a1 Medical Research Council (MRC) Social, Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, King's College London, UK
a2 University of California, Los Angeles, CA, USA
a3 Laboratoire de Psychologie Médicale, Université Libre de Bruxelles and Psy Pluriel – Centre Européen de Psychologie Médicale, Bruxelles, Belgium
a4 Aarhus University Hospital, Risskov, Denmark
a5 Laboratory of Psychiatric Genetics, Department of Psychiatry, Poznan University of Medical Sciences, Poland
a6 Biological Psychiatry Unit and Dual Diagnosis Ward IRCCS, Centro San Giovanni di Dio, FBF, Brescia, Italy
a7 Institute of Public Health, Ljubljana, Slovenia
a8 Rheinische Friedrich-Wilhelms-Universitaet Bonn, Germany
a9 Croatian Institute for Brain Research, Medical School, University of Zagreb, Croatia
a10 Central Institute of Mental Health, Division of Genetic Epidemiology in Psychiatry, Mannheim, Germany
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.
(Received April 21 2009)
(Revised July 20 2009)
(Accepted September 10 2009)
(Online publication October 29 2009)
c1 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: email@example.com)