A new semi-parametric mixture model for interval censored data, with applications in the field of antimicrobial resistance

Jaspers, Stijn; Aerts, Marc; Verbeke, Geert; Belœil, Pierre‐Alexandre

doi:10.1016/j.csda.2013.01.024

Cited by 16 publications

(36 citation statements)

References 22 publications

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“…More specifically, the assumption of having a well-separated wild-type and non-wild-type component could be relaxed through the consideration of the entire mixture in (1). Accounting for the non-wild-type component in a non-parametric way, Jaspers et al [14] provide an alternative estimation procedure in which the estimator developed in this paper is used to construct a semi-parametric mixture model that is able to estimate the MIC distribution on the full continuous scale. We can use this mixture to determine the prevalence of non-wild-type isolates in a more accurate way.…”

Section: Discussionmentioning

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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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: Discussionmentioning

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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“…Esta metodología fue dirigida inicialmente a la determinación de la actividad de los antibióticos pero ha sido modificado para determinar la actividad de los AE; adaptándose para determinar la actividad antimicrobiana de los AE y los extractos de plantas [30,31]. la CMI se define como la menor concentración del extracto que produce el 90% de reducción en el crecimiento de las colonias.…”

Section: Resultsunclassified

“…los resultados de la curva de letalidad se observan en la figura 1; en 256 µg/ml no se da ninguna inhibición, lo que si se da en 512 µg/ml y la eliminación del crecimiento se observa en 2048 µg/ml a las 24 horas. Estos resultados contrastan con las pruebas hechas para CMB del S. aureus que mostro el punto de corte en 4096 µg/ml; explicándose quizás por una serie de factores que influyen en la estimación de la actividad antimicrobiana de los AE, entre los que se encuentran la temperatura, el pH, el potencial óxido- reducción y la actividad de agua, según Hernández et al, [31]; el método utilizado, tipo y volumen del medio, concentración y edad del inoculo, el tipo de cepa del microorganismo en estudio, la temperatura, el tiempo, la atmósfera de incubación y el solvente o agente dispersante.…”

Section: Resultsunclassified

Efecto Antimicrobiano Del Clavo Y La Canela Sobre Patógenos

Puche

Villadiego

Correa

2017

BSAA

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“…In the absence of a golden standard, we decided to compare between three existing methods. The adjusted CLM approach is compared to the back-fitting algorithm and to the two-stage penalized mixture (PM) approach presented in Jaspers et al (2014bJaspers et al ( , 2016, respectively.…”

Section: Simulation Studymentioning

confidence: 99%

“…Therefore, a nonparametric second component seems more appealing. Jaspers et al (2014b) provide a two-stage semiparametric mixture model to estimate the mixture density of interest. The first stage determines the estimates of the first component using the MBM.…”

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confidence: 99%

A Bayesian approach to the semiparametric estimation of a minimum inhibitory concentration distribution

Jaspers¹,

Lambert²,

Aerts³

2016

Ann. Appl. Stat.

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Bacteria that have developed a reduced susceptibility against antimicrobials pose a major threat to public health. Hence, monitoring their distribution in the general population is of major importance. This monitoring is performed based on minimum inhibitory concentration (MIC) values, which are collected through dilution experiments. We present a semiparametric mixture model to estimate the MIC density on the full continuous scale. The wild-type first component is assumed to be of a parametric form, while the nonwild-type second component is modelled nonparametrically using Bayesian P-splines combined with the composite link model. A Metropolis within Gibbs strategy was used to draw a sample from the joint posterior. The newly developed method was applied to a specific bacterium-antibiotic combination, that is, Escherichia coli tested against ampicillin. After obtaining an estimate for the entire density, model-based classification can be performed to check whether or not an isolate belongs to the wild-type subpopulation. The performance of the new method, compared to two existing competitors, is assessed through a small simulation study.

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A new semi-parametric mixture model for interval censored data, with applications in the field of antimicrobial resistance

Cited by 16 publications

References 22 publications

Estimation of the wild‐type minimum inhibitory concentration value distribution

Estimation of the wild‐type minimum inhibitory concentration value distribution

Efecto Antimicrobiano Del Clavo Y La Canela Sobre Patógenos

A Bayesian approach to the semiparametric estimation of a minimum inhibitory concentration distribution

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