Background: Therapeutic drug monitoring of carboplatin is based on its unbound clearance (CLU) determined by Bayesian analysis on unbound (U) concentrations. However, the ultrafiltration of plasma samples presents technical and time constraints. Therefore, this study aims to estimate CLU using total plasma (P) concentrations.
Methods: U and P concentration data of 407 patients were obtained from 2 clinical studies in which actual CLU had been determined for each patient. The patients were then split into development (277 patients) and prospective data sets (130 patients). Two approaches were evaluated. PK-model-only approach: a 3-compartment pharmacokinetic (PK) model based on U and P concentrations and taking into account the protein binding process was developed. The model with patient covariates was also evaluated. Linear regression approach: an equation (CLU = aCLP + b) was obtained by linear regression analysis between actual CLU and CLP, which is the total plasma clearance obtained by analyzing P concentrations according to a 2-compartment PK model. Predictive performance was then assessed within the prospective data set by estimating CLU from P concentrations using each approach and computing the relative percentage error (PE) between estimated CLU and actual CLU.
Results: The linear regression equation was CLU (L/h) = 1.15 CLP (L/h) + 0.13. The mean PE (MPE) between CLU (estimated using the equation) and the actual CLU was +1.2% (ranging from -31% to +33%) and the mean absolute PE (MAPE) was 9.7%. With the 3-compartment PK model, the MPE was +2.3% (ranging from -41% to +31%) and the MAPE was 11.1%. Inclusion of covariates in the 3-compartment model did not improve the estimation of CLU [MPE = +6.3% (from -33% to +37%); MAPE = 11.4%].
Conclusions: The linear equation gives a relatively good estimation of CLU based on P concentrations, making PK-based carboplatin dose adaptation possible for centers without ultrafiltration facilities.
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