Development of a Population Pharmacokinetic Model of Vancomycin and its Application in Chinese Geriatric Patients with Pulmonary Infections

Population pharmacokinetics of antibacterial agents in the older population: a literature review

INTRODUCTION

Older individuals face an elevated risk of developing bacterial infections. The optimal use of antibacterial agents in this population is challenging because of age-related physiological alterations, changes in pharmacokinetics (PK) and pharmacodynamics (PD), and the presence of multiple underlying diseases. Therefore, population pharmacokinetics (PPK) studies are of great importance for optimizing individual treatments and prompt identification of potential risk factors.

AREA COVERED

Our search involved keywords such as 'elderly,' 'old people,' and 'geriatric,' combined with 'population pharmacokinetics' and 'antibacterial agents.' This comprehensive search yielded 11 categories encompassing 28 antibacterial drugs, including vancomycin, ceftriaxone, meropenem, and linezolid. Out of 127 studies identified, 26 (20.5%) were associated with vancomycin, 14 (11%) with meropenem, and 14 (11%) with piperacillin. Other antibacterial agents were administered less frequently.

EXPERT OPINION

PPK studies are invaluable for elucidating the characteristics and relevant factors affecting the PK of antibacterial agents in the older population. Further research is warranted to develop and validate PPK models for antibacterial agents in this vulnerable population.

Pharmacokinetics of Antibacterial Agents in the Elderly: The Body of Evidence

Infections are important factors contributing to the morbidity and mortality among elderly patients. High rates of consumption of antimicrobial agents by the elderly may result in increased risk of toxic reactions, deteriorating functions of various organs and systems and leading to the prolongation of hospital stay, admission to the intensive care unit, disability, and lethal outcome. Both safety and efficacy of antibiotics are determined by the values of their plasma concentrations, widely affected by physiologic and pathologic age-related changes specific for the elderly population. Drug absorption, distribution, metabolism, and excretion are altered in different extents depending on functional and morphological changes in the cardiovascular system, gastrointestinal tract, liver, and kidneys. Water and fat content, skeletal muscle mass, nutritional status, use of concomitant drugs are other determinants of pharmacokinetics changes observed in the elderly. The choice of a proper dosing regimen is essential to provide effective and safe antibiotic therapy in terms of attainment of certain pharmacodynamic targets. The objective of this review is to perform a structure of evidence on the age-related changes contributing to the alteration of pharmacokinetic parameters in the elderly.

Intraperitoneally Administered Vancomycin in Patients with Peritoneal Dialysis-Associated Peritonitis: Population Pharmacokinetics and Dosing Implications

Peritonitis is a limiting complication of peritoneal dialysis, which is treated by intraperitoneal administration of antibiotics. Various dosing strategies are recommended for intraperitoneally administered vancomycin, which leads to large differences in intraperitoneal vancomycin exposure. Based on data from therapeutic drug monitoring, we developed the first-ever population pharmacokinetic model for intraperitoneally administered vancomycin to evaluate intraperitoneal and plasma exposure after dosing schedules recommended by the International Society for Peritoneal Dialysis. According to our model, currently recommended dosing schedules lead to possible underdosing of a large proportion of patients. To prevent this, we suggest avoiding intermittent intraperitoneal vancomycin administration, and for the continuous dosing regimen, we suggest a loading dose of 20 mg/kg followed by maintenance doses of 50 mg/L in each dwell to improve the intraperitoneal exposure. Vancomycin plasma level measurement on the fifth day of treatment with subsequent dose adjustment would prevent it from reaching toxic levels in the few patients who are susceptible to overdose.

Pharmacokinetic equations versus Bayesian guided vancomycin monitoring: Pharmacokinetic model and model-informed precision dosing trial simulations

The recently released revised vancomycin consensus guideline endorsed area under the concentration‐time curve (AUC) guided monitoring. Means to AUC‐guided monitoring include pharmacokinetic (PK) equations and Bayesian software programs, with the latter approach being preferable. We aimed to evaluate the predictive performance of these two methods when monitoring using troughs or peaks and troughs at varying single or mixed dosing intervals (DIs), and evaluate the significance of satisfying underlying assumptions of steady‐state and model transferability. Methods included developing a vancomycin population PK model and conducting model‐informed precision dosing clinical trial simulations. A one‐compartment PK model with linear elimination, exponential between‐subject variability, and mixed (additive and proportional) residual error model resulted in the best model fit. Conducted simulations demonstrated that Bayesian‐guided AUC can, potentially, outperform that of equation‐based AUC predictions depending on the quality of model diagnostics and met assumptions. Ideally, Bayesian‐guided AUC predictive performance using a trough from the first DI was equivalent to that of PK equations using two measurements (peak and trough) from the fifth DI. Model transferability diagnostics can guide the selection of Bayesian priors but are not strong indicators of predictive performance. Mixed versus single fourth and/or fifth DI sampling seems indifferent. This study illustrated cases associated with the most reliable AUC predictions and showed that only proper Bayesian‐guided monitoring is always faster and more reliable than equations‐guided monitoring in pre‐steady‐state DIs in the absence of a loading dose. This supports rapid Bayesian monitoring using data as sparse and early as a trough at the first DI.

Dose Tailoring of Vancomycin Through Population Pharmacokinetic Modeling Among Surgical Patients in Pakistan

Background: Vancomycin is a narrow therapeutic agent, and it is necessary to optimize the dose to achieve safe therapeutic outcomes. The purpose of this study was to identify the significant covariates for vancomycin clearance and to optimize the dose among surgical patients in Pakistan. Methods: Plasma concentration data of 176 samples collected from 58 surgical patients treated with vancomycin were used in this study. A population pharmacokinetic model was developed on NONMEM^® using plasma concentration-time data. The effect of all available covariates was evaluated on the pharmacokinetic parameters of vancomycin by stepwise covariate modeling. The final model was evaluated using bootstrap, goodness-of-fit plots, and visual predictive checks. Results: The pharmacokinetics of vancomycin followed a one-compartment model with first-order elimination. The vancomycin clearance (CL) and volume of distribution (Vd) were 2.45 L/h and 22.6 l, respectively. Vancomycin CL was influenced by creatinine clearance (CRCL) and body weight of the patients; however, no covariate was significant for its effect on the volume of distribution. Dose tailoring was performed by simulating dosage regimens at a steady state based on the CRCL of the patients. The tailored doses were 400, 600, 800, and 1,000 mg for patients with a CRCL of 20, 60, 100, and 140 ml/min, respectively. Conclusion: Vancomycin CL is influenced by CRCL and body weight of the patient. This model can be helpful for the dose tailoring of vancomycin based on renal status in Pakistani patients.

Comparison of the Predictive Performance Between Cystatin C and Serum Creatinine by Vancomycin via a Population Pharmacokinetic Models: A Prospective Study in a Chinese Population

BACKGROUND

Most of the current published population pharmacokinetic (PopPK) models are based on serum creatinine, but we often encounter an underestimation of its concentration in our clinical work. Therefore, we established a cystatin C-based model of vancomycin.

OBJECTIVES

The purpose of this study was to externally verify the PopPK model of vancomycin based on the glomerular filtration rate (GFR) estimated by serum cystatin C in our previous study and to compare the prediction performance of cystatin C (Cys C) and serum creatinine (SCR)-based models.

METHODS

The external data set consists of adults receiving vancomycin treatment at The First Affiliated Hospital of Guangxi Medical University. We summarized and restored published models based on serum creatinine values from the literature and used our external data set for initial screening. Visual and external verifications were used to further select candidate models for comparison. The mean prediction error (ME), mean absolute error (MAE) and root mean squared error (RMSE) were the primary outcomes for the overall comparison. Group comparisons of patients with different glomerular filtration rates (GFRs), ages and body mass index (BMI) levels were obtained by the Bayesian method.

RESULTS

A total of 156 patients with 233 samples were collected as an external data set. Sixteen published models were summarized and restored. After screening, four candidate models suitable for the external data set were finally obtained for comparison. The cystatin C-based model has a smaller ME value in the overall comparison. In the group comparison, serum creatinine-based models were underestimated in the prediction for patient groups with age ≥ 60 years, abnormal BMI values and GFR < 90 ml/min/1.73 m², for which the cystatin C-based model could solve this problem.

CONCLUSION

After comparison, we suggest that cystatin C is a superior renal function marker to serum creatinine for vancomycin PopPK models.

Development and comparison of population pharmacokinetic models of vancomycin in neurosurgical patients based on two different renal function markers

WHAT IS KNOWN AND OBJECTIVES

Some previous studies have indicated that serum cystatin C (Cys C) is a better marker than serum creatinine (SCR) for assessing the glomerular filtering rate (GFR). However, in almost all population pharmacokinetic models of vancomycin, the GFR is usually estimated from SCR. Therefore, the aim of this study was to compare the GFR estimated from SCR (sGFR) with the GFR estimated from Cys C (cGFR) and investigate which one can describe the characteristics of vancomycin population pharmacokinetics better in Chinese neurosurgical adult patients.

METHODS

Patients from the Neurosurgery Department aged ≥18 years were enrolled retrospectively. Among these patients, the data from 222 patients were used to establish two population pharmacokinetic models based on sGFR and cGFR, separately. The data from another 95 patients were used for the external validation of these two models. Non-linear mixed-effect modelling (NONMEM) 7.4.3 was used for the population pharmacokinetic analysis.

RESULTS

We developed two one-compartment models with first-order absorption based on Cys C and SCR, separately. In the Cys C model, age, body weight and cGFR were significant covariates on the clearance rate (CL) of vancomycin (typical value, 6.4 L/hour). In the SCR model, age and sGFR were significant covariates on the CL (typical value, 6.46 L/hour). The external validation results showed that the predictive performance of the two models was similar.

WHAT IS NEW AND CONCLUSION

In this study, the predictive performance of two models was similar in neurosurgical patients. We did not find a significant improvement in the predictive performance of the model when GFR was estimated from Cys C.

Vancomycin Pharmacokinetics in Patients with Advanced Cancer Near End of Life

BACKGROUND AND OBJECTIVE

The effect of cancer cachexia on the pharmacokinetics of vancomycin remains unclear. We investigated whether the pharmacokinetics of vancomycin and the risk of kidney injury are altered with the development of cancer cachexia.

METHODS

A retrospective analysis was conducted using therapeutic drug monitoring data obtained from 86 cancer patients who received vancomycin intravenously for infection. The patients were classified into four groups according to the stage of cachexia defined by international consensus-non-cachexia (n = 26), pre-cachexia (n = 10), cachexia (n = 21) and refractory cachexia (n = 29). Vancomycin pharmacokinetics were analyzed by a traditional one-compartment model and Bayesian method using plasma concentrations measured in these patients. Renal function and pharmacokinetic parameters were compared between the non-cachexia patients (n = 26) and total cancer cachexia patients (n = 60).

RESULT

No significant difference in estimated glomerular filtration rate was observed between the non-cachexia and the total cancer cachexia patients. In contrast, systemic clearance of vancomycin was significantly lower in the total cancer cachexia patients compared with the non-cachexia patients when analyzed by the traditional one-compartment model [median (range)-49.7 (9.8‒98.7) vs 70.2 (12.5‒211.8) mL/min, p < 0.01] and by the Bayesian method [45.6 (12.5-84.7) vs 63.3 (12.2-102.5) mL/min, p < 0.05]. None of the non-cachexia patients developed kidney injury, whereas 15% (9 of 60 patients) of the total cancer cachexia patients developed kidney injuries (p = 0.052).

CONCLUSIONS

The present study revealed that cancer patients with cachexia may have reduced vancomycin clearance compared with those without cachexia. Cancer cachexia may be a risk factor of vancomycin-associated kidney injury, independent of renal function.