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.
College Answer
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:
 Question 13 from the first paper of 2005
 Question 29.2 from the first paper of 2008
 Question 19.1 from the first paper of 2010
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.