You have diagnosed a patient clinically as having SLE and ordered 6 tests. Out of which 4 tests have come positive and 2 are negative. To determine the probability of SLE at this point, you need to know-

Ans. is 'a' i.e. Prior probability of SLE; sensitivity and specificity of each test o Probability allows for an accurate method of calculating how much the likelihood of changes as new information (i.e., a test result) becomes available. o Probability of disease after a given test (post-term probability) can be calculated by (Bayes' theorem) Post test probability = Pretest probability x Likelihood ratio Pre test probability o It is the probability of disease before getting a test. o There is a principal "The interpretation of new information depends on old information". o That means the interpretation of a test result (post-test probability) depends on the probability of disease before test (pre-test probability). o Pre-test probability depends on prevalence, infact prevalence rate is described as pre-test probability of having a disease. Likelihood ratio o The likelihood ratio provides a direct estimate of how much a test result will change the probability of having the disease. o Tests results are often expressed as either positive or negative. o So, there is A likelihood ratio for a positive test result (LR +), and A likelihood ratio for a negative test result (LR-) o The positive likelihood ratio (LR +) tells us how much to increased the probability of a disease if the test is positive. It is calculated by following formula. The likelihood ratio is generally a better descriptor than sensitivity or specificity because it more directly describes the effect of a test result on the probability of disease and it incorporates both the sensitivity and specificity. So, in sho o To know the probability of a disease after a test (post test probability) depends upon : i) Pretest probability --> Prevalence ii) Likelihood ratio --> Specificity & sensitivity