From WikiLectures

This is the probability of a positive test result from patients with disease a/a+c. Sensitivity of a test gives values from 0 to 1 (0-100%) and tells us how the test captures the presence of the reference condition in the body.

[math]\displaystyle{ \begin{align} \text{sensitivity} & = \frac{\text{number of true positives}}{\text{number of true positives} + \text{number of false negatives}} \\ \\ & = \text{probability of a positive test given that the patient is ill} \end{align} }[/math]

For example, if he had a mammography screening test for breast cancer with 100% sensitivity, it would mean that all women who had breast cancer, the tumour was actually detected. We have a group of 4 women - Lucy, Jane, Cathie and Lenka. 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 100% sensitivity.

Test Disease + Healthy- Total
+ a b a+b
- c d c+d
Total a+c b+d n
Searchtool right.svg For more information see Requirements at Examination Methods.

Links[edit | edit source]

Related Articles[edit | edit source]

Bibliography[edit | edit source]

  • 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.