A sequence of diagnostic tests may be necessary to achieve a post-test probability sufficient to diagnose a condition. The number of tests of comparable quality required to achieve the final end-point can be calculated using Baye's theorem.
Parameters:
(1) sensitivity of the test
(2) specificity of the test
(3) prevalence of the condition in the population
(4) target post-test probability
(5) cost of the test
Algorithm:
(1) The post-test probability after the first test can be determined using Baye's theorem with prevalence as the initial pre-test probability.
(2) Each time a comparable test is run the post-test probability from the previous test is used as the new pre-test probability.
(3) The algorithm is complete when the post-test probability after a test is equal to or greater than the target post-test probability.
cost of the testing =
= (cost for the test) * (number of tests performed)
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