Assessment of the validity of a population pharmacokinetic model for epirubicin.

AIMS: The aim of this study was to evaluate a population model for epirubicin clearance using internal and external validation techniques. METHODS: Jackknife samples were used to identify outliers in the population dataset and individuals influencing covariate selection. Sensitivity analyses were performed in which serum aspartate transaminase (AST) values (a covariate in the population model) or epirubicin concentrations were randomly changed by +/-10%. Cross-validation was performed five times, on each occasion using 80% of the data for model development and 20% to assess the performance of the model. External validation was conducted by assessing the ability of the population model to predict concentrations and clearances in a separate group of 79 patients. RESULTS: Structural parameter estimates from all jackknife samples were within 7.5% of the final population estimates and examination of log likelihood values indicated that the selection of AST in the final model was not due to the presence of outliers. Alteration of AST or epirubicin concentrations by +/-10% had a negligible effect on population parameter estimates and their precision. In the cross-validation analysis, the precision of clearance estimates was better in patients with AST concentrations>150 U l-1. In the external validation, epirubicin concentrations were over-predicted by 81.4% using the population model and clearance values were also poorly predicted (imprecision 43%). CONCLUSIONS: The results of internal validation of population pharmacokinetic models should be interpreted with caution, especially when the dataset is relatively small.

Maximum a posteriori Bayesian estimation of epirubicin clearance by limited sampling.

AIMS: To develop a limited sampling strategy for estimation of epirubicin clearance. METHODS: The data set comprised 1051 concentrations measured in 105 patients with advanced or metastatic breast cancer treated with epirubicin alone. Ten limited sampling designs comprising two or three blood samples were proposed, taken at times identified by D-optimality from population pharmacokinetic parameter estimates. The data set was then truncated to include the sampling times for each of the designs. MAP Bayesian estimates of clearance were generated for each design and compared with clearance estimates obtained using all the data. The limited sampling designs were also validated using a separate data set obtained from 18 patients with either breast cancer or hepatocellular carcinoma. The sensitivity of the best limited sampling designs to sample time recording errors of 0-10% or 10-20% was then assessed using a simulated data set including 200 patients. RESULTS: The optimum sampling times were: end of the injection and 18 min, 40 min, 3 h, 10 h and 48 h after the start of the injection. The best three-sample design included samples at 40 min, 3 h and 48 h and gave unbiased estimates of clearance with an imprecision of 9.1% (95% CI 7.3, 10.5). The best two sample design included samples at 3 and 48 h and gave unbiased estimates of clearance with an imprecision of 12.4% (95% CI 9.6, 14.6). Using the validation data set, these two and three sample designs gave unbiased estimates of clearance with an imprecision of 5.6% (95% CI 3.7, 7.0) and 4.2% (95% CI 2.6, 5.3), respectively. Simulations that included 0-10% or 10-20% errors in the recording of the blood sampling times had negligible effects on the bias and imprecision of clearance estimates. CONCLUSIONS: Limited sampling designs have been identified and validated that estimate epirubicin clearance with adequate precision and without bias from two or three blood samples. These designs also allow flexibility in blood sample collection and are robust with regard to sample time recording errors.

A population model of epirubicin pharmacokinetics and application to dosage guidelines.

PURPOSE: To use a population approach to identify readily available clinical or biochemical characteristics that influence the pharmacokinetics of epirubicin and to develop new dosage guidelines based on these results. METHODS: Data were available from 109 patients with advanced breast cancer, 72 of whom were known to have liver metastases. They were treated with single-agent epirubicin 12.5 to 120 mg/m(2). Analysis was performed using the software package NONMEM and a three-compartment model was fitted to the data. RESULTS: Individual clearance (CL) estimates ranged from 4 to 86 l/h and the final model included CL as a function of aspartate aminotransferase (AST): CL (l/h)=72.9-(72.9x0.135xlnAST). Inclusion of this factor reduced the interindividual variability in CL from 49% to 39%. Using a target AUC of 4000 ng.h/ml, the following doses were predicted to achieve this exposure with the greatest precision: AST <150 IU/l 125 mg; AST 150-250 IU/l 90 mg; AST 250-500 IU/l 60 mg; AST >500 IU/l 30 mg. These new guidelines were compared with three other guidelines based on serum bilirubin or AST concentrations and body surface area (BSA). The new guidelines achieved the target with greater precision (root mean squared error, rmse, 39.0%) than the current UK guidelines, current USA guidelines or an earlier equation based on AST (rmse 63%, 62% and 59%, respectively). CONCLUSIONS: The proposed dosing guidelines should reduce variability in systemic exposure to epirubicin more effectively than traditional approaches. In addition, as they do not require adjustment according to BSA, they could reduce dosage preparation time and the potential for prescribing and dispensing errors.