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Specificity is the probability of a negative result in healthy patients b/b+d. The specificity of a test reflects on the ability of a test to identify true negatives.

\text{specificity} & = \frac{\text{number of true negatives}}{\text{number of true negatives} + \text{number of false positives}} \\  \\
& = \text{probability of a negative test given that the patient is well}

For example, if he had a mammography screening for breast cancer with 100% specificity, it would mean that all women without breast cancer that underwent screening tested negative. We have a group of 4 women - Lucy, Jane, Cathie and Lenka. has breast cancer. Lucy has breast cancer. All women undergo the screening mammography. It detects Lucy and Jane as positive. Lucy is really positive. Jane is a false positive. Cathie and Lenka are actually negative. Nobody is falsely negative. When you enter the values into the formula above, we find that the test showed about 67% specificity (specificity = 0.67). One woman with no tumor was identified as positive (we have one woman falsely positive).

Test Disease + Healthy- Total
+ a b a+b
- c d c+d
Total a+c b+d n
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  • BENCKO, Vladimír. Epidemiologie, výukové texty pro studenty. 2nd edition. Karolinum, 2002. ISBN 80-246-0383-7..
  • BENCKO, Vladimír. Biomedicínská statistika. 1st edition. Karolinum, 2003. ISBN 80-246-0763-8.
  • KUPKA, Karel. Nukleární medicína. 1st edition. Karolinum, 2007. ISBN 978-80-903584-9-2.