First-Dose Vancomycin Pharmacokinetics Versus Empiric Dosing on Area-Under-the-Curve Target Attainment in Critically Ill Patients

Characterizing Day 1 Area Under the Curve Following Vancomycin Loading Dose Administration in Adult Hospitalized Patients Using Non-Trapezoidal Linear Pharmacokinetic Equations: A Retrospective Observational Study

INTRODUCTION

Methicillin-resistant Staphylococcus aureus (MRSA) infections are a serious threat to public health. Vancomycin (VAN) remains the primary treatment for these infections, and achieving the recommended area under the curve (AUC) target has been linked to improved clinical outcomes. The current VAN therapeutic monitoring guidelines recommend a loading dose (LD) of 20-35 mg/kg to rapidly attain targeted VAN exposures within 24 h of therapy. However, there is a paucity of data describing the impact of VAN LD on day 1 area under the curve (AUC0-24). This study aims to employ pharmacokinetic (PK) equations to calculate and describe the AUC0-24 following a VAN LD of 20 mg/kg.

METHODS

This was a retrospective study of adult patients who were loaded with VAN 20 mg/kg, received ≥ 48 h of treatment, and had two consecutive serum VAN levels collected within 24 h. Linear, non-trapezoidal PK equations and two post-infusion VAN levels were used to calculate AUC0-24. Therapeutic AUC0-24 was defined as 400-600 mg/l*h.

RESULTS

Among 123 included patients, the median age was 46 years (IQR 36, 62), 54% (67/123) of the patients had a body mass index (BMI) ≥ 30 kg/m2 and 27% (33/123) were admitted to the intensive care unit (ICU). Following a LD of 20 mg/kg, 50% (61/123) of the patients met the therapeutic AUC0-24, while 22% (27/123) of the patients were subtherapeutic, and 28% (35/123) were supratherapeutic. Compared with patients who achieved therapeutic AUC0-24, patients with subtherapeutic AUC0-24 were more likely to be younger (44 vs. 37 years old) and have a BMI ≥ 30 kg/m2 (67 vs. 52%). In contrast, patients with supratherapeutic AUC0-24 were more likely to be older (64 vs. 44 years old) and to have chronic kidney disease diagnosis (23 vs. 7%) when compared to patients who achieved a therapeutic AUC0-24. CONCLUSIONS: Only 50% of patients achieve the target AUC0-24 following a VAN 20 mg/kg LD, with younger, heavier patients underexposed and older patients with renal impairment overexposed, suggesting that different dosing strategies are needed for these populations.

Three methods to optimise polymyxin B dosing using estimated AUC after first dose: validation with the data generated by Monte Carlo simulation

To achieve the AUC-guided dosing, we proposed three methods to estimate polymyxin B AUC across 24 h at steady state (AUCSS,24h) using limited concentrations after its first dose.Monte Carlo simulation based on a well-established population PK model was performed to generate the PK profiles of 1000 patients with normal or abnormal renal function. Polymyxin B AUCSS,24h was estimated for each subject using three methods (two-point PK approach, three-point PK approach, and four-point PK approach) based on limited concentration data in its first dose and compared with the actual AUC at steady state calculated using the linear-trapezoidal formula.In patients with normal renal function, the mean bias of two-point PK approach, three-point PK approach, and four-point PK approach was -8.73%, 1.37%, and -0.48%, respectively. The corresponding value was -11.15%, 1.99%, and -0.28% in patients with renal impairment, respectively. The largest mean bias of two-point PK approach, three-point PK approach, and four-point PK approach was -12.63%, -6.47%, and -0.54% when the sampling time shifted.The Excel calculators designed based on the three methods can be potentially used to optimise the dosing regimen of polymyxin B in the clinic.

Is It Still Beneficial to Monitor the Trough Concentration of Vancomycin? A Quantitative Meta-Analysis of Nephrotoxicity and Efficacy

This study conducted a quantitative meta-analysis to investigate the association of vancomycin indicators, particularly area under the curve over 24 h (AUC24) and trough concentrations (Ctrough), and their relationship with both nephrotoxicity and efficacy. Literature research was performed in PubMed and Web of Science on vancomycin nephrotoxicity and efficacy in adult inpatients. Vancomycin Ctrough, AUC24, AUC24/minimum inhibitory concentration (MIC), nephrotoxicity evaluation and treatment outcomes were extracted. Logistic regression and Emax models were conducted, stratified by evaluation criterion for nephrotoxicity and primary outcomes for efficacy. Among 100 publications on nephrotoxicity, 29 focused on AUC24 and 97 on Ctrough, while of 74 publications on efficacy, 27 reported AUC24/MIC and 68 reported Ctrough. The logistic regression analysis indicated a significant association between nephrotoxicity and vancomycin Ctrough (odds ratio = 2.193; 95% CI 1.582-3.442, p < 0.001). The receiver operating characteristic curve had an area of 0.90, with a cut-off point of 14.55 mg/L. Additionally, 92.3% of the groups with a mean AUC24 within 400-600 mg·h/L showed a mean Ctrough of 10-20 mg/L. However, a subtle, non-statistically significant association was observed between the AUC24 and nephrotoxicity, as well as between AUC24/MIC and Ctrough concerning treatment outcomes. Our findings suggest that monitoring vancomycin Ctrough remains a beneficial and valuable approach to proactively identifying patients at risk of nephrotoxicity, particularly when Ctrough exceeds 15 mg/L. Ctrough can serve as a surrogate for AUC24 to some extent. However, no definitive cut-off values were identified for AUC24 concerning nephrotoxicity or for Ctrough and AUC24/MIC regarding efficacy.

Performance of Bayesian Area Under the Concentration-Time Curve-Based Pharmacokinetic Dosing Based on a One-Compartment Model and Trough-Only Monitoring for Vancomycin

A novel Bayesian method was developed to interpret serum vancomycin concentrations (SVCs) following the administration of one or more vancomycin doses with potential varying doses and intervals based on superposition principles. The method was evaluated using retrospective data from 442 subjects from three hospitals. The patients were required to receive vancomycin for more than 3 days, have stable renal function (fluctuation in serum creatinine of ≤0.3 mg/dL), and have at least 2 trough concentrations reported. Pharmacokinetic parameters were predicted using the first SVC, and the fitted parameters were then used to predict subsequent SVCs. Using only covariate-adjusted population prior estimates, the first two SVC prediction errors were 47.3 to 54.7% for the scaled mean absolute error (sMAE) and 62.1 to 67.8% for the scaled root mean squared error (sRMSE). "Scaled" refers to the division of the MAE or RMSE by the mean value. The Bayesian method had minimal errors for the first SVC (by design), and for the second SVC, the sMAE was 8.95%, and the sRMSE was 36.5%. The predictive performance of the Bayesian method did degrade with subsequent SVCs, which we attributed to time-dependent pharmacokinetics. The 24-h area under the concentration-time curve (AUC) was determined from simulated concentrations before and after the first SVC was reported. Prior to the first SVC, 170 (38.4%) patients had a 24-h AUC of <400 mg · h/L, 186 (42.1%) had a 24-h AUC within the target range, and 86 (19.5%) had a 24-h AUC of >600 mg · h/L. After the first SVC was reported, 322 (72.9%) had a 24-h AUC within the target range, 68 (15.4%) had low values, and 52 (11.8%) had high values based on the model simulation. Target attainments were 38% before the first SVC and 73% after the first SVC. The hospitals had no policies or procedures in place for targeting 24-h AUCs, although the trough target was typically 13 to 17 mg/L. Our data provide evidence of time-dependent pharmacokinetics, which will require regular therapeutic drug monitoring regardless of the method used to interpret SVCs.

Two Innovative Approaches to Optimize Vancomycin Dosing Using Estimated AUC after First Dose: Validation Using Data Generated from Population PK Model Coupled with Monte-Carlo Simulation and Comparison with the First-Order PK Equation Approach

The revised consensus guidelines for optimizing vancomycin doses suggest that maintaining the area under the concentration-time curve to minimal inhibitory concentration ratio (AUC/MIC) of 400–600 mg·h/L is the target pharmacokinetic/pharmacodynamic (PK/PD) index for efficacy. AUC-guided dosing approach uses a first-order pharmacokinetics (PK) equation to estimate AUC using two samples obtained at steady state and one-compartment model, which can cause inaccurate AUC estimation and fail to achieve the effective PK/PD target early in therapy (days 1 and 2). To achieve an efficacy target from the third or fourth dose, two innovative approaches (Method 1 and Method 2) to estimate vancomycin AUC at steady state (AUCSS) using two-compartment model and three or four levels after the first dose are proposed. The feasibility of the proposed methods was evaluated and compared with another published dosing algorithm (Method 3), which uses two samples and a one-compartment approach. Monte Carlo simulation was performed using a well-established population PK model, and concentration-time profiles for virtual patients with various degrees of renal function were generated, with 1000 subjects per group. AUC extrapolated to infinity (AUC0–∞) after the first dose was estimated using the three methods, whereas reference AUC (AUCref) was calculated using the linear-trapezoidal method at steady state after repeated doses. The ratio of AUC0–∞: AUCref and % bias were selected as the indicators to evaluate the accuracy of three methods. Sensitivity analysis was performed to examine the influence of change in each sampling time on the estimated AUC0–∞ using the two proposed approaches. For simulated patients with various creatinine clearance, the mean of AUC0–∞: AUCref obtained from Method 1, Method 2 and Method 3 ranged between 0.98 to 1, 0.96 to 0.99, and 0.44 to 0.69, respectively. The mean bias observed with the three methods was −0.10% to −2.09%, −1.30% to −3.59% and −30.75% to −55.53%, respectively. The largest mean bias observed by changing sampling time while using Method 1 and Method 2 were −4.30% and −10.50%, respectively. Three user-friendly and easy-to-use excel calculators were built based on the two proposed methods. The results showed that our approaches ensured sufficient accuracy and achieved target PK/PD index early and were superior to the published methodologies. Our methodology has the potential to be used for vancomycin dose optimization and can be easily implemented in clinical practice.

Panacea or oversimplification: Relating AUC and troughs

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Individualized Vancomycin Dosing with Therapeutic Drug Monitoring and Pharmacokinetic Consultation Service: A Large-Scale Retrospective Observational Study

Background

To date, outcome data with a large sample size and data regarding the clinical outcomes of pharmacokinetic-guided (PK) dosing of vancomycin are limited.

Aim

We evaluated the pharmacokinetic and clinical outcomes of a PK-guided dosing advisory program, pharmacokinetic consultation service (PKCS), in vancomycin treatment.

Methods

We investigated vancomycin therapeutic drug monitoring (TDM) and PKCS use through a retrospective review of patients who had serum vancomycin trough concentration data from October 2017 to November 2018. Among these patients, we selected non-critically ill adult patients satisfying our selection criteria to evaluate the effect of PKCS. Target trough attainment rate, time to target attainment, vancomycin-induced nephrotoxicity (VIN), vancomycin treatment failure rate, and duration of vancomycin therapy were compared between patients whose dosing was adjusted according to PKCS (PKCS group), and those whose dose was adjusted at the discretion of the attending physician (non-PKCS group).

Results

A total of 280 patients met the selection criteria for the VIN analysis (PKCS, n=134; non-PKCS, n=146). The incidence of VIN was similar between the two groups (PKCS, n=5; non-PKCS, n=5); however, the target attainment rate was higher in the PKCS group (75% vs 60%, P = 0.012). The time to target attainment was similar between the two groups. Further exclusions yielded 112 patients for the clinical outcome evaluation (PKCS, n=51; non-PKCS, n=61). The treatment failure rate was similar, and the duration of vancomycin therapy was longer in the PKCS group (12 vs 8 days, P = 0.008).

Conclusion

In non-critically ill patients, an increase in target trough achieved by PKCS did not lead to decreased vancomycin treatment failures, shorter vancomycin treatment, or decreased nephrotoxicity in vancomycin treatment. Considering the excessive amount of effort currently put into vancomycin dosing and monitoring, more selective criteria for individualized pharmacokinetic-guided dosing needs to be applied.