Thomas Fabienne, Séronie-Vivien Sophie, Gladieff Laurence, Dalenc Florence, Durrand Valérie, Malard Laurence, Lafont Thierry, Poublanc Muriel, Bugat Roland, Chatelut Etienne
Department of Clinical Biology and EA3035, Institut Claudius-Regaud, Toulouse, France.
Clin Pharmacokinet. 2005;44(12):1305-16. doi: 10.2165/00003088-200544120-00009.
The individual dosing of drugs that are mainly eliminated unchanged in the urine is made possible by assessing renal function. Most of the methods used are based on serum creatinine (SCr) levels. Cystatin C (CysC) has been proposed as an alternative endogenous marker of the glomerular filtration rate (GFR). Carboplatin is one of the drugs for which elimination is most dependent on the GFR. A prospective clinical trial including 45 patients was conducted to assess the value of serum CysC as a predictor of carboplatin clearance (CL).
The patients were receiving carboplatin as part of established protocols. Carboplatin was administered as a daily 60-minute infusion at doses ranging from 290 to 1700mg. A population pharmacokinetic analysis was performed using the nonlinear mixed effect modelling NONMEM program according to a two-compartment pharmacokinetic model.
Data from 30 patients were used to test the relationships between carboplatin CL and morphological, biological and demographic covariates previously proposed for prediction of the GFR. The interindividual variability of carboplatin CL decreased from 31% (no covariate) to 14% by taking into account five covariates (SCr, CysC, bodyweight [BW], age and sex). Prospective evaluation of these relationships using the data from the other 15 patients confirmed that the best equation to predict carboplatin CL was based on these five covariates, with a mean absolute percentage error of 13% as an assessment of precision. NONMEM analysis of the whole dataset (n = 45 patients) was performed. The best covariate equation corresponding to the overall analysis was: CL (mL/min) = 110 x (SCr/75)-0.512 x (CysC/1.0)-0.327 x (BW/65)0.474 x (age/56)-0.387 x 0.854sex, with SCr in micromol/L, CysC in mg/L, BW in kilograms, age in years and sex = 0 if male and 1 if female. To put the value of CysC as an endogenous marker of the GFR into perspective, covariate equations without SCr were also evaluated; a better prediction was obtained by considering CysC together with age and BW (interindividual variability of 16.6% vs 23.3% for CysC alone).
CysC is a marker of drug elimination that is at least as good as SCr for predicting carboplatin CL. The model based on five covariates was superior to those based on only four covariates (with BW, age and sex combined with either SCr or CysC), indicating that CysC and SCr are not completely redundant to each other. Further pharmacokinetic evaluation is needed to determine whether SCr or CysC is the better marker of renal elimination of other drugs.
通过评估肾功能,可以实现对主要经尿液以原形排出的药物进行个体化给药。大多数使用的方法基于血清肌酐(SCr)水平。胱抑素C(CysC)已被提议作为肾小球滤过率(GFR)的替代内源性标志物。卡铂是消除过程最依赖于GFR的药物之一。进行了一项纳入45例患者的前瞻性临床试验,以评估血清CysC作为卡铂清除率(CL)预测指标的价值。
患者按照既定方案接受卡铂治疗。卡铂以每日1次、60分钟静脉滴注的方式给药,剂量范围为290至1700mg。根据二室药代动力学模型,使用非线性混合效应建模NONMEM程序进行群体药代动力学分析。
30例患者的数据用于测试卡铂CL与先前提出的用于预测GFR的形态学、生物学和人口统计学协变量之间的关系。考虑5个协变量(SCr、CysC、体重[BW]、年龄和性别)后,卡铂CL的个体间变异性从31%(无协变量)降至14%。使用另外15例患者的数据对这些关系进行前瞻性评估,证实预测卡铂CL的最佳方程基于这5个协变量,平均绝对百分比误差为13%作为精度评估。对整个数据集(n = 45例患者)进行NONMEM分析。总体分析对应的最佳协变量方程为:CL(mL/min)= 110×(SCr/75)-0.512×(CysC/1.0)-0.327×(BW/65)0.474×(年龄/56)-0.387×0.854性别,其中SCr以微摩尔/升为单位,CysC以毫克/升为单位,BW以千克为单位,年龄以岁为单位,男性性别=0,女性性别=1。为了正确看待CysC作为GFR内源性标志物的价值,还评估了不含SCr的协变量方程;将CysC与年龄和BW一起考虑可获得更好的预测(单独CysC时个体间变异性为23.3%,联合考虑时为16.6%)。
CysC是一种药物消除标志物,在预测卡铂CL方面至少与SCr一样好。基于5个协变量的模型优于基于仅4个协变量(BW、年龄和性别与SCr或CysC联合)的模型,表明CysC和SCr并非完全相互冗余。需要进一步进行药代动力学评估,以确定SCr或CysC是否是其他药物肾脏消除的更好标志物。