WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Despite the frequent use of vancomycin in intensive care unit (ICU) patients, few studies aimed at characterizing vancomycin population pharmacokinetics have been performed in this critical population. • Population pharmacokinetics coupled with pharmacodynamic analysis, in order to optimize drug exposure and hence antibacterial effectiveness, has been little applied in these specific patients. WHAT THIS STUDY ADDS • Our population model characterized the pharmacokinetic profile of vancomycin in adult ICU patients, higher distribution volume values (V) being observed when the patient's serum creatinine (CrSe) was greater than 1 mg dl−1. • Age and creatinine clearance (CLcr) were identified as the main covariates explaining the pharmacokinetic variability in vancomycin CL. • Our pharmacokinetic/pharmacodynamic (PK/PD) simulation should aid clinicians to select initial vancomycin doses that will maximize the rate of response in the ICU setting, taking into account the patient's age and renal function as well as the susceptibility of Staphylococcus aureus. AIM To estimate the vancomycin pharmacokinetic profile in adult ICU patients and to assess vancomycin dosages for increasing the likelihood of optimal exposure. METHODS Five hundred and sixty‐nine concentration–time data from 191 patients were analysed using a population pharmacokinetic approach (NONMEN™). External model evaluation was made in 46 additional patients. The 24 h area under the concentration–time curve (AUC(0,24 h)) was derived from the final model. Minimum inhibitory concentration (MIC) values for S. aureus were obtained from the EUCAST database. AUC(0,24 h) : MIC ≥ 400 was considered as PK/PD efficacy index. The probability of different dosages attaining the target considering different strains of S. aureus and patient subgroups was estimated with Monte Carlo simulation. RESULTS Vancomycin CL showed a significant dependence on patient age and renal function whereas CrSe > 1 mg dl−1 increased V more than twofold. For our representative ICU patient, 61 years, 73 kg, CrSe= 1.4 mg dl−1, measured CLCr= 74.7 ml min−1, the estimated values were CL = 1.06 ml min−1 kg−1 and V= 2.04 l kg−1. The cumulative fraction of response for a standard vancomycin dose (2 g day−1) was less than 25% for VISA strains, and 33% to 95% for susceptible S. aureus, depending on patient characteristics. CONCLUSIONS Simulations provide useful information regarding the initial assessment of vancomycin dosing, the conventional dosing regimen probably being suboptimal in adult ICU patients. A graphic approach provides the recommended dose for any selected probability of attaining the PK/PD efficacy target or to evaluate the cumulative fraction of response for any dosing regimen in this population.
Background and Objectives Uncertainty exists regarding the optimal dosing regimen for vancomycin in different patient populations, leading to a plethora of subgroup-specific pharmacokinetic models and derived dosing regimens. We aimed to investigate whether a single model for vancomycin could be developed based on a broad dataset covering the extremes of patient characteristics. Furthermore, as a benchmark for current dosing recommendations, we evaluated and optimised the expected vancomycin exposure throughout life and for specific patient subgroups. Methods A pooled population-pharmacokinetic model was built in NONMEM based on data from 14 different studies in different patient populations. Steady-state exposure was simulated and compared across patient subgroups for two US Food and Drug Administration/European Medicines Agency-approved drug labels and optimised doses were derived. Results The final model uses postmenstrual age, weight and serum creatinine as covariates. A 35-year-old, 70-kg patient with a serum creatinine level of 0.83 mg dL −1 (73.4 µmol L −1) has a V 1 , V 2 , CL and Q 2 of 42.9 L, 41.7 L, 4.10 L h −1 and 3.22 L h −1. Clearance matures with age, reaching 50% of the maximal value (5.31 L h −1 70 kg −1) at 46.4 weeks postmenstrual age then declines with age to 50% at 61.6 years. Current dosing guidelines failed to achieve satisfactory steady-state exposure across patient subgroups. After optimisation, increased doses for the Food and Drug Administration label achieve consistent target attainment with minimal (± 20%) risk of under-and over-dosing across patient subgroups. Conclusions A population model was developed that is useful for further development of age and kidney function-stratified dosing regimens of vancomycin and for individualisation of treatment through therapeutic drug monitoring and Bayesian forecasting.
According to our pharmacokinetic population model, initial doses of gentamicin of 10 mg/kg, and dosage intervals between 36-48 h, appear to be appropriate to achieve target peak and trough serum levels of 15-20 and <0.5 mg/L, respectively, when extended-interval dosage regimens are implemented in newborns. The half-life of gentamicin in premature babies of very low weight and gestational age <31 weeks is long. Thus, to achieve serum concentrations in the 1-10 mg/L range, the use of dosage regimens of 5 mg/kg at 36-48 h dosage intervals seems suitable.
Aims: Therapeutic drug monitoring (TDM) of trough serum infliximab concentrations has been mainly used in case of loss of response in patients with inflammatory bowel disease (IBD). The aim of this study was to evaluate the effectiveness and safety of a multidisciplinary early proactive TDM (mep-TDM) programme for dose adjustment. Methods: A 3-year prospective study was conducted based on a sample of 81 patients who started treatment and were subsequently subjected to mep-TDM with the first control at week 14. Data of a historical control group of 72 patients treated with infliximab and managed with empirical dosing were included. Effectiveness variables were treatment failure, IBD-related surgery and IBD-related hospitalization. Safety variables were serious infusion reactions (SIRs) and adverse reactions. Cox regression was used for survival analysis. Results: In the mep-TDM study group, compared to the control group, there was a significant reduction in the risk of treatment failure (hazard ratio [HR]: 0.51; 95% confidence interval [CI]: 0.27-0.92; P = .037), IBD-related surgery (HR: 0.14; 95% CI:0.03-0.65; P = .012) and hospitalization (HR: 0.38; 95% CI: 0.17-0.87; P = .022). SIRs were lower in the mep-TDM group (2.5% vs 10.4%; P < .050); the incidence of adverse reactions was similar (3.7% vs 3.9%; p > .999).Conclusion: This study found that compared to empirical dosing, mep-TDM is associated with improved efficacy and safety of infliximab therapy, reduced IBD-related hospitalization and surgery and incidence of SIRs, and increasing long-term durability of treatment effects. K E Y W O R D Sinflammatory bowel diseases, infliximab, personalized medicine, therapeutic drug monitoring
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