Julie M Janssen1, Thomas P C Dorlo1, Jos H Beijnen1,2, Alwin D R Huitema1,3. 1. Department of Pharmacy and Pharmacology, The Netherlands Cancer Institute-Antoni van Leeuwenhoek, Amsterdam. 2. Department of Pharmaceutical Sciences, Utrecht University, Utrecht; and. 3. Department of Clinical Pharmacy, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Abstract
BACKGROUND: For oral anticancer drugs, trough concentration (Cmin) is usually used as a target in therapeutic drug monitoring (TDM). Recording of Cmin is highly challenging in outpatients, in whom there is typically a variability in sample collection time after dosing. Various methods are used to estimate Cmin from the collected samples. This simulation study aimed to evaluate the performance of 3 different methods in estimating the Cmin of 4 oral anticancer drugs for which TDM is regularly performed. METHODS: Plasma concentrations of abiraterone, dabrafenib, imatinib, and pazopanib at a random time (Ct,sim) and at the end of the dosing interval (Cmin,sim) were simulated from population pharmacokinetic models including 1000 patients, and the values were converted into simulated observed concentrations (Ct,sim,obs and Cmin,sim,obs) by adding a residual error. From Ct, sim,obs, Cmin was predicted (Cmin,pred) by the Bayesian estimation (method 1), taking the ratio of the Ct,sim,obs and typical population concentration and multiplying this ratio with the typical population value of Cmin,sim (method 2), and log-linear extrapolation (method 3). Target attainment was assessed by comparing Cmin,pred with the proposed pharmacokinetic targets related to efficacy and calculating the positive predictive and negative predictive values. RESULTS: The mean relative prediction error and root mean squared relative prediction error results showed that method 3 was out-performed by method 1 and 2. Target attainment was adequately predicted by all 3 methods (the respective positive predictive value of method 1, 2, and 3 was 92.1%, 92.5%, and 93.1% for abiraterone; 87.3%, 86.9%, and 99.1% for dabrafenib; 79.3%, 79.3%, and 75.9% for imatinib; and 72.5%, 73.5%, and 67.6% for pazopanib), indicating that dose adjustments were correctly predicted. CONCLUSIONS: Both method 1 and 2 provided accurate and precise individual Cmin,pred values. However, method 2 was easier to implement than method 1 to guide individual dose adjustments in TDM programs.
BACKGROUND: For oral anticancer drugs, trough concentration (Cmin) is usually used as a target in therapeutic drug monitoring (TDM). Recording of Cmin is highly challenging in outpatients, in whom there is typically a variability in sample collection time after dosing. Various methods are used to estimate Cmin from the collected samples. This simulation study aimed to evaluate the performance of 3 different methods in estimating the Cmin of 4 oral anticancer drugs for which TDM is regularly performed. METHODS: Plasma concentrations of abiraterone, dabrafenib, imatinib, and pazopanib at a random time (Ct,sim) and at the end of the dosing interval (Cmin,sim) were simulated from population pharmacokinetic models including 1000 patients, and the values were converted into simulated observed concentrations (Ct,sim,obs and Cmin,sim,obs) by adding a residual error. From Ct, sim,obs, Cmin was predicted (Cmin,pred) by the Bayesian estimation (method 1), taking the ratio of the Ct,sim,obs and typical population concentration and multiplying this ratio with the typical population value of Cmin,sim (method 2), and log-linear extrapolation (method 3). Target attainment was assessed by comparing Cmin,pred with the proposed pharmacokinetic targets related to efficacy and calculating the positive predictive and negative predictive values. RESULTS: The mean relative prediction error and root mean squared relative prediction error results showed that method 3 was out-performed by method 1 and 2. Target attainment was adequately predicted by all 3 methods (the respective positive predictive value of method 1, 2, and 3 was 92.1%, 92.5%, and 93.1% for abiraterone; 87.3%, 86.9%, and 99.1% for dabrafenib; 79.3%, 79.3%, and 75.9% for imatinib; and 72.5%, 73.5%, and 67.6% for pazopanib), indicating that dose adjustments were correctly predicted. CONCLUSIONS: Both method 1 and 2 provided accurate and precise individual Cmin,pred values. However, method 2 was easier to implement than method 1 to guide individual dose adjustments in TDM programs.
Authors: Neeltje Steeghs; Alwin D R Huitema; Stefanie L Groenland; Remy B Verheijen; Markus Joerger; Ron H J Mathijssen; Alex Sparreboom; Jos H Beijnen; Jan H Beumer Journal: Clin Cancer Res Date: 2021-09-21 Impact factor: 12.531
Authors: René J Boosman; Merel Jebbink; Wouter B Veldhuis; Stefanie L Groenland; Bianca A M H van Veggel; Pim Moeskops; Adrianus J de Langen; Jos H Beijnen; Egbert F Smit; Alwin D R Huitema; Neeltje Steeghs Journal: Pharm Res Date: 2022-08-17 Impact factor: 4.580
Authors: Stefanie L Groenland; Dieuwertje R Geel; Julie M Janssen; Niels de Vries; Hilde Rosing; Jos H Beijnen; Jacobus A Burgers; Egbert F Smit; Alwin D R Huitema; Neeltje Steeghs Journal: Clin Pharmacol Ther Date: 2020-08-19 Impact factor: 6.875