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Purpose: This study assessed whether a cycle of "routine" therapeutic drug monitoring (TDM) for imatinib dosage individualization, targeting an imatinib trough plasma concentration (C min) of 1,000 ng/ml (tolerance: 750-1,500 ng/ml), could improve clinical outcomes in chronic myelogenous leukemia (CML) patients, compared with TDM use only in case of problems ("rescue" TDM)., Methods: Imatinib concentration monitoring evaluation was a multicenter randomized controlled trial including adult patients in chronic or accelerated phase CML receiving imatinib since less than 5 years. Patients were allocated 1:1 to "routine TDM" or "rescue TDM." The primary endpoint was a combined outcome (failure- and toxicity-free survival with continuation on imatinib) over 1-year follow-up, analyzed in intention-to-treat (ISRCTN31181395)., Results: Among 56 patients (55 evaluable), 14/27 (52 %) receiving "routine TDM" remained event-free versus 16/28 (57 %) "rescue TDM" controls (P = 0.69). In the "routine TDM" arm, dosage recommendations were correctly adopted in 14 patients (median C min: 895 ng/ml), who had fewer unfavorable events (28 %) than the 13 not receiving the advised dosage (77 %; P = 0.03; median C min: 648 ng/ml)., Conclusions: This first target concentration intervention trial could not formally demonstrate a benefit of "routine TDM" because of small patient number and surprisingly limited prescriber's adherence to dosage recommendations. Favorable outcomes were, however, found in patients actually elected for target dosing. This study thus shows first prospective indication for TDM being a useful tool to guide drug dosage and shift decisions. The study design and analysis provide an interesting paradigm for future randomized TDM trials on targeted anticancer agents.

This observational study analyzed imatinib pharmacokinetics and response in 2478 chronic myeloid leukemia (CML) patients. Data were obtained through centralized therapeutic drug monitoring (TDM) at median treatment duration of ≥ 2 years. First, individual initial trough concentrations under 400mg/day imatinib starting dose were estimated. Second, their correlation (Cmin(400mg)) with reported treatment response was verified. Low imatinib levels were predicted in young male patients and those receiving P-gp/CYP3A4 inducers. These patients had also lower response rates (7% lower 18-months MMR in male, 17% lower 1-year CCyR in young patients, Kaplan-Meier estimates). Time-point independent multivariate regression confirmed a correlation of individual Cmin(400mg) with response and adverse events. Possibly due to confounding factors (e.g. dose modifications, patient selection bias), the relationship seemed however flatter than previously reported from prospective controlled studies. Nonetheless, these observational results strongly suggest that a subgroup of patients could benefit from early dosage optimization assisted by TDM, because of lower imatinib concentrations and lower response rates., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Several population pharmacokinetic (PPK) analyses of the anticancer drug imatinib have been performed to investigate different patient populations and covariate effects. The present analysis offers a systematic qualitative and quantitative summary and comparison of those. Its primary objective was to provide useful information for evaluating the expectedness of imatinib plasma concentration measurements in the frame of therapeutic drug monitoring. The secondary objective was to review clinically important concentration-effect relationships to provide help in evaluating the potential suitability of plasma concentration values. Nine PPK models describing total imatinib plasma concentration were identified. Parameter estimates were standardized to common covariate values whenever possible. Predicted median exposure (C min) was derived by simulations and ranged between models from 555 to 1388 ng/mL (grand median: 870 ng/mL and interquartile "reference" range: 520-1390 ng/mL). Covariates of potential clinical importance (up to 30% change in pharmacokinetic predicted by at least 1 model) included body weight, albumin, α1 acid glycoprotein, and white blood cell count. Various other covariates were included but were statistically not significant or seemed clinically less important or physiologically controversial. Concentration-response relationships had more importance below the average reference range and concentration-toxicity relationships above. Therapeutic drug monitoring-guided dosage adjustment seems justified for imatinib, but a formal predictive therapeutic range remains difficult to propose in the absence of prospective target concentration intervention trials. To evaluate the expectedness of a drug concentration measurement in practice, this review allows comparison of the measurement either to the average reference range or to a specific range accounting for individual patient characteristics. For future research, external PPK model validation or meta-model development should be considered.

Background: The imatinib trough plasma concentration (C(min)) correlates with clinical response in cancer patients. Therapeutic drug monitoring (TDM) of plasma C(min) is therefore suggested. In practice, however, blood sampling for TDM is often not performed at trough. The corresponding measurement is thus only remotely informative about C(min) exposure., Objectives: The objectives of this study were to improve the interpretation of randomly measured concentrations by using a Bayesian approach for the prediction of C(min), incorporating correlation between pharmacokinetic parameters, and to compare the predictive performance of this method with alternative approaches, by comparing predictions with actual measured trough levels, and with predictions obtained by a reference method, respectively., Methods: A Bayesian maximum a posteriori (MAP) estimation method accounting for correlation (MAP-ρ) between pharmacokinetic parameters was developed on the basis of a population pharmacokinetic model, which was validated on external data. Thirty-one paired random and trough levels, observed in gastrointestinal stromal tumour patients, were then used for the evaluation of the Bayesian MAP-ρ method: individual C(min) predictions, derived from single random observations, were compared with actual measured trough levels for assessment of predictive performance (accuracy and precision). The method was also compared with alternative approaches: classical Bayesian MAP estimation assuming uncorrelated pharmacokinetic parameters, linear extrapolation along the typical elimination constant of imatinib, and non-linear mixed-effects modelling (NONMEM) first-order conditional estimation (FOCE) with interaction. Predictions of all methods were finally compared with 'best-possible' predictions obtained by a reference method (NONMEM FOCE, using both random and trough observations for individual C(min) prediction)., Results: The developed Bayesian MAP-ρ method accounting for correlation between pharmacokinetic parameters allowed non-biased prediction of imatinib C(min) with a precision of ±30.7%. This predictive performance was similar for the alternative methods that were applied. The range of relative prediction errors was, however, smallest for the Bayesian MAP-ρ method and largest for the linear extrapolation method. When compared with the reference method, predictive performance was comparable for all methods. The time interval between random and trough sampling did not influence the precision of Bayesian MAP-ρ predictions., Conclusion: Clinical interpretation of randomly measured imatinib plasma concentrations can be assisted by Bayesian TDM. Classical Bayesian MAP estimation can be applied even without consideration of the correlation between pharmacokinetic parameters. Individual C(min) predictions are expected to vary less through Bayesian TDM than linear extrapolation. Bayesian TDM could be developed in the future for other targeted anticancer drugs and for the prediction of other pharmacokinetic parameters that have been correlated with clinical outcomes.