CPT-11 Pharmacokinetics Stepwise regression models Simulation studies Area under the curve;
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Purpose: We developed limited sampling models (LSMs) for predicting the area under the curve (AUC) of irinotecan (CPT-11) and its metabolites SN-38 and SN-38 glucuronide (SN-38G). Patients and methods: Regression models were developed based on data from a phase I clinical trial involving 34 patients with advanced solid tumor malignancies who received CPT-11 as a 90-min infusion on an every 3-week dosing schedule. Multiple stepwise regression procedures were supplemented by all possible subsets regression analysis. Alternative clinically based and empirically derived LSMs were determined via model validation assessment including bootstrap simulation testing. Results: The best LSMs for CPT-11 AUC included concentrations recorded at the end of infusion and 4 h later with an option to include a blood draw at 7.5 h from infusion start. For SN-38 and SN-38G AUC, optimal LSMs included the additional metabolite concentration at 48 h after infusion. The LSMs were able to predict most patient AUC values to within 10% of the true value. Conclusion: CPT-11 AUC can be modeled with acceptable accuracy using only two or three plasma concentration time-points. A variety of LSM alternatives provided comparable accuracy in predicting AUC. Given the wide variety of LSM alternatives, clinical considerations and patient burden become more important performance parameters than statistical considerations for the choice of time-points in constructing LSMs.
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3D Imaging LLC, Little Rock, AR 72205 USA3D Imaging LLC, Little Rock, AR 72205 USA
Apana, Scott M.
Anderson, Lawrence W.
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US FDA, Ctr Drug Evaluat & Res, Silver Spring, MD USA3D Imaging LLC, Little Rock, AR 72205 USA
Anderson, Lawrence W.
Berridge, Marc S.
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3D Imaging LLC, Little Rock, AR 72205 USA
Univ Arkansas Med Sci, Dept Radiol, Little Rock, AR 72205 USA
Univ Arkansas Med Sci, Dept Pharmaceut Sci, Little Rock, AR 72205 USA3D Imaging LLC, Little Rock, AR 72205 USA
机构:
E China Normal Univ, Dept Chem, Shanghai 200062, Peoples R ChinaE China Normal Univ, Dept Chem, Shanghai 200062, Peoples R China
Yu, Shanbao
Huang, Qing-Qing
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E China Normal Univ, Inst Drug Discovery & Dev, iAIR, Shanghai 200062, Peoples R ChinaE China Normal Univ, Dept Chem, Shanghai 200062, Peoples R China
Huang, Qing-Qing
Luo, Yu
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E China Normal Univ, Dept Chem, Shanghai 200062, Peoples R ChinaE China Normal Univ, Dept Chem, Shanghai 200062, Peoples R China
Luo, Yu
Lu, Wei
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E China Normal Univ, Inst Drug Discovery & Dev, iAIR, Shanghai 200062, Peoples R ChinaE China Normal Univ, Dept Chem, Shanghai 200062, Peoples R China