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Trajectories of change in depression severity during treatment with antidepressants

Published online by Cambridge University Press:  29 October 2009

R. Uher*
Affiliation:
Medical Research Council (MRC) Social, Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, King's College London, UK
B. Muthén
Affiliation:
University of California, Los Angeles, CA, USA
D. Souery
Affiliation:
Laboratoire de Psychologie Médicale, Université Libre de Bruxelles and Psy Pluriel – Centre Européen de Psychologie Médicale, Bruxelles, Belgium
O. Mors
Affiliation:
Aarhus University Hospital, Risskov, Denmark
J. Jaracz
Affiliation:
Laboratory of Psychiatric Genetics, Department of Psychiatry, Poznan University of Medical Sciences, Poland
A. Placentino
Affiliation:
Biological Psychiatry Unit and Dual Diagnosis Ward IRCCS, Centro San Giovanni di Dio, FBF, Brescia, Italy
A. Petrovic
Affiliation:
Institute of Public Health, Ljubljana, Slovenia
A. Zobel
Affiliation:
Rheinische Friedrich-Wilhelms-Universitaet Bonn, Germany
N. Henigsberg
Affiliation:
Croatian Institute for Brain Research, Medical School, University of Zagreb, Croatia
M. Rietschel
Affiliation:
Central Institute of Mental Health, Division of Genetic Epidemiology in Psychiatry, Mannheim, Germany
K. J. Aitchison
Affiliation:
Medical Research Council (MRC) Social, Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, King's College London, UK
A. Farmer
Affiliation:
Medical Research Council (MRC) Social, Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, King's College London, UK
P. McGuffin
Affiliation:
Medical Research Council (MRC) Social, Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, King's College London, UK
*
*Address for correspondence: Dr R. Uher, Medical Research Council (MRC) Social, Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, King's College London, UK (Email: rudolf.uher@iop.kcl.ac.uk)

Abstract

Background

Response and remission defined by cut-off values on the last observed depression severity score are commonly used as outcome criteria in clinical trials, but ignore the time course of symptomatic change and may lead to inefficient analyses. We explore alternative categorization of outcome by naturally occurring trajectories of symptom change.

Method

Growth mixture models were applied to repeated measurements of depression severity in 807 participants with major depression treated for 12 weeks with escitalopram or nortriptyline in the part-randomized Genome-based Therapeutic Drugs for Depression study. Latent trajectory classes were validated as outcomes in drug efficacy comparison and pharmacogenetic analyses.

Results

The final two-piece growth mixture model categorized participants into a majority (75%) following a gradual improvement trajectory and the remainder following a trajectory with rapid initial improvement. The rapid improvement trajectory was over-represented among nortriptyline-treated participants and showed an antidepressant-specific pattern of pharmacogenetic associations. In contrast, conventional response and remission favoured escitalopram and produced chance results in pharmacogenetic analyses. Controlling for drop-out reduced drug differences on response and remission but did not affect latent trajectory results.

Conclusions

Latent trajectory mixture models capture heterogeneity in the development of clinical response after the initiation of antidepressants and provide an outcome that is distinct from traditional endpoint measures. It differentiates between antidepressants with different modes of action and is robust against bias due to differential discontinuation.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2009

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