Evaluation of Tobramycin Exposure Predictions in Three Bayesian Forecasting Programmes Compared with Current Clinical Practice in Children and Adults with Cystic Fibrosis

Burgard, Marc; Sandaradura, Indy; Hal, Sebastiaan J. van; Stacey, Sonya; Hennig, Stefanie

doi:10.1007/s40262-017-0610-9

Cited by 18 publications

(26 citation statements)

References 28 publications

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“…51 Software is readily available to implement the Bayesian approach at the patient's bedside, 51,53,54 and guidance for adopting this approach for the dosing of gentamicin and tobramycin has been published. 40,55,56 The Bayesian software requires only one or two serum concentrations to accurately calculate AUC, can support innovative dosing regimens, does not require waiting until steady state is reached to obtain the concentration sample, and can model covariates such as creatinine clearance that affect drug PK. 50,51 Recent studies have provided support for the AUC-guided, Bayesian approach to dosing for vancomycin.…”

Section: Therapeutic Drug Management For Toxicitymentioning

confidence: 99%

Reappraisal of Contemporary Pharmacokinetic and Pharmacodynamic Principles for Informing Aminoglycoside Dosing

2018

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Therapeutic drug management is regularly performed for aminoglycosides in an effort to maximize their effectiveness and safety. The ratio of maximum plasma drug concentration to minimum inhibitory concentration (Cmax/MIC) has long been regarded as the primary pharmacokinetic/pharmacodynamic (PK/PD) index of clinical efficacy for aminoglycosides due to their concentration‐dependent killing. In this review, however, we discuss why the area under the plasma concentration–time curve (AUC)/MIC ratio may be a more reliable indicator of bacterial killing and clinical efficacy for these agents. The definitive AUC/MIC efficacy targets for aminoglycosides are less clear, unlike those that exist for fluoroquinolones. Evaluation of available literature suggests that an AUC/MIC ratio of 30–50 for aminoglycoside therapy may provide optimal outcomes when targeting non–critically ill immunocompetent patients with low–bacterial burden gram‐negative infections such as urinary tract infections or in patients receiving additional gram‐negative therapy with good source control. However, an AUC/MIC target of 80–100 may be more prudent when treating patients with aminoglycoside monotherapy or in critically ill patients with high–bacterial burden infections, such as nosocomial pneumonia. Reappraisal of current antimicrobial susceptibility breakpoints for aminoglycosides against gram‐negative bacteria may also be necessary to achieve these AUC/MIC targets and ensure that current empiric doses are not grossly suboptimal in critically ill patients. Although it has been historically difficult to calculate AUCs in clinical practice, equation‐based and Bayesian approaches now can be used to estimate the AUC in clinical practice, with limited PK sampling. Additional research is needed to better define optimal AUC/MIC targets for efficacy, especially when drugs are used in combination, as well as PK/PD targets associated with suppression of resistance. It is also important to determine if AUC can predict nephrotoxicity of these agents or whether trough concentrations should be used instead.

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Section: Therapeutic Drug Management For Toxicitymentioning

confidence: 99%

Reappraisal of Contemporary Pharmacokinetic and Pharmacodynamic Principles for Informing Aminoglycoside Dosing

2018

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“…Finally, and as expected, the amount of information available should be considered when comparing a conventional approach with model‐based TDM, since more occasions and richer data are usually linked to better predictions of doses, given that the Bayesian prior model is not biased. Our results obtained using NONMEM are expected to be comparable across TDM software tools, provided that Bayesian maximum a posteriori estimation is used and uncertainty is handled in a similar way …”

Section: Discussionmentioning

confidence: 70%

Handling interoccasion variability in model‐based dose individualization using therapeutic drug monitoring data

Abrantes

Jönsson

Karlsson

et al. 2019

Brit J Clinical Pharma

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Aims: This study aims to assess approaches to handle interoccasion variability (IOV) in a model-based therapeutic drug monitoring (TDM) context, using a population pharmacokinetic model of coagulation factor VIII as example.Methods: We assessed 5 model-based TDM approaches: empirical Bayes estimates (EBEs) from a model including IOV, with individualized doses calculated based on individual parameters either (i) including or (ii) excluding variability related to IOV;and EBEs from a model excluding IOV by (iii) setting IOV to zero, (iv) summing variances of interindividual variability (IIV) and IOV into a single IIV term, or (v) reestimating the model without IOV. The impact of varying IOV magnitudes (0-50%) and number of occasions/observations was explored. The approaches were compared with conventional weight-based dosing. Predictive performance was assessed with the prediction error percentiles.Results: When IOV was lower than IIV, the accuracy was good for all approaches (50 th percentile of the prediction error [P50] <7.4%), but the precision varied substantially between IOV magnitudes (P97.5 61-528%). Approach (ii) was the most precise forecasting method across a wide range of scenarios, particularly in case of sparse sampling or high magnitudes of IOV. Weight-based dosing led to less precise predictions than the model-based TDM approaches in most scenarios.Conclusions: Based on the studied scenarios and theoretical expectations, the best approach to handle IOV in model-based dose individualization is to include IOV in the generation of the EBEs but exclude the portion of unexplained variability related to IOV in the individual parameters used to calculate the future dose.

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“…We examined retrospectively examined a BF approach to estimating tobramycin AUC 24 in our patients. The framework and potential clinical utility of a BF approach to guide tobramycin dose individualization in patients with CF has been well‐described 4,14,25‐27 . BF approaches have been shown to be more accurate and precise compared to LLR methods in estimating tobramycin AUC 24 14,26 .…”

Section: Discussionmentioning

confidence: 99%

Area under the curve achievement of once daily tobramycin in children with cystic fibrosis during clinical care

Brockmeyer

Wise

Burgener

et al. 2020

Pediatric Pulmonology

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Background The area under the concentration‐time curve over 24 hours (AUC24) is frequently utilized to monitor tobramycin exposure in children with cystic fibrosis (CF). An understanding of exposure target achievement during clinical implementation of an AUC24 based approach in children is limited. Methods A retrospective chart review was performed in children with CF treated with once daily tobramycin and drug concentration monitoring at a pediatric CF center. During clinical care AUC24 was estimated using a traditional log‐linear regression approach (LLR). AUC24 was also estimated retrospectively using a pharmacokinetic model‐based Bayesian forecasting approach (BF). AUC24 achievement after both approaches were compared. Results In 77 treatment courses (mean age, 12.7 ± 5.0 years), a target AUC24 100 to 125 mg h/L was achieved after starting dose in 21 (27%) and after initial dose adjustment in 35 (45%). In the first 7 days of treatment, 24 (32%) required ≥3 dose adjustments, and the mean number of drug concentrations measured was 7.1 ± 3.2. Examination of a BF approach demonstrated adequate prediction of measured tobramycin concentrations (median bias −2.1% [95% CI −3.1 to −1.4]; median precision 7.6% [95% CI, 7.1%‐8.2%]). AUC24 estimates utilizing the BF approach were higher than the LLR approach with a mean difference of 6.4 mg h/L (95% CI, 4.8 to 8.0 mg h/L). Conclusions Achievement of a narrow AUC24 target is challenging during clinical care, and dose individualization is needed in most children with CF. Implementing a BF approach for estimating AUC24 in children with CF is supported.

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Evaluation of Tobramycin Exposure Predictions in Three Bayesian Forecasting Programmes Compared with Current Clinical Practice in Children and Adults with Cystic Fibrosis

Abstract: On average, the predictions made by the BF programmes were similar, however substantial individual differences were observed for some patients. This suggests the need for detailed investigations of true tobramycin exposure.

Cited by 18 publications

References 28 publications

Reappraisal of Contemporary Pharmacokinetic and Pharmacodynamic Principles for Informing Aminoglycoside Dosing

Reappraisal of Contemporary Pharmacokinetic and Pharmacodynamic Principles for Informing Aminoglycoside Dosing

Handling interoccasion variability in model‐based dose individualization using therapeutic drug monitoring data

Area under the curve achievement of once daily tobramycin in children with cystic fibrosis during clinical care

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