This Article Full Text Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Salinger, D. H. Articles by Vicini, P. Search for Related Content PubMed PubMed Citation Articles by Salinger, D. H. Articles by Vicini, P.

Real-time Dose Adjustment of Cyclophosphamide in a Preparative Regimen for Hematopoietic Cell Transplant: A Bayesian Pharmacokinetic Approach

Authors' Affiliations: Departments of ¹ Pharmacy, ² Pharmaceutics, ³ Medicine, and ⁴ Bioengineering, University of Washington, Seattle, Washington and ⁵ Fred Hutchinson Cancer Research Center, Seattle, Washington

Requests for reprints: Paolo Vicini, Department of Bioengineering, University of Washington, Box 352255, Seattle, WA 98195-2255. Phone: 206-616-1133; Fax: 206-543-3081; E-mail: vicini{at}u.washington.edu.

Purpose: Dose-related toxicity of cyclophosphamide may be reduced and therapeutic efficacy may be improved by pharmacokinetic sampling and dose adjustment to achieve a target area under the curve (AUC) for two of its metabolites, hydroxycyclophosphamide (HCY) and carboxyethylphosphoramide mustard (CEPM). To facilitate real-time dose adjustment, we developed open-source code within the statistical software R that incorporates individual data into a population pharmacokinetic model.

Experimental Design: Dosage prediction performance was compared to that obtained with nonlinear mixed-effects modeling using NONMEM in 20 cancer patients receiving cyclophosphamide. Bayesian estimation of individual pharmacokinetic parameters was accomplished from limited (i.e., five samples over 0-16 hours) sampling of plasma HCY and CEPM after the initial cyclophosphamide dose. Conditional on individual pharmacokinetics, simulations of the AUC of both HCY and CEPM were provided for a range of second doses (i.e., 0-100 mg/kg cyclophosphamide).

Results: The results compared favorably with NONMEM and returned accurate predictions for AUCs of HCY and CEPM with comparable mean absolute prediction error and root mean square prediction error. With our method, the mean absolute prediction error and root mean square prediction error of AUC CEPM were 11.0% and 12.8% and AUC HCY were 31.7% and 44.8%, respectively.

Conclusions: We developed dose adjustment software that potentially can be used to adjust cyclophosphamide dosing in a clinical setting, thus expanding the opportunity for pharmacokinetic individualization of cyclophosphamide. The software is simple to use (requiring no programming experience), reads individual patient data directly from an Excel spreadsheet, and runs in less than 5 minutes on a desktop PC.

This article has been cited by other articles:

				R. A. Miksad, M. Gonen, T. J. Lynch, and T. G. Roberts Jr Interpreting Trial Results in Light of Conflicting Evidence: A Bayesian Analysis of Adjuvant Chemotherapy for Non-Small-Cell Lung Cancer J. Clin. Oncol., May 1, 2009; 27(13): 2245 - 2252. [Abstract] [Full Text] [PDF]

				J. S. McCune, D. H. Salinger, P. Vicini, C. Oglesby, D. K. Blough, and J. R. Park Population Pharmacokinetics of Cyclophosphamide and Metabolites in Children With Neuroblastoma: A Report From the Children's Oncology Group J. Clin. Pharmacol., January 1, 2009; 49(1): 88 - 102. [Abstract] [Full Text] [PDF]

				G B McDonald and D Frieze A problem-oriented approach to liver disease in oncology patients Gut, July 1, 2008; 57(7): 987 - 1003. [Full Text] [PDF]