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Several population pharmacokinetic (PK) models for cefepime in critically ill patients have been described, all indicating that variability in renal clearance is the main determinant of observed variability in exposure. The main objective of this study was hence to determine which renal marker best predicts cefepime clearance.
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Timely and appropriate antibiotic therapy, sufficient to guarantee adequate antibiotic concentrations in blood and tissues, is one of the most important interventions in critically ill patients with infections.1,2 Cefepime is a fourth generation cephalosporin with broad spectrum activity against Gram-negative bacteria that is used as empirical and directed therapy for severe infections like sepsis and pneumonia. Nevertheless, administration of adequate antibiotic doses is a real challenge in critically ill patients because the pharmacokinetics (PK) of these drugs may be influenced by the complex pathophysiological changes that occur during sepsis.2 Recent reviews described the enormous pharmacokinetic variability of beta-lactam antibiotics in critically ill patients.3,4 Therefore, strategies for dose individualization are explored in an attempt to better control a patient's exposure to the antibiotic, thereby potentially improving the prognosis of critically ill patients with infection. On the one hand, several smaller studies have already shown that better outcomes for critically ill patients can be expected with higher drug exposures, at least for less severely ill patients.5,6 This conclusion was supported by the DALI study, a large multi-center prospective study.7 On the other hand, it was shown that insufficient antibiotic exposure may lead to the development of antibiotic resistance.8 This link was initially shown with inappropriately low quinolone exposures, but more recently with other classes of antibiotics including beta-lactams.9,10 In addition to ensuring that plasma levels are high enough for optimal antimicrobial activity and suppressing emergence of resistance, individualized dosing might offer a perspective to prevent potential side-effects originating from toxic plasma levels. This seems particularly relevant for cefepime, a beta-lactam antibiotic, as it was shown that cefepime is an underappreciated cause of neurotoxicity, especially in intensive care unit (ICU) patients,11,12 patients with impaired renal function,13-16 and patients with brain disorders.17 Population pharmacokinetic models provide a quantitative view of the effect of particular individual factors on the plasma concentration time profile of a drug. Population PK models thereby help to establish individual treatment regimen in patients, depending on the specific patient covariates that were included in the model. As cefepime is a hydrophilic compound, drug elimination is mainly determined by renal clearance and to a lesser extent by non-renal clearance. Therefore, renal markers have been explored as the main determinant to predict cefepime variability in population PK models.18-24 However, none of the published PK models was developed using both plasma and urinary data, though having access to both matrices may be an advantage to identify clinically relevant covariates. Moreover, only creatinine-based markers were used as covariates and, up to now, it was unclear whether the newer markers to assess renal function (e.g. cystatine C, uromodulin and Kidney Injury Moleclure-1 (KIM-1)) are more accurate to predict cefepime clearance.
In this study, a clinical trial was conducted to develop a population PK model for cefepime in critically ill patients assessing renal and non-renal clearance separately, based on both plasma and urinary cefepime concentrations. This model then served as a tool to compare the adequacy of six different renal markers as predictors for renal cefepime clearance. After integrating the most adequate predictor into the PK model, the final model was used to evaluate current dose recommendations for cefepime.
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