Abstract：
BACKGROUND:The probability of a disease, given the result of two diagnostic tests, can be calculated by multiplying the odds of disease after the first test by the likelihood ratio of the second test. OBJECTIVE:To illustrate the error that occurs when calculating disease probability by combining the results of tests that are correlated. METHODS:Simulation study in which we randomly generated disease status and the results of two binary tests for a range of disease prevalence, test-operating characteristics, and correlation between tests. The primary outcome was the absolute difference between calculated and true probability of disease after two positive tests. RESULTS:When the tests were correlated, the calculated probability of a disease exceeded the true probability of the disease. With perfect correlation, the true probability of the disease after two positive tests equaled that after a single positive test. Error arising from correlated tests increased as the difference in the calculated probability between the first and second positive tests increased. We noted several combinations of disease prevalence, test-operating characteristics, and test correlation where the absolute difference between calculated and true probability of disease exceeded 25%. CONCLUSION:Disease probability is overestimated when the results of correlated tests are combined. Clinicians must consider the correlation between serial tests when calculating the posttest probability.
journal_name
J Clin Epidemioljournal_title
Journal of clinical epidemiologyauthors
van Walraven C,Austin PC,Jennings A,Forster AJdoi
10.1016/j.jclinepi.2009.04.010subject
Has Abstractpub_date
2009-12-01 00:00:00pages
1301-5issue
12eissn
0895-4356issn
1878-5921pii
S0895-4356(09)00159-0journal_volume
62pub_type
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