Shen Meiyu, Schilder Russell J, Obasaju Coleman, Gallo James M
Department of Pharacology, Fox Chase Cancer Center, Philadelphia, PA 19111, USA.
Cancer Chemother Pharmacol. 2002 Sep;50(3):243-50. doi: 10.1007/s00280-002-0490-y. Epub 2002 Jul 16.
By means of a nonlinear mixed effect modeling technique, a population pharmacokinetic (PK) model was developed to evaluate the effects of a variety of covariates on clearance and other pharmacokinetic parameters of ultrafilterable carboplatin administered in high-dose combination regimens with peripheral blood stem cell support. In addition, single-sample and two-sample limited sampling models (LSMs) were derived to estimate carboplatin's AUC that could be used in the design of drug dosing regimens.
A total of 44 female patients with advanced ovarian cancer participated in two phase I studies. All 44 patients received a high-dose carboplatin chemotherapy with other anticancer drugs. A population PK model was applied to the plasma concentration-time data of ultrafilterable carboplatin using the NONMEM and Xpose computer programs. The Xpose program utilized a general additive modeling technique to identify significant patient covariates and PK parameter relationships. The resultant PK model was validated using a bootstrap method. Stepwise linear regression analyses were used to develop LSMs based on the correlation between carboplatin's AUC and plasma concentrations.
The best structural covariate-free model for high-dose carboplatin was a linear two-compartment model with an exponential error model to account for intersubject variability and a CCV error model to account for intrasubject variability. Subsequently, a final covariate model for clearance (l/min) was obtained as follows: TVCL=0.101+0011*(WT-62.35)-0.0658*(SCR-0.65) where WT is body weight (kg) and SCR is serum creatinine (mg/dl). Both WT and SCR were found to significantly influence carboplatin's total clearance. It was determined that the best single-sample LSM was AUC(LSM)=0.553*C(240min) ( r=0.998).
Both a population PK model and a LSM for high-dose carboplatin were developed following its administration in combination chemotherapeutic regimens with peripheral blood stem cell support. In both cases, the models performed well when analyzed in the context of the retrospective and bootstrap analyses. Prospective studies in ovarian cancer patients should be conducted to further tailor the current models.
采用非线性混合效应建模技术,建立群体药代动力学(PK)模型,以评估多种协变量对在高剂量联合方案中给予外周血干细胞支持的可超滤卡铂清除率及其他药代动力学参数的影响。此外,推导单样本和两样本有限采样模型(LSM)以估算卡铂的AUC,可用于药物给药方案的设计。
共有44例晚期卵巢癌女性患者参与两项I期研究。所有44例患者均接受高剂量卡铂化疗及其他抗癌药物治疗。使用NONMEM和Xpose计算机程序将群体PK模型应用于可超滤卡铂的血浆浓度-时间数据。Xpose程序利用一般加法建模技术识别显著的患者协变量和PK参数关系。使用自助法对所得PK模型进行验证。基于卡铂AUC与血浆浓度之间的相关性,采用逐步线性回归分析来建立LSM。
高剂量卡铂的最佳无结构协变量模型是线性二室模型,采用指数误差模型来解释个体间变异性,采用CCV误差模型来解释个体内变异性。随后,得到清除率(l/min)的最终协变量模型如下:TVCL = 0.101 + 0.011×(WT - 62.35) - 0.0658×(SCR - 0.65),其中WT为体重(kg),SCR为血清肌酐(mg/dl)。发现WT和SCR均显著影响卡铂的总清除率。确定最佳单样本LSM为AUC(LSM)=0.553×C(240min)(r = 0.998)。
在高剂量卡铂与外周血干细胞支持联合化疗方案给药后,建立了群体PK模型和LSM。在回顾性分析和自助法分析的背景下分析时,这两种模型均表现良好。应在卵巢癌患者中进行前瞻性研究,以进一步完善当前模型。