Exposure–outcome analysis in depressed patients treated with paroxetine using population pharmacokinetics
Received 16 March 2015
Accepted for publication 16 June 2015
Published 16 September 2015 Volume 2015:9 Pages 5247—5254
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Professor Shu-Feng Zhou
Jung-Ryul Kim,1 Hye In Woo,2 Mi-Ryung Chun,3 Shinn-Won Lim,4 Hae Deun Kim,5 Han Sung Na,5 Myeon Woo Chung,5 Woojae Myung,6 Soo-Youn Lee,1,3 Doh Kwan Kim6
1Department of Clinical Pharmacology and Therapeutics, Samsung Medical Center, Seoul, 2Department of Laboratory Medicine, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, 3Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 4Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Seoul, 5Clinical Research Division, Toxicological Evaluation and Research Department, National Institute of Food and Drug Safety Evaluation, Ministry of Food and Drug Safety, Osong, Chungcheongbuk-do, 6Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
Purpose: 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.
Patients and methods: 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.
Results: 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.
Conclusion: In depressed patients treated with paroxetine, TDM may be of limited value for individualization of treatment.
Keywords: exposure–outcome relationship, paroxetine, therapeutic drug monitoring, population pharmacokinetics, NONMEM
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