Kim Jung-Ryul, Woo Hye In, Chun Mi-Ryung, Lim Shinn-Won, Kim Hae Deun, Na Han Sung, Chung Myeon Woo, Myung Woojae, Lee Soo-Youn, Kim Doh Kwan
Department of Clinical Pharmacology and Therapeutics, Samsung Medical Center, Seoul, Republic of Korea.
Department of Laboratory Medicine, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, Republic of Korea.
Drug Des Devel Ther. 2015 Sep 16;9:5247-54. doi: 10.2147/DDDT.S84718. eCollection 2015.
This study investigated population pharmacokinetics of paroxetine, and then performed an integrated analysis of exposure and clinical outcome using population pharmacokinetic parameter estimates in depressed patients treated with paroxetine.
A total of 271 therapeutic drug monitoring (TDM) data were retrospectively collected from 127 psychiatric outpatients. A population nonlinear mixed-effects modeling approach was used to describe serum concentrations of paroxetine. For 83 patients with major depressive disorder, the treatment response rate and the incidence of adverse drug reaction (ADR) were characterized by logistic regression using daily dose or area under the concentration-time curve (AUC) estimated from the final model as a potential exposure predictor.
One compartment model was developed. The apparent clearance of paroxetine was affected by age as well as daily dose administered at steady-state. Overall treatment response rate was 72%, and the incidence of ADR was 30%. The logistic regression showed that exposure predictors were not associated with treatment response or ADR in the range of dose commonly used in routine practice. However, the incidence of ADR increased with the increase of daily dose or AUC for the patients with multiple concentrations.
In depressed patients treated with paroxetine, TDM may be of limited value for individualization of treatment.
本研究调查了帕罗西汀的群体药代动力学,然后使用帕罗西汀治疗的抑郁症患者的群体药代动力学参数估计值对暴露量和临床结局进行综合分析。
回顾性收集了127名精神科门诊患者的271份治疗药物监测(TDM)数据。采用群体非线性混合效应建模方法描述帕罗西汀的血清浓度。对于83名重度抑郁症患者,使用最终模型估计的每日剂量或浓度-时间曲线下面积(AUC)作为潜在暴露预测因子,通过逻辑回归来表征治疗反应率和药物不良反应(ADR)的发生率。
建立了一室模型。帕罗西汀的表观清除率受年龄以及稳态时每日给药剂量的影响。总体治疗反应率为72%,ADR发生率为30%。逻辑回归显示,在常规实践中常用的剂量范围内,暴露预测因子与治疗反应或ADR无关。然而,对于有多个浓度数据的患者,ADR的发生率随每日剂量或AUC的增加而增加。
在接受帕罗西汀治疗的抑郁症患者中,TDM对个体化治疗的价值可能有限。