Pretest probability (~ prevalence)
This is the proportion of people in the population at risk who have the disease at a specific time or time interval, i.e. the point prevalence or the period prevalence of the disease. In other words, it is the probability − before the diagnostic test is performed − that a patient has the disease. Pretest probabilities may be estimated from routine data, practice data or clinical judgement.
Posttest probability
This is the proportion of patients testing positive who truly have the disease. It is similar to the positive predictive value but apart from the test performance also includes a patientbased probability of having disease
Posttest probability =  Posttest odds  
(1 + Posttest odds) 
Using pre and posttest probability and LR
By comparing the pre and posttest probabilities, it is possible to determine whether the probability of diagnosis has risen (i.e. the posttest probability has increased) or fallen (i.e. posttest probability has decreased). In this way, it is possible to provide comprehensive information about a screening test in order to enable informed choice. In practice assessing posttest probability is commonly done by using a Likelihood Ratio Nomogram (below):
Summary of calculations of key features of screening tests
Feature 
Formula 
Sensitivity 
a/ (a+c) 
Specificity 
d/ (b+d) 
Positive predictive value 
a/ (a+b) 
Negative predictive value 
d/ (c+d) 
Accuracy 
(a+d)/ (a+b+c+d) 
Likelihood ratio: 

Positive test  Sensitivity/ (1specificity) 
Negative test  (1sensitivity)/specificity 
© Dr Murad Ruf and Dr Oliver Morgan 2008, Dr Kelly Mackenzie 2017