Population pharmacokinetic–pharmacodynamic modeling and model-based prediction of docetaxel-induced neutropenia in Japanese patients with non-small cell lung cancer

Masato Fukae, Yoshimasa Shiraishi, Takeshi Hirota, Yuka Sasaki, Mika Yamahashi, Koichi Takayama, Yoichi Nakanishi, Ichiro Ieiri

研究成果: ジャーナルへの寄稿記事

7 引用 (Scopus)

抄録

Purpose: Docetaxel is used to treat many cancers, and neutropenia is the dose-limiting factor for its clinical use. A population pharmacokinetic–pharmacodynamic (PK–PD) model was introduced to predict the development of docetaxel-induced neutropenia in Japanese patients with non-small cell lung cancer (NSCLC). Methods: Forty-seven advanced or recurrent Japanese patients with NSCLC were enrolled. Patients received 50 or 60 mg/m2 docetaxel as monotherapy, and blood samples for a PK analysis were collected up to 24 h after its infusion. Laboratory tests including absolute neutrophil count data and demographic information were used in population PK–PD modeling. The model was built by NONMEM 7.2 with a first-order conditional estimation using an interaction method. Based on the final model, a Monte Carlo simulation was performed to assess the impact of covariates on and the predictability of neutropenia. Results: A three-compartment model was employed to describe PK data, and the PK model adequately described the docetaxel concentrations observed. Serum albumin (ALB) was detected as a covariate of clearance (CL): CL (L/h) = 32.5 × (ALB/3.6)0.965 × (WGHT/70)3/4. In population PK–PD modeling, a modified semi-mechanistic myelosuppression model was applied, and characterization of the time course of neutrophil counts was adequate. The covariate selection indicated that α1-acid glycoprotein (AAG) was a predictor of neutropenia. The model-based simulation also showed that ALB and AAG negatively correlated with the development of neutropenia and that the time course of neutrophil counts was predictable. Conclusion: The developed model may facilitate the prediction and care of docetaxel-induced neutropenia.

元の言語英語
ページ(範囲)1013-1023
ページ数11
ジャーナルCancer chemotherapy and pharmacology
78
発行部数5
DOI
出版物ステータス出版済み - 11 1 2016

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docetaxel
Neutropenia
Non-Small Cell Lung Carcinoma
Cells
Population
Neutrophils
Albumins
Serum Albumin
Glycoproteins
Demography

All Science Journal Classification (ASJC) codes

  • Oncology
  • Toxicology
  • Pharmacology
  • Cancer Research
  • Pharmacology (medical)

これを引用

Population pharmacokinetic–pharmacodynamic modeling and model-based prediction of docetaxel-induced neutropenia in Japanese patients with non-small cell lung cancer. / Fukae, Masato; Shiraishi, Yoshimasa; Hirota, Takeshi; Sasaki, Yuka; Yamahashi, Mika; Takayama, Koichi; Nakanishi, Yoichi; Ieiri, Ichiro.

:: Cancer chemotherapy and pharmacology, 巻 78, 番号 5, 01.11.2016, p. 1013-1023.

研究成果: ジャーナルへの寄稿記事

Fukae, Masato ; Shiraishi, Yoshimasa ; Hirota, Takeshi ; Sasaki, Yuka ; Yamahashi, Mika ; Takayama, Koichi ; Nakanishi, Yoichi ; Ieiri, Ichiro. / Population pharmacokinetic–pharmacodynamic modeling and model-based prediction of docetaxel-induced neutropenia in Japanese patients with non-small cell lung cancer. :: Cancer chemotherapy and pharmacology. 2016 ; 巻 78, 番号 5. pp. 1013-1023.
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title = "Population pharmacokinetic–pharmacodynamic modeling and model-based prediction of docetaxel-induced neutropenia in Japanese patients with non-small cell lung cancer",
abstract = "Purpose: Docetaxel is used to treat many cancers, and neutropenia is the dose-limiting factor for its clinical use. A population pharmacokinetic–pharmacodynamic (PK–PD) model was introduced to predict the development of docetaxel-induced neutropenia in Japanese patients with non-small cell lung cancer (NSCLC). Methods: Forty-seven advanced or recurrent Japanese patients with NSCLC were enrolled. Patients received 50 or 60 mg/m2 docetaxel as monotherapy, and blood samples for a PK analysis were collected up to 24 h after its infusion. Laboratory tests including absolute neutrophil count data and demographic information were used in population PK–PD modeling. The model was built by NONMEM 7.2 with a first-order conditional estimation using an interaction method. Based on the final model, a Monte Carlo simulation was performed to assess the impact of covariates on and the predictability of neutropenia. Results: A three-compartment model was employed to describe PK data, and the PK model adequately described the docetaxel concentrations observed. Serum albumin (ALB) was detected as a covariate of clearance (CL): CL (L/h) = 32.5 × (ALB/3.6)0.965 × (WGHT/70)3/4. In population PK–PD modeling, a modified semi-mechanistic myelosuppression model was applied, and characterization of the time course of neutrophil counts was adequate. The covariate selection indicated that α1-acid glycoprotein (AAG) was a predictor of neutropenia. The model-based simulation also showed that ALB and AAG negatively correlated with the development of neutropenia and that the time course of neutrophil counts was predictable. Conclusion: The developed model may facilitate the prediction and care of docetaxel-induced neutropenia.",
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T1 - Population pharmacokinetic–pharmacodynamic modeling and model-based prediction of docetaxel-induced neutropenia in Japanese patients with non-small cell lung cancer

AU - Fukae, Masato

AU - Shiraishi, Yoshimasa

AU - Hirota, Takeshi

AU - Sasaki, Yuka

AU - Yamahashi, Mika

AU - Takayama, Koichi

AU - Nakanishi, Yoichi

AU - Ieiri, Ichiro

PY - 2016/11/1

Y1 - 2016/11/1

N2 - Purpose: Docetaxel is used to treat many cancers, and neutropenia is the dose-limiting factor for its clinical use. A population pharmacokinetic–pharmacodynamic (PK–PD) model was introduced to predict the development of docetaxel-induced neutropenia in Japanese patients with non-small cell lung cancer (NSCLC). Methods: Forty-seven advanced or recurrent Japanese patients with NSCLC were enrolled. Patients received 50 or 60 mg/m2 docetaxel as monotherapy, and blood samples for a PK analysis were collected up to 24 h after its infusion. Laboratory tests including absolute neutrophil count data and demographic information were used in population PK–PD modeling. The model was built by NONMEM 7.2 with a first-order conditional estimation using an interaction method. Based on the final model, a Monte Carlo simulation was performed to assess the impact of covariates on and the predictability of neutropenia. Results: A three-compartment model was employed to describe PK data, and the PK model adequately described the docetaxel concentrations observed. Serum albumin (ALB) was detected as a covariate of clearance (CL): CL (L/h) = 32.5 × (ALB/3.6)0.965 × (WGHT/70)3/4. In population PK–PD modeling, a modified semi-mechanistic myelosuppression model was applied, and characterization of the time course of neutrophil counts was adequate. The covariate selection indicated that α1-acid glycoprotein (AAG) was a predictor of neutropenia. The model-based simulation also showed that ALB and AAG negatively correlated with the development of neutropenia and that the time course of neutrophil counts was predictable. Conclusion: The developed model may facilitate the prediction and care of docetaxel-induced neutropenia.

AB - Purpose: Docetaxel is used to treat many cancers, and neutropenia is the dose-limiting factor for its clinical use. A population pharmacokinetic–pharmacodynamic (PK–PD) model was introduced to predict the development of docetaxel-induced neutropenia in Japanese patients with non-small cell lung cancer (NSCLC). Methods: Forty-seven advanced or recurrent Japanese patients with NSCLC were enrolled. Patients received 50 or 60 mg/m2 docetaxel as monotherapy, and blood samples for a PK analysis were collected up to 24 h after its infusion. Laboratory tests including absolute neutrophil count data and demographic information were used in population PK–PD modeling. The model was built by NONMEM 7.2 with a first-order conditional estimation using an interaction method. Based on the final model, a Monte Carlo simulation was performed to assess the impact of covariates on and the predictability of neutropenia. Results: A three-compartment model was employed to describe PK data, and the PK model adequately described the docetaxel concentrations observed. Serum albumin (ALB) was detected as a covariate of clearance (CL): CL (L/h) = 32.5 × (ALB/3.6)0.965 × (WGHT/70)3/4. In population PK–PD modeling, a modified semi-mechanistic myelosuppression model was applied, and characterization of the time course of neutrophil counts was adequate. The covariate selection indicated that α1-acid glycoprotein (AAG) was a predictor of neutropenia. The model-based simulation also showed that ALB and AAG negatively correlated with the development of neutropenia and that the time course of neutrophil counts was predictable. Conclusion: The developed model may facilitate the prediction and care of docetaxel-induced neutropenia.

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