Voriconazole: an audit of hospital-based dosing and monitoring and evaluation of the predictive performance of a dose-prediction software package

2020 ◽  
Vol 75 (7) ◽  
pp. 1981-1984 ◽  
Author(s):  
Kanika Chaudhri ◽  
Sophie L Stocker ◽  
Kenneth M Williams ◽  
Robert C McLeay ◽  
Deborah J E Marriott ◽  
...  
Keyword(s):  
Prediction Error ◽  
Software Package ◽  
Fungal Infections ◽  
Plasma Concentrations ◽  
Predictive Performance ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Dose Prediction ◽  
Retrospective Audit ◽  
Trough Concentrations

Abstract Background Therapeutic drug monitoring (TDM) is recommended to guide voriconazole therapy. Objectives To determine compliance of hospital-based voriconazole dosing and TDM with the Australian national guidelines and evaluate the predictive performance of a one-compartment population pharmacokinetic voriconazole model available in a commercial dose-prediction software package. Methods A retrospective audit of voriconazole therapy at an Australian public hospital (1 January to 31 December 2016) was undertaken. Data collected included patient demographics, dosing history and plasma concentrations. Concordance of dosing and TDM with Australian guidelines was assessed. Observed concentrations were compared with those predicted by dose-prediction software. Measures of bias (mean prediction error) and precision (mean squared prediction error) were calculated. Results Adherence to dosing guidelines for 110 courses of therapy (41% for prophylaxis and 59% for invasive fungal infections) was poor, unless oral formulation guidelines recommended a 200 mg dose, the most commonly prescribed dose (56% of prescriptions). Plasma voriconazole concentrations were obtained for 82% (90/110) of courses [median of 3 (range: 1–27) obtained per course]. A minority (27%) of plasma concentrations were trough concentrations [median concentration: 1.5 mg/L (range: <0.1 to >5.0 mg/L)]. Of trough concentrations, 57% (58/101) were therapeutic, 37% (37/101) were subtherapeutic and 6% (6/101) were supratherapeutic. The dose-prediction software performed well, with acceptable bias and precision of 0.09 mg/L (95% CI −0.08 to 0.27) and 1.32 (mg/L)2 (95% CI 0.96–1.67), respectively. Conclusions Voriconazole dosing was suboptimal based on published guidelines and TDM results. Dose-prediction software could enhance TDM-guided therapy.

scholarly journals Population pharmacokinetics of dolutegravir: influence of drug–drug interactions in a real-life setting

2019 ◽  
Vol 74 (9) ◽  
pp. 2690-2697 ◽  
Author(s):  
Catalina Barcelo ◽  
Manel Aouri ◽  
Perrine Courlet ◽  
Monia Guidi ◽  
Dominique L Braun ◽  
...  
Keyword(s):  
Drug Interactions ◽  
Plasma Concentrations ◽  
Real Life ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Genetic Barrier ◽  
Good Tolerability ◽  
Standard Dosage ◽  
Real Life Setting ◽  
Trough Concentrations

Abstract Objectives Dolutegravir is widely prescribed owing to its potent antiviral activity, high genetic barrier and good tolerability. The aim of this study was to characterize dolutegravir’s pharmacokinetic profile and variability in a real-life setting and to identify individual factors and co-medications affecting dolutegravir disposition. Methods A population pharmacokinetic model was developed using NONMEM®. Relevant demographic factors, clinical factors and co-medications were tested as potential covariates. Simulations based on the final model served to compare expected dolutegravir concentrations under standard and alternative dosage regimens in the case of drug–drug interactions. Results A total of 620 dolutegravir plasma concentrations were collected from 521 HIV-infected individuals under steady-state conditions. A one-compartment model with first-order absorption and elimination best characterized dolutegravir pharmacokinetics. Typical dolutegravir apparent clearance (CL/F) was 0.93 L/h with 32% between-subject variability, the apparent volume of distribution was 20.2 L and the absorption rate constant was fixed to 2.24 h−1. Older age, higher body weight and current smoking were associated with higher CL/F. Atazanavir co-administration decreased dolutegravir CL/F by 38%, while darunavir modestly increased CL/F by 14%. Rifampicin co-administration showed the largest impact on CL/F. Simulations suggest that average dolutegravir trough concentrations are 63% lower after 50 mg/12h with rifampicin compared with a standard dosage of 50 mg/24h without rifampicin. Average trough concentrations after 100 mg/24h and 100 mg/12h with rifampicin are 92% and 25% lower than the standard dosage without rifampicin, respectively. Conclusions Patients co-treated with dolutegravir and rifampicin might benefit from therapeutic drug monitoring and individualized dosage increase, up to 100 mg/12 h in some cases.

scholarly journals Model Based Identification of Linezolid Exposure–toxicity Thresholds in Hospitalized Patients

2021 ◽  
Vol 12 ◽  
Author(s):  
Jie Fang ◽  
Xiao-Shan Zhang ◽  
Chun-Hong Zhang ◽  
Zi-Ye Zhou ◽  
Lu Han ◽  
...  
Keyword(s):  
Steady State ◽  
Serum Albumin ◽  
White Cell Count ◽  
Plasma Concentrations ◽  
Regression Tree ◽  
Predictive Performance ◽  
Volume Of Distribution ◽  
Classification And Regression Tree ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic

Evidence supports linezolid therapeutic drug monitoring as the exposure–response relationship has been identified for toxicity among patients receiving linezolid, but the data to establish the upper limit are limited and the published toxicity thresholds range widely. The purpose of this study was to determine the linezolid exposure–toxicity thresholds to improve the safety of linezolid. This is a multicenter retrospective study of adult patients treated with linezolid from 2018 to 2019. The population pharmacokinetic model of linezolid was established based on 270 plasma concentrations in 152 patients, which showed creatinine clearance and white cell count are covariates affecting the clearance of linezolid, and serum albumin is the covariate affecting the volume of distribution. Classification and regression tree analysis was used to determine the linezolid exposure thresholds associated with an increased probability of toxicity. Among 141 patients included for toxicity analysis, the rate of occurring toxicity was significantly higher among patients with an AUC0-24, d1 ≥163 mg h/L, AUC0-24, d2 ≥207 mg h/L, AUC0-24, ss ≥210 mg h/L, and Cmin,d2 ≥6.9 mg/L, Cmin,ss ≥6.9 mg/L, while no threshold was discovered for Cmin, d1. Those exposure thresholds and duration of linezolid treatment were independently associated with linezolid-related toxicity in the logistic regression analyses. In addition, the predictive performance of the AUC0-24 and Cmin thresholds at day 2 and steady state were close. Considering that the AUC estimation is cumbersome, Cmin threshold at 48 h and steady state with a value of ≥6.9 mg/L is recommended to improve safety, especially for patients with renal insufficiency and patients with low serum albumin.

scholarly journals Comparative Evaluation of the Predictive Performances of Three Different Structural Population Pharmacokinetic Models To Predict Future Voriconazole Concentrations

2016 ◽  
Vol 60 (11) ◽  
pp. 6806-6812 ◽  
Author(s):  
Andras Farkas ◽  
Gergely Daroczi ◽  
Phillip Villasurda ◽  
Michael Dolton ◽  
Midori Nakagaki ◽  
...  
Keyword(s):  
Prediction Error ◽  
Fungal Infections ◽  
Nonlinear Models ◽  
Point Of View ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Cell Transplant ◽  
Concentration Data ◽  
Hematopoietic Stem ◽  
Squared Prediction Error

ABSTRACTBayesian methods for voriconazole therapeutic drug monitoring (TDM) have been reported previously, but there are only sparse reports comparing the accuracy and precision of predictions of published models. Furthermore, the comparative accuracy of linear, mixed linear and nonlinear, or entirely nonlinear models may be of high clinical relevance. In this study, models were coded into individually designed optimum dosing strategies (ID-ODS) with voriconazole concentration data analyzed using inverse Bayesian modeling. The data used were from two independent data sets, patients with proven or suspected invasive fungal infections (n =57) and hematopoietic stem cell transplant recipients (n =10). Observed voriconazole concentrations were predicted whereby for each concentration value, the data available to that point were used to predict that value. The mean prediction error (ME) and mean squared prediction error (MSE) and their 95% confidence intervals (95% CI) were calculated to measure absolute bias and precision, while ΔME and ΔMSE and their 95% CI were used to measure relative bias and precision, respectively. A total of 519 voriconazole concentrations were analyzed using three models. MEs (95% CI) were 0.09 (−0.02, 0.22), 0.23 (0.04, 0.42), and 0.35 (0.16 to 0.54) while the MSEs (95% CI) were 2.1 (1.03, 3.17), 4.98 (0.90, 9.06), and 4.97 (−0.54 to 10.48) for the linear, mixed, and nonlinear models, respectively. In conclusion, while simulations with the linear model were found to be slightly more accurate and similarly precise, the small difference in accuracy is likely negligible from the clinical point of view, making all three approaches appropriate for use in a voriconazole TDM program.

scholarly journals Software for Dosage Individualization of Voriconazole for Immunocompromised Patients

2013 ◽  
Vol 57 (4) ◽  
pp. 1888-1894 ◽  
Author(s):  
William W. Hope ◽  
Michael VanGuilder ◽  
J. Peter Donnelly ◽  
Nicole M. A. Blijlevens ◽  
Roger J. M. Brüggemann ◽  
...  
Keyword(s):  
Therapeutic Drug Monitoring ◽  
Drug Monitoring ◽  
Fungal Infections ◽  
Plasma Concentrations ◽  
Therapeutic Drug ◽  
Cell Transplant ◽  
Multiple Model ◽  
Pharmacokinetic Variability ◽  
Hematopoietic Stem ◽  
Wide Range

ABSTRACTThe efficacy of voriconazole is potentially compromised by considerable pharmacokinetic variability. There are increasing insights into voriconazole concentrations that are safe and effective for treatment of invasive fungal infections. Therapeutic drug monitoring is increasingly advocated. Software to aid in the individualization of dosing would be an extremely useful clinical tool. We developed software to enable the individualization of voriconazole dosing to attain predefined serum concentration targets. The process of individualized voriconazole therapy was based on concepts of Bayesian stochastic adaptive control. Multiple-model dosage design with feedback control was used to calculate dosages that achieved desired concentration targets with maximum precision. The performance of the software program was assessed using the data from 10 recipients of an allogeneic hematopoietic stem cell transplant (HSCT) receiving intravenous (i.v.) voriconazole. The program was able to model the plasma concentrations with a high level of precision, despite the wide range of concentration trajectories and interindividual pharmacokinetic variability. The voriconazole concentrations predicted after the last dosages were largely concordant with those actually measured. Simulations provided an illustration of the way in which the software can be used to adjust dosages of patients falling outside desired concentration targets. This software appears to be an extremely useful tool to further optimize voriconazole therapy and aid in therapeutic drug monitoring. Further prospective studies are now required to define the utility of the controller in daily clinical practice.

scholarly journals Pregnancy-Related Effects on Nelfinavir-M8 Pharmacokinetics: a Population Study with 133 Women

2006 ◽  
Vol 50 (6) ◽  
pp. 2079-2086 ◽  
Author(s):  
Déborah Hirt ◽  
Jean-Marc Treluyer ◽  
Vincent Jullien ◽  
Ghislaine Firtion ◽  
Hélène Chappuy ◽  
...  
Keyword(s):  
Population Study ◽  
Time Course ◽  
Plasma Concentrations ◽  
Elimination Rate ◽  
Concomitant Administration ◽  
Individual Characteristics ◽  
Individual Treatment ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Linear Absorption

ABSTRACT A relationship between nelfinavir antiretroviral efficacy and plasma concentrations has been previously established. As physiological changes associated with pregnancy have a large impact on the pharmacokinetics of many drugs, a nelfinavir population study with women was developed, and the large intersubject variability was analyzed in order to optimize individual treatment schedules for this drug during pregnancy. A population pharmacokinetic model was developed in order to describe the concentration time course of nelfinavir and its metabolite M8 in pregnant and nonpregnant women. Individual characteristics, such as age, body weight, and weeks of gestation or delivery, which may influence nelfinavir-M8 pharmacokinetics were investigated. Data from therapeutic drug monitoring in 133 women treated with nelfinavir were retrospectively analyzed with NONMEM. Nelfinavir pharmacokinetics was described by a one-compartment model with linear absorption and elimination and M8 produced from the nelfinavir central compartment. Mean pharmacokinetic estimates and the corresponding intersubject percent variabilities for a nonpregnant woman were the following: absorption rate, 0.83 h−1; absorption lag time, 0.85 h; apparent nelfinavir elimination clearance (CL10/F), 35.5 liters/h (50%); apparent volume of distribution (V/F), 596 liters (118%); apparent formation clearance to M8 (CL1M/F), 0.65 liters/h (69%); and M8 elimination rate constant (k M0), 3.3 h−1 (59%). During pregnancy, we observed significant increases in nelfinavir (44.4 liters/h) and M8 (5 h−1) elimination but unchanged nelfinavir transformation clearance to M8, suggesting an induction of CYP3A4 but no effect on CYP2C19. Apparent nelfinavir clearance and volume showed a twofold increase on the day of delivery, suggesting a decrease in bioavailability on this day. The M8 elimination rate was increased by concomitant administration of nonnucleoside reverse transcriptase inhibitors. A trough nelfinavir plasma concentration above 1 mg/liter was previously shown to improve the antiretroviral response. The Bayesian individual pharmacokinetic estimates suggested that the dosage should not be changed in pregnant women but may be doubled on the day of delivery.

POPULATION PHARMACOKINETICS AND DOSING OPTIMIZATION OF TEICOPLANIN IN CHILDREN WITH MALIGNANT HAEMATOLOGICAL DISEASE

2015 ◽  
Vol 101 (1) ◽  
pp. e1.41-e1
Author(s):  
Wei Zhao ◽  
Daolun Zhang ◽  
Thomas Storme ◽  
André Baruchel ◽  
Xavier Declèves ◽  
...  
Keyword(s):  
Population Pharmacokinetics ◽  
Haematological Malignancy ◽  
External Validation ◽  
Predictive Performance ◽  
Paediatric Population ◽  
Pharmacokinetic Parameters ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
High Risk Population ◽  
Dosing Regimen

BackgroundChildren with haematological malignancy represent an identified subgroup of the paediatric population with specific pharmacokinetic parameters. In these patients, inadequate empirical antibacterial therapy may result in infection-related morbidity and increased mortality, making optimization of the dosing regimen essential. As paediatric data are limited, our aim was to evaluate the population pharmacokinetics of teicoplanin in order to define the appropriate dosing regimen in this high-risk population.MethodsThe current dose of teicoplanin was evaluated in children with haematological malignancy. Population pharmacokinetics of teicoplanin was analysed using NONMEM software. The dosing regimen was optimised based on the final model.ResultsEighty-five children (age range: 0.5 to 16.9 years) were included. Therapeutic drug monitoring and opportunistic samples (n=143) were available for analysis. With the current recommended dose of 10 mg/kg/day, 41 children (48%) had sub-therapeutic steady-state trough concentrations (Css,min<10 mg/liter). A two-compartment pharmacokinetic model with first-order elimination was developed. Systematic covariate analysis identified that bodyweight (size) and creatinine clearance significantly influenced teicoplanin clearance. The model was validated internally. Its predictive performance was further confirmed in an external validation. In order to reach the target AUC of 750 mg·h/L, 18 mg/kg was required for infants, 14 mg/kg for children and 12 mg/kg for adolescents. A patient-tailored dose regimen was further developed and reduced variability in AUC and Css,min values compared to the mg/kg-basis dose, making the modelling approach an important tool for dosing individualization.ConclusionsThis first population pharmacokinetic study of teicoplanin in children with haematological malignancy provided evidence-based support to individualize teicoplanin therapy in this vulnerable population.

scholarly journals External validation of the predictive performance of population pharmacokinetic models for phenobarbital in pediatric patients

2020 ◽  
Author(s):  
Sunae Ryu ◽  
Woo Jin Jung ◽  
Zheng Jiao ◽  
Jung Woo Chae ◽  
Hwi-yeol Yun
Keyword(s):  
External Validation ◽  
Predictive Performance ◽  
Validation Dataset ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Pharmacokinetic Models ◽  
Bayesian Forecasting ◽  
Predictive Capability ◽  
Young Infants ◽  
Simulation Based

Aim: Several studies have reported population pharmacokinetic models for phenobarbital (PB), but the predictive performance of these models has not been well documented. This study aims to do external validation of the predictive performance in published pharmacokinetic models. Methods: Therapeutic drug monitoring data collected in neonates and young infants treated with PB for seizure control, was used for external validation. A literature review was conducted through PubMed to identify population pharmacokinetic models. Prediction- and simulation-based diagnostics, and Bayesian forecasting were performed for external validation. The incorporation of size or maturity functions into the published models was also tested for prediction improvement. Results: A total of 79 serum concentrations from 28 subjects were included in the external validation dataset. Seven population pharmacokinetic studies of PB were selected for evaluation. The model by Voller et al. [27] showed the best performance concerning prediction-based evaluation. In simulation-based analyses, the normalized prediction distribution error of two models (those of Shellhaas et al. [24] and Marsot et al. [25]) obeyed a normal distribution. Bayesian forecasting with more than one observation improved predictive capability. Incorporation of both allometric size scaling and maturation function generally enhanced the predictive performance, but with marked improvement for the adult pharmacokinetic model. Conclusion: The predictive performance of published pharmacokinetic models of PB was diverse, and validation may be necessary to extrapolate to different clinical settings. Our findings suggest that Bayesian forecasting improves the predictive capability of individual concentrations for pediatrics.

scholarly journals Pharmacokinetic Modeling and Optimal Sampling Strategies for Therapeutic Drug Monitoring of Rifampin in Patients with Tuberculosis

2015 ◽  
Vol 59 (8) ◽  
pp. 4907-4913 ◽  
Author(s):  
Marieke G. G. Sturkenboom ◽  
Leonie W. Mulder ◽  
Arthur de Jager ◽  
Richard van Altena ◽  
Rob E. Aarnoutse ◽  
...  
Keyword(s):  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Mean Squared Error ◽  
Geometric Mean ◽  
Plasma Concentrations ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Optimal Sampling ◽  
Sampling Strategies ◽  
Wide Range

ABSTRACTRifampin, together with isoniazid, has been the backbone of the current first-line treatment of tuberculosis (TB). The ratio of the area under the concentration-time curve from 0 to 24 h (AUC0–24) to the MIC is the best predictive pharmacokinetic-pharmacodynamic parameter for determinations of efficacy. The objective of this study was to develop an optimal sampling procedure based on population pharmacokinetics to predict AUC0–24values. Patients received rifampin orally once daily as part of their anti-TB treatment. A one-compartmental pharmacokinetic population model with first-order absorption and lag time was developed using observed rifampin plasma concentrations from 55 patients. The population pharmacokinetic model was developed using an iterative two-stage Bayesian procedure and was cross-validated. Optimal sampling strategies were calculated using Monte Carlo simulation (n= 1,000). The geometric mean AUC0–24value was 41.5 (range, 13.5 to 117) mg · h/liter. The median time to maximum concentration of drug in serum (Tmax) was 2.2 h, ranging from 0.4 to 5.7 h. This wide range indicates that obtaining a concentration level at 2 h (C2) would not capture the peak concentration in a large proportion of the population. Optimal sampling using concentrations at 1, 3, and 8 h postdosing was considered clinically suitable with anr2value of 0.96, a root mean squared error value of 13.2%, and a prediction bias value of −0.4%. This study showed that the rifampin AUC0–24in TB patients can be predicted with acceptable accuracy and precision using the developed population pharmacokinetic model with optimal sampling at time points 1, 3, and 8 h.

scholarly journals P99 Clinical validation of published vancomycin population PK models in critically ill neonates

2019 ◽  
Vol 104 (6) ◽  
pp. e58.2-e59
Author(s):  
A van der Veen ◽  
RJ Keizer ◽  
W de Boode ◽  
A Somers ◽  
R Brüggemann ◽  
...  
Keyword(s):  
Therapeutic Drug Monitoring ◽  
Drug Monitoring ◽  
A Priori ◽  
Predictive Performance ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Suitable Model ◽  
List Type ◽  
A Posteriori ◽  
Target Attainment

BackgroundVancomycin is commonly used for treatment of severe Gram+ neonatal infections. Currently, even with the use of optimized dosing regimens and therapeutic drug monitoring (TDM), target attainment rates are abominable, leaving patients at risk for therapeutic failure and toxicity. Model-informed precision dosing (MIPD) offers a large potential to improve therapy in the individual patient.The aim of this study was to identify a suitable model for bedside MIPD by assessing the predictive performance of published population pharmacokinetic (popPK) models.MethodsA literature search was conducted to identify parametric popPK models. PK vancomycin data were retrospectively collected from NICU patients at the Radboud University Hospital, Nijmegen, The Netherlands. The model predictive performance was assessed by comparison of predictions to observations, calculation of bias (Mean Percentage Errors, MPE) and imprecision (Normalized Root Mean Squared Errors, NRMSE). Evaluations included both a priori (model covariate input) and a posteriori (model covariate and TDM concentration input) scenarios.Results265 TDM measurements from 65 neonates (median postmenstrual age:32 weeks [range:25–45 weeks]; median weight:1281g [range:597–5360g]; median serum creatinine:0,48 mg/dL [range:0,15–1,28 mg/dL]) were used for model evaluation. Six popPK models were evaluated1–6. A posteriori predictions of all models were consistently more accurate and precise compared to the a priori (starting dose) predictions. PopPK models of Frymoyer et al. and Capparelli et al. consistently performed best through all evaluations in both the a priori and a posteriori scenario (MPE ranging from -18 to 6,4% in a priori scenario and -6,5 to -3,8% in a posteriori scenario; NRMSE ranging from 34 to 40% in a priori scenario and 23 to 24% in a posteriori scenario).ConclusionLarge differences in predictive performance of popPK models were observed. Repeated therapeutic drug monitoring remains necessary to increase target attainment rate. Best performing models for bedside MIPD were identified in our patient population.ReferencesZhao W, Lopez E, Biran V, et al. ( 2013). Vancomycin continuous infusion in neonates: Dosing optimisation and therapeutic drug monitoring. Arch Dis Child;98(6):449–453.Capparelli EV, Lane JR, Romanowski GL, et al. ( 2001). The influences of renal function and maturation on vancomycin elimination in newborns and infants. J Clin Pharmacol, 41:927–934.De Cock RFW, Allegaert K, Brussee JM, et al. ( 2014). Simultaneous pharmacokinetic modeling of gentamicin, tobramycin and vancomycin clearance from neonates to adults: towards a semi-physiological function for maturation in glomerular filtration. Pharm Res;31(10):2642–2654.Frymoyer A, Hersh AL, El-Komy MH, et al. ( 2014). Association between vancomycin trough concentration and area under the concentration-time curve in neonates. Antimicrob Agents Chemother, 58(11):6454–6461.Anderson BJ, Allegaert K, Van Den Anker JN, Cossey V, Holford NHG. ( 2006). Vancomycin pharmacokinetics in preterm neonates and the prediction of adult clearance. Br J Clin Pharmacol;63(1):75–84.Germovsek E, Osborne L, Gunaratnam F, Lounis SA, Busquets FB, Sinha AK. ( 2019). Development and external evaluation of a population pharmacokinetic model for continuous and intermittent administration of vancomycin in neonates and infants using prospectively collected data. J Antimicrob Chemother, 1–9.Disclosure(s)R. Keizer is an employee and stockholder of InsightRX.

Accuracy of predicting the vancomycin concentration in Japanese cancer patients by the Sawchuk–Zaske method or Bayesian method

2019 ◽  
Vol 26 (3) ◽  
pp. 543-548
Author(s):  
Toshihisa Nakashima ◽  
Takayuki Ohno ◽  
Keiichi Koido ◽  
Hironobu Hashimoto ◽  
Hiroyuki Terakado
Keyword(s):  
Cancer Patients ◽  
Prediction Error ◽  
Bayesian Method ◽  
Predictive Accuracy ◽  
Pharmacokinetic Parameters ◽  
Population Pharmacokinetic ◽  
Squared Prediction Error ◽  
Trough Concentrations ◽  
The Mean ◽  
Mean Prediction Error

Background In cancer patients treated with vancomycin, therapeutic drug monitoring is currently performed by the Bayesian method that involves estimating individual pharmacokinetics from population pharmacokinetic parameters and trough concentrations rather than the Sawchuk–Zaske method using peak and trough concentrations. Although the presence of malignancy influences the pharmacokinetic parameters of vancomycin, it is unclear whether cancer patients were included in the Japanese patient populations employed to estimate population pharmacokinetic parameters for this drug. The difference of predictive accuracy between the Sawchuk–Zaske and Bayesian methods in Japanese cancer patients is not completely understood. Objective To retrospectively compare the accuracy of predicting vancomycin concentrations between the Sawchuk–Zaske method and the Bayesian method in Japanese cancer patients. Methods Using data from 48 patients with various malignancies, the predictive accuracy (bias) and precision of the two methods were assessed by calculating the mean prediction error, the mean absolute prediction error, and the root mean squared prediction error. Results Prediction of the trough and peak vancomycin concentrations by the Sawchuk–Zaske method and the peak concentration by the Bayesian method showed a bias toward low values according to the mean prediction error. However, there were no significant differences between the two methods with regard to the changes of the mean prediction error, mean absolute prediction error, and root mean squared prediction error. Conclusion The Sawchuk–Zaske method and Bayesian method showed similar accuracy for predicting vancomycin concentrations in Japanese cancer patients.

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