European harmonization of MIC breakpoints for antimicrobial susceptibility testing of bacteria

Kahlmeter, Gunnar; Brown, Derek F. J.; Goldstein, F. W.; MacGowan, Alasdair; Mouton, Johan W.; Österlund, Anders; Rodloff, Arne C.; Steinbakk, Martin; Urbášková, P; Vatopoulos, Alkiviadis

doi:10.1093/jac/dkg312

Cited by 343 publications

(323 citation statements)

References 4 publications

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“…Typically, MIC values are dichotomised using epidemiological cut-off values (ECOFFs) to define nonwild-type isolates [3,4]. As such, the MIC distribution is collapsed into a binary variable, and a large amount of information is lost.…”

Section: Introductionmentioning

confidence: 99%

“…Annis and Craig [5] provide a distribution free estimate, which is still suffering from the shortcoming that a trend above the ECOFF cannot be detected. One can remedy this disadvantage via the exploration of the MIC distribution on the full continuous scale, in which interest emerged during the process of harmonisation of breakpoints [4]. Craig [6] proposed an appealing maximum likelihood estimate based on a censored normal mixture.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of the wild‐type minimum inhibitory concentration value distribution

Jaspers

Aerts

Verbeke

et al. 2013

Statistics in Medicine

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Antimicrobial resistance has become one of the main public health burdens of the last decades, and monitoring the development and spread of non-wild-type isolates has therefore gained increased interest. Monitoring is performed based on the minimum inhibitory concentration (MIC) values, which are collected through the application of dilution experiments. In order to account for the unobserved population heterogeneity of wild-type and non-wild-type isolates, mixture models are extremely useful. Instead of estimating the entire mixture globally, it was our major aim to provide an estimate for the wild-type first component only. The characteristics of this first component are not expected to change over time, once the wild-type population has been confidently identified for a given antimicrobial. With this purpose, we developed a new method based on the multinomial distribution, and we carry out a simulation study to study the properties of the new estimator. Because the new approach fits within the likelihood framework, we can compare distinct distributional assumptions in order to determine the most suitable distribution for the wild-type population. We determine the optimal parameters based on the AIC criterion, and attention is also paid to the model-averaged approach using the Akaike weights. The latter is thought to be very suitable to derive specific characteristics of the wild-type distribution and to determine limits for the wild-type MIC range. In this way, the new method provides an elegant means to compare distinct distributional assumptions and to quantify the wild-type MIC distribution of specific antibiotic-bacterium combinations.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Estimation of the wild‐type minimum inhibitory concentration value distribution

Jaspers

Aerts

Verbeke

et al. 2013

Statistics in Medicine

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“…This CLSI protocols is functionally equivalent to that previously published by Alderman and Smith (2001) but is associated with acceptable ranges for control strains. Miller and Reimschuessel (2006) have recently used the MIC and disc diffusion data generated by the application of the CLSI protocols (2006a,b) to 217 strains of Aeromonas salmonicida to estimate appropriate epidemiological cut-off values (EUCAST, 2000;Kahlmeter et al, 2003;CLSI, 2002) for SFO.…”

Section: Bacteriamentioning

confidence: 99%

“…With respect to the therapy of disease in aquatic animals we are a long way from having the PK/PD and clinical efficacy data that would be required to set clinical breakpoints. In such situations, Kahlmeter et al (2003) have argued that it is legitimate to use epidemiological cut-off values generated from distributions of MIC data, to estimate provisional and tentative breakpoints.…”

Section: Nri Cut-off Values and Clinical Breakpointsmentioning

confidence: 99%

The advantages of the use of discs containing single agents in disc diffusion testing of the susceptibility of Aeromonas salmonicida to potentiated sulphonamides

Douglas¹,

Ruane²,

Geary³

et al. 2007

Aquaculture

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The susceptibilities of 106 strains of Aeromonas salmonicida to trimethoprim/sulfamethoxazole (SFT) were determined in two laboratories using the Clinical and Laboratory Standards Institute's M42-A disc diffusion protocols. The data generated by the use of discs containing 25 μg SFT (SFT25) allowed the strains to be placed into two groups. Strains in one group (17 strains) generated no inhibition zones and the zones obtained from the other 89 strains were distributed over a wide range but showed no natural division into separate sub-classes. A further investigation performed by one of the participating laboratories, of the susceptibility of 91 of these 106 strains used discs containing 100 μg sulfmethoxazole (SFM100) and 5 μg trimethoprim (TMP5). Application of normalised resistance interpretation to these data allowed the estimation of epidemiological cut-off values for WT strains of ≥ 9 mm for SFM100 and ≥ 21 mm for TMP5. This investigation demonstrated the presence of three distinct phenotypic classes, one containing strains manifesting wild type susceptibility to both agents, another containing strains manifesting non-wild type susceptibility to both and a third containing strains manifesting wild type susceptibility with respect to TMP but non-wild type with respect to SFM. Analysis demonstrated the inability of SFT25 discs to generate data that allowed the separate identification of strains that were fully susceptible to both TMP and SFM from those that were fully susceptible to TMP but were not fully susceptible to SFM.It is recommended that, in investigation of the susceptibility to potentiated sulphonamides of isolates from diseased fish, separate discs, containing the individual components of the mixture, should be employed.

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“…Both EUCAST and the CLSI issued breakpoint guidelines in 2011. These take into account certain mechanisms of resistance, wild-type population distributions and pharmacokinetic/pharmacodynamics (PK/PD) modelling [5,6]. A detailed discussion of the differences between the EUCAST and CLSI breakpoints is beyond the scope of this review but should be considered when comparing and defining multidrug resistance and extensive drug resistance.…”

Section: Introductionmentioning

confidence: 99%