Application of the Vertex Exchange Method to estimate a semi-parametric mixture model for the MIC density of Escherichia coli isolates tested for susceptibility against ampicillin.
In the last decades, considerable attention has been paid to the collection of antimicrobial resistance data, with the aim of monitoring non-wild-type isolates. This monitoring is performed based on minimum inhibition concentration (MIC) values, which are collected through dilution experiments. We present a semi-parametric mixture model to estimate the entire MIC density on the continuous scale. The parametric first component is extended with a non-parametric second component and a new back-fitting algorithm, based on the Vertex Exchange Method, is proposed. Our data example shows how to estimate the MIC density for Escherichia coli tested for ampicillin and how to use this estimate for model-based classification. A simulation study was performed, showing the promising behavior of the new method, both in terms of density estimation as well as classification.
Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Diepenbeek 3590, Belgium stijn.jaspers@uhasselt.be.
Stijn
S
Jaspers
Interuniversity Institute for Biostatistics and Statistical Bioinformatics, KU Leuven, Leuven B-3000, Belgium.
Geert
G
Verbeke
Southampton Statistical Sciences Research Institute, University of Southampton, Highfield, Southampton SO17 I BJ, UK.
Dankmar
D
Böhning
Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Diepenbeek 3590, Belgium.
Marc
M
Aerts
D000667:Ampicillin / Q000494:pharmacology*; D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D024881:Drug Resistance, Bacterial; D004926:Escherichia coli / Q000187:drug effects* / Q000302:isolation & purification; D008826:Microbial Sensitivity Tests / Q000379:methods*
D000900:Anti-Bacterial Agents; D000667:Ampicillin
Antimicrobial resistance; Censoring; Model-based classification; Semi-parametric; Vertex Exchange Method