Peak Measurement for Vancomycin AUC Estimation in Obese Adults Improves Precision and Lowers Bias

A Brief Review of Pharmacokinetic Assessments of Vancomycin in Special Groups of Patients with Altered Pharmacokinetic Parameters

Vancomycin is considered the drug of choice against many Gram-positive bacterial infections. Therapeutic drug monitoring (TDM) is essential to achieve an optimum clinical response and avoid vancomycin-induced adverse reactions including nephrotoxicity. Although different studies are available on vancomycin TDM, still there are controversies regarding the selection among different pharmacokinetic parameters including trough concentration, the area under the curve to minimum inhibitory concentration ratio (AUC24h/MIC), AUC of intervals, elimination constant, and vancomycin clearance. In this review, different pharmacokinetic parameters for vancomycin TDM have been discussed along with corresponding advantages and disadvantages. Also, vancomycin pharmacokinetic assessments are discussed in patients with altered pharmacokinetic parameters including those with renal and/or hepatic failure, critically ill patients, patients with burn injuries, intravenous drug users, obese and morbidly obese patients, those with cancer, patients undergoing organ transplantation, and vancomycin administration during pregnancy and lactation. An individualized dosing regimen is required to guarantee the optimum therapeutic responses and minimize adverse reactions including acute kidney injury in these special groups of patients. According to the pharmacoeconomic data on vancomycin TDM, pharmacokinetic assessments would be cost-effective in patients with altered pharmacokinetics and are associated with shorter hospitalization period, faster clinical stability status, and shorter courses of inpatient vancomycin administration.

Clinical Practice Guidelines for Therapeutic Drug Monitoring of Vancomycin in the Framework of Model-Informed Precision Dosing: A Consensus Review by the Japanese Society of Chemotherapy and the Japanese Society of Therapeutic Drug Monitoring

Background: To promote model-informed precision dosing (MIPD) for vancomycin (VCM), we developed statements for therapeutic drug monitoring (TDM). Methods: Ten clinical questions were selected. The committee conducted a systematic review and meta-analysis as well as clinical studies to establish recommendations for area under the concentration-time curve (AUC)-guided dosing. Results: AUC-guided dosing tended to more strongly decrease the risk of acute kidney injury (AKI) than trough-guided dosing, and a lower risk of treatment failure was demonstrated for higher AUC/minimum inhibitory concentration (MIC) ratios (cut-off of 400). Higher AUCs (cut-off of 600 μg·h/mL) significantly increased the risk of AKI. Although Bayesian estimation with two-point measurement was recommended, the trough concentration alone may be used in patients with mild infections in whom VCM was administered with q12h. To increase the concentration on days 1–2, the routine use of a loading dose is required. TDM on day 2 before steady state is reached should be considered to optimize the dose in patients with serious infections and a high risk of AKI. Conclusions: These VCM TDM guidelines provide recommendations based on MIPD to increase treatment response while preventing adverse effects.

Towards precision medicine: Therapeutic drug monitoring-guided dosing of vancomycin and β-lactam antibiotics to maximize effectiveness and minimize toxicity

PURPOSE

The goal of this review is to explore the role of antimicrobial therapeutic drug monitoring (TDM), especially in critically ill, obese, and older adults, with a specific focus on β-lactams and vancomycin.

SUMMARY

The continued rise of antimicrobial resistance prompts the need to optimize antimicrobial dosing. The aim of TDM is to individualize antimicrobial dosing to achieve antibiotic exposures associated with improved patient outcomes. Initially, TDM was developed to minimize adverse effects during use of narrow therapeutic index agents. Today, patient and organism complexity are expanding the need for precision dosing through TDM services. Alterations of pharmacokinetics and pharmacodynamics (PK/PD) in the critically ill, obese, and older adult populations, in conjunction with declining organism susceptibility, complicate attainment of therapeutic targets. Over the last decade, antimicrobial TDM has expanded with the emergence of literature supporting β-lactam TDM and a shift from monitoring vancomycin trough concentrations to monitoring of the ratio of area under the concentration (AUC) curve to minimum inhibitory concentration (MIC). PK/PD experts should be at the forefront of implementing precision dosing practices.

CONCLUSION

Precision dosing through TDM is expanding and is especially important in populations with altered PK/PD, including critically ill, obese, and older adults. Due to wide PK/PD variability in these populations, TDM is vital to maximize antimicrobial effectiveness and decrease adverse event rates. However, there is still a need for studies connecting TDM to patient outcomes. Providing patient-specific care through β-lactam TDM and transitioning to vancomycin AUC/MIC monitoring may be challenging, but with experts at the forefront of this initiative, PK-based optimization of antimicrobial therapy can be achieved.

Why we should sample sparsely and aim for a higher target: Lessons from model-based therapeutic drug monitoring of vancomycin in intensive care patients

Aims

To explore the optimal data sampling scheme and the pharmacokinetic (PK) target exposure on which dose computation is based in the model‐based therapeutic drug monitoring (TDM) practice of vancomycin in intensive care (ICU) patients.

Methods

We simulated concentration data for 1 day following four sampling schemes, C_min, C_max + C_min, C_max + C_{mid‐interval} + C_min, and rich sampling where a sample was drawn every hour within a dose interval. The datasets were used for Bayesian estimation to obtain PK parameters, which were used to compute the doses for the next day based on five PK target exposures: AUC₂₄ = 400, 500, and 600 mg·h/L and C_min = 15 and 20 mg/L. We then simulated data for the next day, adopting the computed doses, and repeated the above procedure for 7 days. Thereafter, we calculated the percentage error and the normalized root mean square error (NRMSE) of estimated against “true” PK parameters, and the percentage of optimal treatment (POT), defined as the percentage of patients who met 400 ≤ AUC₂₄ ≤ 600 mg·h/L and C_min ≤ 20 mg/L.

Results

PK parameters were unbiasedly estimated in all investigated scenarios and the 6‐day average NRMSE were 32.5%/38.5% (CL/V, where CL is clearance and V is volume of distribution) in the trough sampling scheme and 27.3%/26.5% (CL/V) in the rich sampling scheme. Regarding POT, the sampling scheme had marginal influence, while target exposure showed clear impacts that the maximum POT of 71.5% was reached when doses were computed based on AUC₂₄ = 500 mg·h/L.

Conclusions

For model‐based TDM of vancomycin in ICU patients, sampling more frequently than taking only trough samples adds no value and dosing based on AUC₂₄ = 500 mg·h/L lead to the best POT.

Assessing the accuracy of two Bayesian forecasting programs in estimating vancomycin drug exposure

Background

Current guidelines for intravenous vancomycin identify drug exposure (as indicated by the AUC) as the best pharmacokinetic (PK) indicator of therapeutic outcome.

Objectives

To assess the accuracy of two Bayesian forecasting programs in estimating vancomycin AUC0–∞ in adults with limited blood concentration sampling.

Methods

The application of seven vancomycin population PK models in two Bayesian forecasting programs was examined in non-obese adults (n = 22) with stable renal function. Patients were intensively sampled following a single (1000 mg or 15 mg/kg) dose. For each patient, AUC was calculated by fitting all vancomycin concentrations to a two-compartment model (defined as AUCTRUE). AUCTRUE was then compared with the Bayesian-estimated AUC0–∞ values using a single vancomycin concentration sampled at various times post-infusion.

Results

Optimal sampling times varied across different models. AUCTRUE was generally overestimated at earlier sampling times and underestimated at sampling times after 4 h post-infusion. The models by Goti et al. (Ther Drug Monit 2018;

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212–21) and Thomson et al. (J Antimicrob Chemother 2009;

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1050–7) had precise and unbiased sampling times (defined as mean imprecision <25% and <38 mg·h/L, with 95% CI for mean bias containing zero) between 1.5 and 6 h and between 0.75 and 2 h post-infusion, respectively. Precise but biased sampling times for Thomson et al. were between 4 and 6 h post-infusion.

Conclusions

When using a single vancomycin concentration for Bayesian estimation of vancomycin drug exposure (AUC), the predictive performance was generally most accurate with sample collection between 1.5 and 6 h after infusion, though optimal sampling times varied across different population PK models.

Examining the Relationship Between Vancomycin Area Under the Concentration Time Curve and Serum Trough Levels in Adults With Presumed or Documented Staphylococcal Infections

BACKGROUND

Investigations of the relationship between vancomycin trough concentrations and area under the concentration time curve (AUC) are growing, but still limited. The authors sought to determine vancomycin exposure among hospitalized adults with presumed or confirmed invasive staphylococcal infections using 2-level pharmacokinetic monitoring to inform changes to an institutional vancomycin dosing protocol.

METHODS

This was a retrospective observational study performed in 2 acute care hospitals. Adults prescribed vancomycin (therapeutic trough 15-20 mg/L) for a presumed or documented invasive staphylococcal infection were evaluated. Two steady-state serum vancomycin levels were used to determine each patient's 24-hour AUC to minimum inhibitory concentration ratio (AUC/MIC) using a non-Bayesian, equation-based approach. Patient demographics and crude clinical outcomes were also collected.

RESULTS

Thirty-four patients were included in the study, with 2 patients having vancomycin levels drawn twice (36 sets of levels). Most patients were located in an intensive care unit (91.2%), and 85.3% of patients were prescribed vancomycin for bacteremia, pneumonia, or endocarditis. The mean ± SD vancomycin Cmin was 16.6 ± 6.1 mg/L, and the mean AUC/MIC was 588 ± 156 mg/L × hour. The rate of 24-hour vancomycin AUC/MIC target attainment was 91.2% (n = 31/34). Of the patients with a Cmin > 9 mg/L, 100% (n = 33) achieved AUC/MIC values >400 mg/L × hour and 93.9% were >500 mg/L × hour. There was a strong correlation between vancomycin Cmin and AUC24 hr (R = 0.731; P < 0.001).

CONCLUSIONS

Targeting a vancomycin trough between 15 and 20 mg/L frequently resulted in an AUC/MIC greater than that thought to be necessary for efficacy optimization. Considering these findings alongside the practical challenges associated with wide-scale implementation of AUC monitoring, reducing the target trough as a means to prevent vancomycin overexposure warrants clinical consideration and further evaluation.

Comparison of Vancomycin Area-Under-the-Curve Dosing Versus Trough Target-Based Dosing in Obese and Nonobese Patients With Methicillin-Resistant Staphylococcus aureus Bacteremia

Background: A vancomycin target of area under the curve to minimum inhibitory concentration (AUC:MIC) ratio ≥400 is recommended for treatment of methicillin-resistant Staphylococcus aureus (MRSA) bacteremia. Objective: To evaluate vancomycin total daily dose (TDD) achieving trough targets versus a calculated strategy achieving AUC targets based on body mass index (BMI). Methods: A retrospective cohort study was performed within a large hospital network. Patients with MRSA bacteremia were eligible if they received vancomycin with a steady-state trough (15-20 mg/L). Cockcroft-Gault was used to estimate creatinine clearance, calculating vancomycin clearance and AUC. Patients were stratified by BMI (less than/greater than 30 kg/m²). The primary outcome was vancomycin TDD for the trough-based strategy compared with an AUC-dosing strategy. Results: A total of 119 patients were included, including 51 (42.9%) and 68 (57.1%) patients with high- and low-BMI, respectively. The TDD for trough-based dosing (2390.76 ± 1224.59 mg) differed significantly from AUC-based dosing (1985.07 ± 616.18 mg) across the cohort (P = 0.0014). For patients with high BMI, there was a significant difference (P < 0.0001) in TDD between trough (2637.25 ± 1327.89 mg) versus AUC (1918.71 ± 625.89 mg) strategies. No difference in TDD between dosing strategies was observed among low-BMI patients. Across all patients, 46 (38.7%) experienced acute kidney injury (AKI); high-BMI patients experienced higher rates of AKI compared with low-BMI patients (54.9 vs 26.5%; P = 0.002). Conclusions and Relevance: An AUC-based dosing strategy may reduce vancomycin TDD required for MRSA bacteremia compared with trough-based dosing, particularly for patients with higher BMI.

Vancomycin volume of distribution estimation in adults with class III obesity

PURPOSE

To compare methods of estimating vancomycin volume of distribution (V) in adults with class III obesity.

METHODS

A retrospective, multicenter pharmacokinetic analysis of adults treated with vancomycin and monitored through measurement of peak and trough concentrations was performed. Individual pharmacokinetic parameter estimates were obtained via maximum a posteriori Bayesian analysis. The relationship between V and body weight was assessed using linear regression. Mean bias and root-mean-square error (RMSE) were calculated to assess the precision of multiple methods of estimating V.

RESULTS

Of 241 patients included in the study sample, 159 (66.0%) had a body mass index (BMI) of 40.0-49.9 kg/m2, and 82 (34.0%) had a BMI of ≥50.0 kg/m2. The median (5th, 95th percentile) weight of patients was 136 (103, 204) kg, and baseline characteristics were similar between BMI groups. The mean ± S.D. V was lower in patients with a BMI of 40.0-49.9 kg/m2 than in those with a BMI of ≥50.0 kg/m2 (72.4 ± 19.6 L versus 79.3 ± 20.6 L, p = 0.009); however, body size poorly predicted V in regression analyses (R2 < 0.20). A fixed estimate of V (75 L) and use of a weight-based value (0.52 L/kg by total body weight [TBW]) yielded similar bias and error in this population.

CONCLUSION

Results of the largest analysis of vancomycin V in class III obesity to date indicated that use of a fixed V value (75 L) and use of a TBW-based estimate (0.52 L/kg) for estimation of vancomycin V in patients with a BMI of ≥40.0 kg/m2 have similar bias. Two postdistribution vancomycin concentrations are needed to accurately determine patient-specific pharmacokinetic parameters, estimate area under the curve, and improve the precision of vancomycin dosing in this patient population.

Relationships of Vancomycin Pharmacokinetics to Body Size and Composition Using a Novel Pharmacomorphomic Approach Based on Medical Imaging

Antibiotics such as vancomycin are empirically dosed on the basis of body weight, which may not be optimal across the expanding adult body size distribution. Our aim was to compare the relationships between morphomic parameters generated from computed tomography images to conventional body size metrics as predictors of vancomycin pharmacokinetics (PK). This single-center retrospective study included 300 patients with 1,622 vancomycin concentration (52% trough) measurements. Bayesian estimation was used to compute individual vancomycin volume of distribution of the central compartment (Vc) and clearance (CL). Approximately 45% of patients were obese with an overall median (5th, 95th percentile) weight and body mass index of 87.2 (54.7, 123) kg and 28.8 (18.9, 43.7) kg/m², respectively. Morphomic parameters of body size such as body depth, total body area, and torso volume of the twelfth thoracic through fourth lumbar vertebrae (T12 to L4) correlated with Vc. The relationship of vancomycin Vc was poorly predicted by body size but was stronger with T12-to-L4 torso volume (coefficient of determination [R²] = 0.11) than weight (R² = 0.04). No relationships between vancomycin CL and traditional body size metrics could be discerned; however, relationships with skeletal muscle volume and total psoas area were found. Vancomycin CL independently correlated with total psoas area and inversely correlated with age. Thus, vancomycin CL was significantly related to total psoas area over age (R² = 0.23, P < 0.0001). This proof-of-concept study suggests a potential role for translation of radiographic information into parameters predictive of drug pharmacokinetics. Prediction of individual antimicrobial pharmacokinetic parameters using analytic morphomics has the potential to improve antimicrobial dose selection and outcomes of obese patients.

Intravenous Vancomycin Associated With the Development of Nephrotoxicity in Patients With Class III Obesity

Background:A consensus statement recommends initial intravenous (IV) vancomycin dosing of 15-20 mg/kg every 8- 24 hours, with an optional 25- to 30-mg/kg loading dose. Although some studies have shown an association between weight and the development of vancomycin-associated nephrotoxicity, results have been inconsistent. Objective: To evaluate the correlation between incidence of nephrotoxicity associated with weight-based IV vancomycin dosing strategies in nonobese and obese patients. Methods: This retrospective cohort study evaluated hospitalized adult patients admitted who received IV vancomycin. Patients were stratified into nonobese (body mass index [BMI] <25 kg/m2), obesity class I and II (BMI 30-39.9kg/m2), and obesity class III (BMI≥40 kg/m2) groups; patients who were overweight but not obese were excluded. Incidence of nephrotoxicity and serum vancomycin trough concentrations were evaluated. Results: Of a total of 62 documented cases of nephrotoxicity (15.1%), 13 (8.7%), 23 (14.3%), and 26 (26.3%) cases were observed in nonobese, obesity class I and II, and obesity class III groups, respectively ( P=0.002). Longer durations of therapy ( P<0.0001), higher initial maintenance doses in both total milligrams/day ( P=0.0137) and milligrams/kilogram ( P=0.0307), and any trough level >20 mg/L ( P<0.0001) were identified as predictors of development of nephrotoxicity. Concomitant administration of piperacillin/tazobactam, diuretics, and IV contrast were associated with development of nephrotoxicity ( P<0.005, all). Patients with class III obesity were 3-times as likely to develop nephrotoxicity when compared with nonobese patients (odds ratio [OR]=2.99; CI=1.12-7.94) and obesity class I and II patients (OR=3.14; CI=1.27-7.75). Conclusions: Obesity and other factors are associated with a higher risk of vancomycin-associated nephrotoxicity.