Das Saibal, Fleming Denise H, Mathew Binu S, Winston A Blessed, Prabhakar Appaswamy T, Alexander Mathew
a Department of Pharmacology and Clinical Pharmacology , Christian Medical College , Vellore , Tamil Nadu , India.
b Department of Neurological Sciences , Christian Medical College , Vellore , Tamil Nadu , India.
Hosp Pract (1995). 2017 Apr;45(2):46-50. doi: 10.1080/21548331.2017.1296318. Epub 2017 Feb 22.
Carbamazepine (CBZ) is a commonly used anti-epileptic in rural hospitals in India. These hospitals lack the facilities to measure CBZ concentration; however, in larger hospitals this is performed using high performance liquid chromatography (HPLC). Dried blood spot (DBS) represents a feasible matrix for safe transportation by post/courier. This study was to determine whether the concentration of CBZ in serum can be predicted from that measured in DBS using an inexpensive HPLC method and inexpensive standard filter paper.
CBZ in serum and DBS from 80 epileptic patients were measured using a validated HPLC assay. The data was then randomly divided into two groups; simple Deming regression was performed with the first group and validation was performed using the second.
There was a good correlation between the serum and DBS concentrations (r = 0.932) in the first group. The regression equation obtained was: predicted serum concentration = DBS concentration x 0.83 + 1.09. In the validation group, the correlation between the predicted and actual serum concentrations was also good (r = 0.958), and the mean difference between them was only 0.28 μg/ml (p = 0.8062). The imprecision and bias in both the groups were acceptable.
Using inexpensive materials, serum CBZ concentrations can be accurately predicted from DBS specimens. This method can be recommended for the therapeutic drug monitoring of CBZ in resource-limited settings.
卡马西平(CBZ)是印度农村医院常用的抗癫痫药物。这些医院缺乏测量CBZ浓度的设备;然而,在较大的医院中,这是通过高效液相色谱法(HPLC)进行的。干血斑(DBS)是一种可行的基质,便于通过邮政/快递安全运输。本研究旨在确定是否可以使用廉价的HPLC方法和廉价的标准滤纸,根据DBS中测得的浓度来预测血清中CBZ的浓度。
采用经过验证的HPLC测定法测量80例癫痫患者血清和DBS中的CBZ。然后将数据随机分为两组;对第一组进行简单的Deming回归,并使用第二组进行验证。
第一组血清和DBS浓度之间存在良好的相关性(r = 0.932)。得到的回归方程为:预测血清浓度 = DBS浓度×0.83 + 1.09。在验证组中,预测血清浓度与实际血清浓度之间的相关性也很好(r = 0.958),两者之间的平均差异仅为0.28μg/ml(p = 0.8062)。两组的不精密度和偏差均可接受。
使用廉价材料,可以从DBS标本中准确预测血清CBZ浓度。该方法可推荐用于资源有限环境下CBZ的治疗药物监测。