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.
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.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
TREATMENT
Masking
NONE
Enrollment
20
Patients will received cefepime administered per standard-of-care as a 30 min intravenous infusion. Dosing will be based on local guidelines (the Sanford guide to antimicrobial therapy 2012-2013) using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine formula to estimate glomerular filtration rate (GFR).
Blood will be sampled immediately prior to dose administration (time = 0 at the start of the 30 min infusion), at 0.5, 1, 3, 5 hours post-start of infusion and just before the subsequent dose. From day two onwards, samples will be taken at the end of the infusion and just before the next dose. For the quantification of cefepime, a validated solid phase extraction-liquid chromatography electrospray-tandem mass spectrometry method will be used.
Median absolute predictive error (MdAPE) of population PK model without covariates
Time frame: Evaluation during a maximum follow-up period of 5 days
Median absolute predictive error (MdAPE) of population PK model with different renal markers incorporated
Time frame: Evaluation during a maximum follow-up period of 5 days
The estimated probability of target attianment (%) for the different categories of the Sanford guide
Time frame: Based on data from a maximum follow-up period of 5 days
The estimated probability of toxic levels (%) for the different categories of the Sanford guide
Time frame: Based on data from a maximum follow-up period of 5 days
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Timed urine collections were taken during one dosing interval (8 hours in a three times daily regimen) every day.
Creatinine (modified Jaffe method) and urea in serum will be determined using an Architect c16000 analyzer (Abbott, Chicago, IL, USA). Cystatin C will be determined using a particle-enhanced immunonephelometric assay (N Latex Cystatin C, Siemens Healthcare Diagnostics, Marburg, Germany) by use of a BN II nephelometer (Siemens Healthcare Diagnostics). This assay has a calibration traceable to the first certified reference material for cystatin C in human serum (ERM-DA471/IFCC). Kidney injury molecule-1 (KIM-1) in urine and uromodulin in serum will be determined using commercially available ELISA assays: Quantikine ELISA Human TIM-1/KIM-1/HAVCR (R\&D Systems, Minneapolis, MN, USA) and Uromodulin ELISA (Euroimmun, Luebeck, Germany), respectively.
The cefepime concentration versus time data will be fitted using the FOCE-I estimation algorithm in NONMEM® (Version 7.3; GloboMax LLC, Hanover, MD, USA). R® (R foundation for statistical computing, Vienna, Austria) will be used to graphically assess the model's goodness-of-fit and to evaluate the model's predictive capabilities. As a measure of prediction error, the absolute prediction error (APE) will be used. In short, the measured cefepime concentrations for each individual i at time point j were compared against the population predicted cefepime concentrations, i.e. the predictions for each individual without taking into account the between-subject variability (PRED in NONMEM). The distribution of APEs will be summarized by the median and 90% percentile.
Renal function will be assessed by four serum based kidney markers (serum creatinine, cystatin C, urea and uromodulin) and two urinary markers (measured creatinine clearance (CrCl) and KIM-1, both on timed urine collections). Serum creatinine and cystatin C will also be used to calculate the eGFR based on CKD-EPI formulas.
Based on the final covariate model, a Monte Carlo-based simulation study will be performed to evaluate the Sanford dose recommendations for ICU patients.