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Development of Vancomycin Dose Individualization Strategy by Bayesian Prediction in Patients Receiving Continuous Renal Replacement Therapy

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Abstract

Purpose

Vancomycin (VCM) concentration is often out of therapeutic range (10–20 μg/ml) in patients receiving continuous renal replacement therapy (CRRT). The purposes of this study were to develop a practical VCM population pharmacokinetic (PPK) model and to evaluate the potential of Bayesian prediction-based therapeutic drug monitoring (Bayes-TDM) in VCM dose individualization for patients receiving CRRT.

Methods

We developed a VCM PPK model using 80 therapeutic concentrations in 17 patients receiving CRRT. Bayes-TDM with the VCM PPK model was evaluated in 23 patients after PPK modeling.

Results

We identified the covariates reduced urine output (RUO, <0.5 ml/kg/h) and effluent flow rate of CRRT for the VCM PPK model. The mean VCM non CRRT clearance (CLnonCRRT) was 2.12 l/h. RUO lowered CLnonCRRT to 0.34 l/h. The volume of distribution was 91.3 l/70 kg. The target concentration attainment rate by Bayes-TDM was higher (87.0%) than that by the PPK modeling period (53.8%, P = 0.046). The variance of the second measured concentrations by the Bayes-TDM was lower (11.5, standard deviation: 3.4 μg/ml) than that by the PPK modeling period (50.5, standard deviation: 7.1 μg/ml, P = 0.003).

Conclusions

Bayes-TDM could be a useful tool for VCM dose individualization in patients receiving CRRT.

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Abbreviations

95% CI:

95% Confidence interval

AKI:

Acute kidney injury

AUC:

Area under concentration curve

AUC0–24/MIC:

Area under concentration curve divided by minimum inhibitory concentration

Bayes-TDM:

Bayesian prediction based therapeutic drug monitoring

CLCRRT :

Clearance by continuous renal replacement therapy

CLnonCRRT :

Clearance by non continuous renal replacement therapy

COV:

Covariate

CRRT:

Continuous renal replacement therapy

CWRES:

Conditional weighted residuals

IIV:

Inter-individual variability

KDIGO:

Kidney disease improving global outcomes

MIC:

Minimum inhibitory concentration

MRSA:

Methicillin-resistant Staphylococcus aureus

NONMEM:

Non linear mixed effect modeling

OFV:

Objective function value

pcVPC:

Prediction corrected visual predictive check

PPK:

Population pharmacokinetic(s)

RMSPE:

Root mean square percentage error

RUO:

Patients with RUO

RUO-:

Patients without RUO

RUO:

Reduced urine output

SD:

Standard deviation

SOFA:

Sequential organ failure assessment

TA:

Target concentration range attainment rate

TDM:

Therapeutic drug monitoring

VBA:

Visual basic for applications

VCM:

Vancomycin

Vdss:

Volume of distribution including central and peripheral volumes

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Authors and Affiliations

  1. Department of Pharmacy, Kumamoto University Hospital, 1-1-1, Honjo, Chuo-ku, Kumamoto city, Kumamoto, Japan

    Kazutaka Oda, Hirofumi Jono, Naomi Tanoue & Hideyuki Saito

  2. Department of Clinical Pharmaceutical Sciences, Graduate School of Pharmaceutical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto city, Kumamoto, Japan

    Hirofumi Jono & Hideyuki Saito

  3. Department of Intensive Care Medicine, Kumamoto University Hospital, 1-1-1, Honjo, Chuo-ku, Kumamoto city, Kumamoto, Japan

    Hidenobu Kamohara

  4. Department of Hemodialysis and Apheresis, Kumamoto University Hospital, 1-1-1, Honjo, Chuo-ku, Kumamoto city, Kumamoto, Japan

    Kazuhiko Nishi

Authors
  1. Kazutaka Oda
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  2. Hirofumi Jono
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Correspondence to Kazutaka Oda.

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Oda, K., Jono, H., Kamohara, H. et al. Development of Vancomycin Dose Individualization Strategy by Bayesian Prediction in Patients Receiving Continuous Renal Replacement Therapy. Pharm Res 37, 108 (2020). https://doi.org/10.1007/s11095-020-02820-0

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