# Question 14

Outline the way you would calculate and how you might use the following features of a diagnostic test: sensitivity, specificity, positive predictive value and negative predictive value.

Disease

Present      Absent

 Test Positive A B A+B Negative C D C+D A+C B+D A+B + C+D

Sensitivity = proportion of patients with disease detected by positive test = A/(A+C) Specificity = proportion of patients without disease detected by negative test = D/(B+D)
Positive predictive value = proportion of patients with positive test who have disease = A/(A+B) Negative predictive value = proportion of patients with negative test who do not have disease = D/(C+D)
Very high sensitivity means few false negatives. Very high specificity means few false positives.

## Discussion

This question closely resembles a whole mass of other questions:

The questions may not be identical, but they test the exact same concepts Here's a helpful list of equations  the college expects us to memorise.

Sensitivity = true positives / (true positives + false negatives)

This is the proportion of patients in whom disease which was correctly identified by the test.

Specificity = true negatives / (true negatives + false positives)

This is the proportion of patients in whom the disease was correctly excluded

Positive predictive value = (true positives / total positives)

This is the proportion of patients with positive test results who are correctly diagnosed.

Negative predictive value = (true negatives / total negatives)

This is the proportion of patients with negative test results who are correctly diagnosed.