For each of the following terms, provide a definition, outline their derivation and outline their role:
 Sensitivity,
 Specificity,
 Positive Predictive Value,
 Negative Predictive Value.
College Answer
Test 
Disease Present 
Disease Absent 

Positive 
A 
B 
A+B 
Negative 
C 
D 
C+D 
A+C 
B+D 
A+B + C+D 
Using the presence or absence of a disease, and the result a specific test as an example: Sensitivity = proportion of patients with disease detected by positive test = A/(A+C). Very high values essential if wish to catch all with disease, and allow a negative result to virtually rule out the diagnosis.
Specificity = proportion of patients without disease detected by negative test = D/(B+D). Very high values of specificity essential if wish to catch all without the disease, and allow a positive result to rule in the diagnosis.
Positive predictive value = proportion of patients with positive test who have disease = A/(A+B). PPV allows estimate of certainty around positive result.
Negative predictive value = proportion of patients with negative test who do not have disease = D/(C+D). NPV allows estimate of certainty about a negative result.
Discussion
Later papers focus merely on the candidate's ability to apply the formulae.
One can make a strong argument for a return to questions which test one's understanding of the actual concept, rather than demanding the regurgitation of rotelearned equations.
To rotelearn the abovemention equations, here is a helpful list.
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.
References
Altman, Douglas G., and J. Martin Bland. "Statistics Notes: Diagnostic tests 2: predictive values." Bmj 309.6947 (1994): 102.