Predicting trajectories of symptom change during and following treatment in adolescents with Unipolar Major Depression.
Davies, Sian Emma
University of Cambridge
Doctor of Philosophy (PhD)
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Davies, S. E. (2020). Predicting trajectories of symptom change during and following treatment in adolescents with Unipolar Major Depression. (Doctoral thesis). https://doi.org/10.17863/CAM.47561
Objective: Definitions of treatment response used in randomised controlled trials for unipolar major depression are non-standardised and arbitrary. Proportion of non-responders has been estimated as ranging from 20%-40% across such trials. I aimed to classify depressed adolescents recruited to the UK IMPACT trial into different trajectories of depression symptom response using a longitudinal data-driven approach: growth mixture modelling (GMM) and investigate potential predictors of trajectory classes in this cohort. Method: 465 depressed adolescents received manualised psychological therapies in the IMPACT trial. GMM was used to plot the trajectories of self-reported depressive symptoms measured at 6 nominal time points over 86 weeks from randomisation, and categorise patients into their most likely trajectory class. Chapters 2-4 investigated the prognostic value of a number of variables. Chapter 2 investigated a battery of demographic and clinical variables including subclinical psychotic symptoms. Chapter 3 focused on a subsample of patients: 109 of the 465 with structural magnetic resonance imaging (MRI) data. FreeSurfer was used to extract cortical thickness (CT) and surface area (SA) measures from 4 regions of interest (ROI; rostral anterior cingulate, dorsolateral prefrontal cortex, orbitofrontal cortex, and insular cortex). Chapter 4 focused on another subsample of patients: 166 of the 465 with salivary basal cortisol data at both waking and evening. Logistic regressions were used in Chapters 2-4 to investigate whether these variables were associated with increased likelihood of membership to a certain GMM class. Results: A piecewise GMM categorised patients into two classes with initially similar and subsequently distinct trajectories. Both groups had a significant decline in depressive symptoms over the first 18 weeks. Eighty-four per cent of patients were classed as “continued-improvers” through reporting an improvement in symptoms over the full duration of the study. A further class of 15.9% of patients were termed “halted-improvers” who had higher depression scores at baseline, faster recovery but no further improvement after 18 weeks. This data-driven method of classification showed only moderate agreement with a priori classification methods, and suggested misclassification rate could be as great as 31%. Co-morbid psychiatric disorders at baseline moderately increased the liability of being a member of the halted-improvers class (OR = 1.40, CI 1.00-1.96). No other clinical, neurological or cortisol variable reached statistical significance for predicting trajectory class. Conclusion: A fast reduction in depressive symptoms in the first few weeks of treatment may not indicate a good prognosis. Further, halted-improvement may not be apparent until after 18 weeks of treatment. Capitalizing on repeated symptom assessments with longitudinal data driven modelling may improve the precision of revealing patient groups with differential responses to treatment. Further work should seek to validate these trajectories in a separate sample of adolescents.
Depression, Treatment, Adolescents, Trajectories
The IMPACT study was funded by the National Institute for Health Research (NIHR) Health Technology Assessment (HTA) programme (project number 06/05/01). MR-IMPACT was funded by the Medical Research Council (grant: G0802226) and IMPACT-GH was funded by the Evelyn Trust. My doctoral studentship was awarded by the Neuroscience in Psychiatry (NSPN.Org) Consortium itself funded by a strategic award from the Wellcome Trust (095844/Z/11/Z) awarded to Professor Ian Goodyer and Professor Peter Fonagy.
This record's DOI: https://doi.org/10.17863/CAM.47561
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