A Meta-Analysis on the Performance of Cystatin C- versus Creatinine-based eGFR Equations in Predicting Vancomycin Clearance

Utility of cystatin C and serum creatinine-based glomerular filtration rate equations in predicting vancomycin clearance: A population pharmacokinetics analysis in elderly Chinese patients

Renal function is an important factor affecting the pharmacokinetics of vancomycin. The renal function in elderly patients gradually decreases with age. An accurate estimated glomerular filtration rate (GFR) is essential in drug dosing. The study aimed to determine the most appropriate renal function estimation equations to describe vancomycin pharmacokinetics in elderly patients using population pharmacokinetic analysis. Data were obtained retrospectively from elderly patients aged ≥65 years who received vancomycin for infection from September 2016 to January 2022. Renal function was estimated using the Cockcroft-Gault equation (CG), Modification of Diet in Renal Disease equation (MDRD), three Chronic Kidney Disease Epidemiology Collaboration equations (CKD-EPIcys-scr , CKD-EPIscr , and CKD-EPIcys ) and two Berlin Initiative Study equations (BIS-1 and BIS-2). The CKD-EPIcys-scr and BIS-2 equations were based on cystatin C (Cys C) and serum creatinine (Scr). The others were based on Cys C or Scr. A nonlinear mixed effects model (NONMEM) was used to develop the population pharmacokinetic model. A total of 471 serum concentrations from 313 elderly patients were used to develop the population pharmacokinetic model. Weight and GFR were identified as significant covariates affecting the pharmacokinetics of vancomycin. Cys C and Scr-based GFR (CKD-EPIcys-scr and BIS-2) yielded significant improvement performance compared with the other equations in model building. The interindividual variability of CL was reduced from 49.4% to 23.6% and 49.4% to 23.7% in CKD-EPIcys-scr and BIS-2 based models, respectively. However, greater interindividual variabilities of CL (from 26.6% to 29.0%) were represented in the other five models which were based on either Cys C or Scr. The GFR estimated by EPIcys-scr and BIS-2 equations and vancomycin CL exhibited a good correlation (r = 0.834 and 0.833). In the external validation with 124 serum concentrations, the predictive performances of the CKD-EPIcys-scr and BIS-2 based models (the mean relative prediction errors were less than 1%, the mean relative absolute prediction errors were about 23%) were also superior to the other five models (the mean relative prediction errors were about 2%, the mean relative absolute prediction errors were greater than 25%) which are based on either Cys C or Scr. In this study, we determined that the equation used to estimate GFR can affect the population pharmacokinetic model fitting result. Population pharmacokinetics model with CKD-EPIcys-scr or BIS-2 can be used to optimize vancomycin dosage in elderly Chinese patients.

The Significance of Bayesian Pharmacokinetics in Dosing for Critically Ill Patients: A Primer for Clinicians Using Vancomycin as an Example

Antibiotic use is becoming increasingly challenging with the emergence of multidrug-resistant organisms. Pharmacokinetic (PK) alterations result from complex pathophysiologic changes in some patient populations, particularly those with critical illness. Therefore, antibiotic dose individualization in such populations is warranted. Recently, there have been advances in dose optimization strategies to improve the utilization of existing antibiotics. Bayesian-based dosing is one of the novel approaches that could help clinicians achieve target concentrations in a greater percentage of their patients earlier during therapy. This review summarizes the advantages and disadvantages of current approaches to antibiotic dosing, with a focus on critically ill patients, and discusses the use of Bayesian methods to optimize vancomycin dosing. The Bayesian method of antibiotic dosing was developed to provide more precise predictions of drug concentrations and target achievement early in therapy. It has benefits such as the incorporation of personalized PK/PD parameters, improved predictive abilities, and improved patient outcomes. Recent vancomycin dosing guidelines emphasize the importance of using the Bayesian method. The Bayesian method is able to achieve appropriate antibiotic dosing prior to the patient reaching the steady state, allowing the patient to receive the right drug at the right dose earlier in therapy.

Prediction Accuracy of Area under the Concentration-Time Curve of Vancomycin by Bayesian Approach Using Creatinine-Based Equations of Estimated Kidney Function in Bedridden Elderly Japanese Patients

An administration plan for vancomycin (VCM) in bedridden elderly patients has not been established. This retrospective study aimed to evaluate the prediction accuracy of the area under the concentration-time curve (AUC) of VCM by the Bayesian approach using creatinine-based equations of estimated kidney function in such patients. Kidney function was estimated using the Japanese equation of estimated glomerular filtration rate (eGFR) and the Cockcroft-Gault equation of estimated creatinine clearance (eCCr). eCCr (serum creatinine (SCr) + 0.2) was calculated by substituting the SCr level +0.2 mg/dL into the Cockcroft-Gault equation. For eGFR/0.789, eGFR, eCCr, and eCCr (SCr + 0.2), the AUC values were calculated by the Bayesian approach using the therapeutic drug monitoring (TDM) software, BMs-Pod (ver 8.06) and denoted as AUC_eGFR/0.789, AUC_eGFR, AUC_eCCr, and AUC_{eCCr (SCr + 0.2)} respectively. The reference AUC (AUC_REF) was calculated by applying VCM's peak and trough steady-state concentrations to first-order pharmacokinetic equations. The medians (range) of AUC_eGFR/0.789/AUC_REF, AUC_eGFR/AUC_REF, AUC_eCCr/AUC_REF, and AUC_{eCCr (SCr + 0.2)}/AUC_REF were 0.88 (0.74-0.93), 0.90 (0.79-1.04), 0.92 (0.81-1.07), and 1.00 (0.88-1.11), respectively. Moreover, the percentage of patients within 10% of the AUC_REF, defined as |Bayesian-estimated AUC - AUC_REF| < AUC_REF × 0.1, was the highest (86%) in AUC_{eCCr (SCr + 0.2)}. These results suggest that the Bayesian approach using eCCr (SCr + 0.2) has the highest prediction accuracy for the AUC_REF in bedridden elderly patients. Although further studies are required with more accurate determination methods of the CCr and AUC, our findings highlight the potential of eCCr (SCr + 0.2) for estimating VCM's AUC by the Bayesian approach in such patients.