phaeochromocytoma who are corectly identified by the screening test = 77%

  • specificity = 100xTN /(TN+FP) = 100 x 25 /(25+0) = 100%
    • 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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