Evidence map›Paper›PMID 19841156›Full record

Trial reportJournal of clinical pharmacology2010

Effect of age, weight, and CYP2C19 genotype on escitalopram exposure.

Yuyan Jin, Bruce G Pollock, Ellen Frank, Giovanni B Cassano, Paola Rucci, Daniel J Müller, James L Kennedy, Rocco Nicola Forgione, Margaret Kirshner, Gail Kepple and 3 more

Open access · greenAbstract readMulticenter StudyRandomized Controlled Trial
In one paragraph

Trial report in Journal of clinical pharmacology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
3.8field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 68 citations in OpenAlex.

  1. Utility of theClinical and translational science · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 4 institutions in 3 countries.

Yuyan JinDepartment of Pharmaceutical Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, USA.
Bruce G Pollock
Ellen Frank
Giovanni B Cassano
Paola Rucci
Daniel J Müller
James L Kennedy
Rocco Nicola Forgione
Margaret Kirshner
Gail Kepple
Andrea Fagiolini
David J Kupfer
Robert R Bies
University of Pittsburgh · USUniversity of Pisa · ITUniversity of Toronto · CAUniversity of Siena · IT

Funding

MHIRC FOR THE STUDY OF MOOD AND ANXIETY DISORDERSP30MH030915 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI KUPFER, DAVID J · 1995 to 2005
$11.9M
Depression: The Search for Treatment-Relevant PhenotypesR01MH065376 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI FRANK, ELLEN · 2003 to 2009
$4.0M
CLINICAL RESEARCH CENTER STUDY OF AFFECTIVE DISORDERSP50MH030915 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI KUPFER, DAVID J · 1985 to 1994
–
NIMH NIH HHS MH30915NIMH NIH HHS MH65376NIMH NIH HHS P30 MH030915NIMH NIH HHS R01 MH065376
6 · The paper itself

Abstract

The purpose of this study was to characterize escitalopram population pharmacokinetics (PK) in patients treated for major depression in a cross-national, US-Italian clinical trial. Data from the 2 sites participating in this trial, conducted at Pittsburgh (United States) and Pisa (Italy), were used. Patients received 5, 10, 15, or 20 mg of escitalopram daily for a minimum of 32 weeks. Nonlinear mixed effects modeling was used to model the PK characteristics of escitalopram. One- and 2-compartment models with various random effect implementations were evaluated during model development. Objective function values and goodness-of-fit plots were used as model selection criteria. CYP2C19 genotype, age, weight, body mass index, sex, race, and clinical site were evaluated as possible covariates. In total, 320 plasma concentrations from 105 Pittsburgh patients and 153 plasma concentrations from 67 Pisa patients were available for the PK model development. A 1-compartmental model with linear elimination and proportional error best described the data. Apparent clearance (CL/F) and volume of distribution (V/F) for escitalopram without including any covariates in the patient population were 23.5 L/h and 884 L, respectively. CYP2C19 genotype, weight, and age had a significant effect on CL/F, and patient body mass index affected estimated V/F. Patients from Pisa, Italy, had significantly lower clearances than patients from Pittsburgh that disappeared after controlling for patient CYP2C19 genotype, age, and weight. Postprocessed individual empirical Bayes estimates on clearance for the 172 patients show that patients without allele CYP2C19(*)2 or (*)3 (n = 82) cleared escitalopram 33.7% faster than patients with heterogeneous or homogeneous (*)2 or (*)3 ((*)17/(*)2, (*)17/(*)3, (*)1/(*)2, (*)1/(*)3, (*)2/(*)2, (*)2/(*)3, and (*)3/(*)3, n = 46). CL/F significantly decreased with increasing patient age. Patients younger than 30 years (n = 45) cleared escitalopram 20.7% and 42.7% faster than patients aged 30 to 50 years (n = 84) and older than 50 years of age (n = 43), respectively. CYP2C19 genotype, age, and weight strongly influenced the CL/F of escitalopram. These variables may affect patient tolerance of this antidepressant and may provide important information in the effort to tailor treatments to patients' individual needs.

Indexed as

AdultAgedAge FactorsAllelesAntidepressive Agents, Second-GenerationAryl Hydrocarbon HydroxylasesBody Mass IndexBody WeightCitalopramCytochrome P-450 CYP2C19Dose-Response Relationship, DrugFemaleGenotypeHumansItalyMajor Depressive DisorderAntidepressive Agents, Second-GenerationAryl Hydrocarbon HydroxylasesCitalopramCYP2C19 protein, humanCytochrome P-450 CYP2C19

Identifiers

PMID19841156
PMCPMC3571021
OpenAlexW2008486886

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.