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Exposure–outcome analysis in depressed patients treated with paroxetine using population pharmacokinetics

Overview of attention for article published in Drug Design, Development and Therapy, September 2015
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Title
Exposure–outcome analysis in depressed patients treated with paroxetine using population pharmacokinetics
Published in
Drug Design, Development and Therapy, September 2015
DOI 10.2147/dddt.s84718
Pubmed ID
Authors

Jung-Ryul Kim, Hye In Woo, Mi-Ryung Chun, Shinn-Won Lim, Hae Deun Kim, Han Sung Na, Myeon Woo Chung, Woojae Myung, Soo-Youn Lee, Doh Kwan Kim

Abstract

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.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 16%
Student > Bachelor 5 14%
Student > Master 4 11%
Researcher 3 8%
Other 3 8%
Other 6 16%
Unknown 10 27%
Readers by discipline Count As %
Medicine and Dentistry 10 27%
Psychology 7 19%
Pharmacology, Toxicology and Pharmaceutical Science 6 16%
Biochemistry, Genetics and Molecular Biology 3 8%
Computer Science 1 3%
Other 1 3%
Unknown 9 24%