期刊
PSYCHOLOGICAL MEDICINE
卷 40, 期 8, 页码 1367-1377出版社
CAMBRIDGE UNIV PRESS
DOI: 10.1017/S0033291709991528
关键词
Antidepressant response; depression; growth mixture modelling; randomized controlled trials
资金
- European Commission [LSHB-CT-2003-503428]
- National Institute for Health Research, Department of Health, UK
- GlaxoSmithKline
- MRC [G0701003] Funding Source: UKRI
- Medical Research Council [G0701003, G9817803B] Funding Source: researchfish
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.
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