Target Concentration Intervention in Oncology

Saleem, Mohamed; Dimeski, Goce; Kirkpatrick, Carl M.; Taylor, Paul J.; Martin, Jennifer

doi:10.1097/ftd.0b013e3182557342

Cited by 20 publications

(14 citation statements)

References 84 publications

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“…Therapeutic drug monitoring (TDM) focuses on the measurement and interpretation of drug serum concentrations in relation to a therapeutic range, but TDM is rarely undertaken. 4 Hence, an alternative strategy, target concentration intervention (TCI) has been proposed 4,5 and a target concentration instead of a range is used. In TCI, a target concentration is selected and pharmacokinetic parameters for the patient are calculated according to the relevant covariates and used to estimate initial dose to achieve the target concentration.…”

Section: What Is Known and Objectivementioning

confidence: 99%

“…6 To perform TCI, one of the prerequisites is building an appropriate population pharmacokinetic model (PopPK). 4,5 During TCI, drug concentration is used to evaluate the clinical effects and to estimate the patient's individual parameters and subsequently to adjust the dosage if the target effect is not reached. 9,10 In TDM of vancomycin in many Chinese hospitals, peak concentration as well as trough concentration is monitored.…”

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confidence: 99%

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Predictive performance of reported population pharmacokinetic models of vancomycin in Chinese adult patients

Deng

Liu

et al. 2013

J Clin Pharm Ther

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SUMMARYWhat is known and objective: There are numerous studies on population pharmacokinetics of vancomycin in adult patients. However, there is no such research for Chinese adult patients. This study was conducted to evaluate the predictive performance of reported population pharmacokinetic models of vancomycin in Chinese adult patients and to identify some models appropriate for our population. Methods: A literature search was conducted in PubMed to obtain the population pharmacokinetic models of vancomycin published between December 2010 and September 2012. The models were assessed using concentration data collected from Chinese patients for external validation. Models with relatively poor predictability were excluded from further analysis. The performance of the remaining models was evaluated in patients with different levels of creatinine clearance, age, body weight and sex by Bayesian method. This method was also used to compare the predictive performance based on peak concentration and trough concentration and the predictability based on different number of observed concentrations. Results: One hundred and sixty-five blood concentrations from 72 Chinese adult patients were collected retrospectively to serve as the test data set. The evaluated models included all those reported in the seven publications reviewed by Marsot et al. and three other studies published after December 2010. Three models with poor performance on external validation were excluded from the next Bayesian analysis. The distribution of covariates in the model building data set had an important effect on prediction. The predictability based on peak/trough concentration was similar among the evaluated models, and no significant difference was found using our data set except for Roberts' model. As expected, an increased number of samples improved the performance of the Bayesian prediction. What is new and conclusion: With our data set, the performance of the evaluated models varied. The characteristics of the patient population and distribution of covariates should be given more consideration when choosing a model to predict blood concentrations. The model developed by Purwonugroho et al. using a data set from patients similar to ours is appropriate for Bayesian dose predictions for vancomycin concentrations in our population of Chinese adult patients. WHAT IS KNOWN AND OBJECTIVEVancomycin is a glycopeptide antibiotic, with time-dependent bacterial killing effect, which is used for therapy of infections caused by penicillinase-producing Staphylococcus aureus, especially methicillin-resistant Staphylococcus aureus (MRSA), Staphylococcus epidermis and Enterococcus faecalis.

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Section: What Is Known and Objectivementioning

confidence: 99%

mentioning

confidence: 99%

Predictive performance of reported population pharmacokinetic models of vancomycin in Chinese adult patients

Deng

Liu

et al. 2013

J Clin Pharm Ther

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“…Clinically, the target concentration intervention (TCI) has been widely applied and can help maximize clinical benefits [23,24] . For TCI, a proper Pop-PK model is required [25,26] and is valuable in highly variable populations that are receiving a drug with a narrow therapeutic window, eg, vancomycin [27] . TCI focuses on the estimation of the initial dose to achieve the target concentration by calculating the pharmacokinetic (PK) and pharmacodynamic (PD) parameters according to the relevant covariates, such as dosage, treatment duration, and clinical effects during treatment [28] .…”

Section: Introductionmentioning

confidence: 99%

Influences of renal function descriptors on population pharmacokinetic modeling of vancomycin in Chinese adult patients

et al. 2017

Acta Pharmacol Sin

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Vancomycin, a glycopeptide antibiotic for the treatment of grampositive infections, is mainly eliminated via glomerular filtration. Thus, its therapeutic effects are affected predominantly by renal function. The aim of this study was to develop a population pharmacokinetic model of vancomycin for Chinese adult patients and to investigate the influence of different renal function descriptors on the predictability of the model. A retrospective analysis was performed based on the blood concentrations of vancomycin in 218 Chinese adult patients. Among these patients, the data from 160 were used to establish the population pharmacokinetic model, and the data from the remaining 58 patients were used for external model validation. A simulation was employed to determine the appropriate initial vancomycin dosage regimens in adult Chinese patients for reaching the target steady-state trough concentrations of 10-15 mg/L and 15-20 mg/L. We developed a one-compartment model with first-order absorption to characterize the concentration-time profile of vancomycin. There was a positive correlation between the body clearance of vancomycin and renal function; both creatinine clearance (CL) and age were the covariates that influenced the PK of vancomycin, and the excretion of vancomycin decreased as renal function diminishing with age. The typical clearance (CL) value was 2.829 L/h for 75-year-old patients with CL values of 80 mL/min, and the rate constant of CL with the CL changing at 1 mL/min was 0.00842. The influence coefficient of age on CL was 0.08143. The external validation results revealed that the current different descriptors of renal function behaved similarly to the predicted performance of the models. In conclusion, the developed model is appropriate for Bayesian dose predictions of vancomycin concentrations in the population of Chinese adult patients. Furthermore, the simulation provides a reference for clinical optimized antibacterial therapy with vancomycin.

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“…Higher initial doses are also given, with the aim of achieving early high serum rituximab concentrations and maintaining the concentrations longer , thus providing a higher overall exposure. In a phase II study, higher PFS and overall survival were shown in study participants with poorer prognosis under the SMARTE‐R‐CHOP‐14 in comparison with the schedule used in the RICOVER‐60 trial . Furthermore, pharmacokinetic analysis showed that maximal rituximab trough concentrations were indeed achieved earlier and remained in the serum for a longer time.…”

Section: Factors Affecting Rituximab Exposurementioning

confidence: 99%

“…The existence of such a concentration–effect relationship might potentially serve as the basis for therapeutic drug monitoring and target concentration intervention, i.e. modifying dose according to concentrations and response, for optimizing the use of rituximab in patients with CD20 + lymphoproliferative disorders . Although the literature for rituximab is sparse, there have been studies demonstrating relationships between PK/PD factors of other chemotherapeutic drugs for haematological malignancies with clinical outcomes.…”

Section: Rituximab and Pharmacokinetic–pharmacodynamic Modellingmentioning

confidence: 99%

A new frontier in haematology – combining pharmacokinetic with pharmacodynamic factors to improve choice and dose of drug

Arpon

Gandhi

Martin

2014

Brit J Clinical Pharma

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The issue of tailored dosing adjusted according to a range of patient-specific factors other than bodyweight or body surface area is of large and increasing clinical and financial concern. Even if it is known that dosing alterations are likely to be required for parameters such as body composition, gender and pharmacogenetics, the amount of dosing change is unknown. Thus, pharmacokinetically guided dosing is making a resurgence, particularly in areas of medicine where there are cost constraints or safety issues, such as in haematology medications. However, the evidence to support the behaviour is minimal, particularly when long-term outcomes are considered. In haematology, there are particular issues around efficacy, toxicity and overall cost. Newer targeted agents, such as the monoclonal antibody rituximab and the tyrosine kinase inhibitor imatinib, whilst clearly being highly effective, are dosed on a milligram per square metre (rituximab) or fixed dose basis (imatinib), regardless of body composition, tumour aspects or comorbidity. This review questions this practice and raises important clinical issues; specifically, the clinical potential for combined pharmacokinetically and pharmacodynamically guided dosing of new targeted agents in haematological malignancies. This pharmacokinetically and pharmacodynamically guided dosing is an emerging area of clinical pharmacology, driven predominantly by toxicity, efficacy and cost issues, but also because reasonable outcomes are being noted with more appropriately dosed older medications adjusted for patient-specific factors. Clinical trials to investigate the optimization of rituximab dose scheduling are required.

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Target Concentration Intervention in Oncology

Cited by 20 publications

References 84 publications

Predictive performance of reported population pharmacokinetic models of vancomycin in Chinese adult patients

Predictive performance of reported population pharmacokinetic models of vancomycin in Chinese adult patients

Influences of renal function descriptors on population pharmacokinetic modeling of vancomycin in Chinese adult patients

A new frontier in haematology – combining pharmacokinetic with pharmacodynamic factors to improve choice and dose of drug

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