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Population Pharmacokinetic-Pharmacodynamic Model for Neutropenia with Patient Subgroup Identification: Comparison across Anticancer Drugs

Authors' Affiliations: ¹ Department of Clinical Pharmacy, Institute of Pharmacy, Freie Universitaet Berlin, Germany; ² Department of Clinical Pharmacy, Faculty of Pharmacy, Martin-Luther-Universitaet Halle-Wittenberg, Germany; ³ Department of Pharmaceutical Biosciences, Uppsala University, Sweden; and ⁴ Institut Claudius-Regaud, Toulouse, France

Requests for reprints: Charlotte Kloft, Department of Clinical Pharmacy, Institute of Pharmacy, Freie Universitaet Berlin, Kelchstrasse 31, 12169 Berlin, Germany. Phone: 49-30-83850628; Fax: 49-30-83850711; E-mail: ckloft{at}zedat.fu-berlin.de.

Purpose: Cancer chemotherapy, although based on body surface area, often causes unpredictable myelosuppression, especially severe neutropenia. The aim of this study was to evaluate qualitatively and quantitatively the influence of patient-specific characteristics on the neutrophil concentration-time course, to identify patient subgroups, and to compare covariates on system-related pharmacodynamic variable between drugs.

Experimental Design: Drug and neutrophil concentration, demographic, and clinical chemistry data of several trials with docetaxel (637 patients), paclitaxel (45 patients), etoposide (71 patients), or topotecan (191 patients) were included in the covariate analysis of a physiology-based pharmacokinetic-pharmacodynamic neutropenia model. Comparisons of covariate relations across drugs were made.

Results: A population model incorporating four to five relevant patient factors for each drug to explain variability in the degree and duration of neutropenia has been developed. Sex, previous anticancer therapy, performance status, height, binding partners, or liver enzymes influenced system-related variables and ₁-acid glycoprotein, albumin, bilirubin, concomitant cytotoxic agents, or administration route changed drug-specific variables. Overall, female and pretreated patients had a lower baseline neutrophil concentration. Across-drug comparison revealed that several covariates (e.g., age) had minor (clinically irrelevant) influences but consistently shifted the pharmacodynamic variable in the same direction.

Conclusions: These mechanistic models, including patient characteristics that influence drug-specific parameters, form the rationale basis for more tailored dosing of individual patients or subgroups to minimize the risk of infection and thus might contribute to a more successful therapy. In addition, nonsignificant or clinically irrelevant relations on system-related parameters suggest that these covariates could be negligible in clinical trails and daily use.

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