[A statistical model for interpreting the antibiogram]

Abstract

Up to now, to interpret antibiotic susceptibility tests, the common practice has been to use: first, breakpoints without any quantitative justification, secondly, concordance curves between the different measurement techniques; these are not well adapted to the heterogeneous character of bacterial populations. We hereby propose another method: it is based on a global data analysis for each bacterial species, each antibiotic family and each measurement technique. So, we have drawn up a new model for the interpretation, both global and data-processed; it is based on qualifying classes, which are obtained and interpreted by hierarchical ascendent classification, principal components analysis, and comparison with pharmacological data. It can be used by any biologist. What is more, justified breakpoints with a numerical risk and quality control are defined. There are also some additional uses: evaluation of the effect of new antibiotics, standardization of new measurement techniques, detection of the emergence of new bacterial resistance in patients, guidance for research into unknown resistance mechanisms and characters.