title: Validation of techniques for the prediction of carboplatin exposure: application of Bayesian methods.
abstract: OBJECTIVE
  Several methods have been developed for the prediction of carboplatin exposure to facilitate pharmacokinetic guided dosing. The aim of this study was to develop and validate sparse data Bayesian methods for the estimation of carboplatin exposure and to validate other commonly applied techniques, such as the Chatelut formula, the Sorensen limited sampling model, and the Calvert formula, in which glomerular filtration rate was estimated with the Cockcroft-Gault, the Jelliffe, and the recently proposed Wright formulas.
  
  
  METHODS
  Complete concentration-time curves were available for a total of 43 patients (45 courses) receiving carboplatin (265 or 400 mg/m2/day) in a 1-hour infusion for 4 consecutive days in combination with thiotepa and cyclophosphamide. A population two-compartment model was developed on an index set of 12 courses. The other 33 courses served as validation set. Bayesian estimates were generated with the population parameters by use of either one or two randomly timed samples or two samples at optimal time points determined with the D-optimality theory.
  
  
  RESULTS
  The Bayesian methods provided an accurate and precise prediction of the area under the concentration-time curve (bias <4% and precision <18%). The other formulas (Sorensen model, Chatelut, and Calvert with Jelliffe, Cockcroft-Gault, and Wright) resulted in a precision >18%, whereas the Jelliffe formula and the Sorensen model resulted in a bias >12%.
  
  
  CONCLUSIONS
  The applicability of a Bayesian method for the prediction of the carboplatin exposure by use of one or two samples without the necessity for exact timing of infusion duration and sampling was demonstrated. The Bayesian method may be very instrumental to execute pharmacokinetic guided dosing for carboplatin.
authors.affiliation: Department of Pharmacy and Pharmacology, The Netherlands Cancer Institute/Slotervaart Hospital, Amsterdam. APAHU@SLZ.NL
authors.forename: A D
authors.initials: AD
authors.lastname: Huitema
authors.forename: R A
authors.initials: RA
authors.lastname: Mathôt
authors.forename: M M
authors.initials: MM
authors.lastname: Tibben
authors.forename: J H
authors.initials: JH
authors.lastname: Schellens
authors.forename: S
authors.initials: S
authors.lastname: Rodenhuis
authors.forename: J H
authors.initials: JH
authors.lastname: Beijnen
mesh_terms: D000328:Adult; D000970:Antineoplastic Agents / Q000008:administration & dosage* / Q000097:blood / Q000493:pharmacokinetics*; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000493:pharmacokinetics; D019540:Area Under Curve; D001499:Bayes Theorem; D016190:Carboplatin / Q000008:administration & dosage* / Q000097:blood / Q000493:pharmacokinetics*; D003520:Cyclophosphamide / Q000493:pharmacokinetics; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007262:Infusions, Intravenous; D008297:Male; D008432:Mathematical Computing; D008875:Middle Aged; D015233:Models, Statistical; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D013852:Thiotepa / Q000493:pharmacokinetics
chemical_list: D000970:Antineoplastic Agents; D003520:Cyclophosphamide; D013852:Thiotepa; D016190:Carboplatin