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Statistical properties and inference of the antimicrobial MIC test
Author(s) -
Annis David H.,
Craig Bruce A.
Publication year - 2005
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.2207
Subject(s) - inference , statistics , minimum inhibitory concentration , antimicrobial drug , minimum bactericidal concentration , statistical inference , mathematics , antimicrobial , econometrics , computer science , biology , microbiology and biotechnology , artificial intelligence
A common method for measuring the drug‐specific minimum inhibitory concentration (MIC) of an antibacterial agent is via a two‐fold broth dilution test known as the MIC test. Because this procedure implicitly rounds data upward, inference based on unadjusted measurements is biased and overestimates bacterial resistance to a drug. We detail this test procedure and its associated bias, which, in many cases, has an expected value of approximately 0.5 on the log 2 scale. In addition, new bias‐corrected estimates of resistance are proposed. A numeric example is used to illustrate the extent to which the traditional resistance estimate can overestimate the true proportion of resistant strains, a phenomenon which is remedied by using the proposed estimates. Published in 2005 by John Wiley & Sons, Ltd.