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The development and internal evaluation of a predictive model to identify for whom Mindfulness-Based Cognitive Therapy (MBCT) offers superior relapse prevention for recurrent depression versus maintenance antidepressant medication.
Cohen, Zachary D; DeRubeis, Robert J; Hayes, Rachel; Watkins, Edward R; Lewis, Glyn; Byng, Richard; Byford, Sarah; Crane, Catherine; Kuyken, Willem; Dalgleish, Tim; Schweizer, Susanne.
Affiliation
  • Cohen ZD; Department of Psychiatry, University of California Los Angeles, Los Angeles, USA.
  • DeRubeis RJ; Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Hayes R; University of Exeter Medical School, South Cloisters, St Luke's Campus, Exeter, UK.
  • Watkins ER; Sir Henry Wellcome Mood Disorder Center, University of Exeter, Exeter, UK.
  • Lewis G; Division of Psychiatry, Faulty of Brain Sciences, University College London, London, UK.
  • Byng R; Community Primary Care Research Group, University of Plymouth, Plymouth, UK.
  • Byford S; Community Primary Care Research Group, University of Plymouth, Plymouth, UK.
  • Crane C; National Institute of Health Research Collaboration for Leadership in Applied Health Research and Care, South West Peninsula.
  • Kuyken W; Health Service and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
  • Dalgleish T; Department of Psychiatry, Medical Sciences Division, University of Oxford, Oxford, UK.
  • Schweizer S; Department of Psychiatry, Medical Sciences Division, University of Oxford, Oxford, UK.
Clin Psychol Sci ; 11(1): 59-76, 2023 Jan.
Article de En | MEDLINE | ID: mdl-36698442
ABSTRACT
Depression is highly recurrent, even following successful pharmacological and/or psychological intervention. We aimed to develop clinical prediction models to inform adults with recurrent depression choosing between antidepressant medication (ADM) maintenance or switching to Mindfulness-Based Cognitive Therapy (MBCT). Using data from the PREVENT trial (N=424), we constructed prognostic models using elastic net regression that combined demographic, clinical and psychological factors to predict relapse at 24 months under ADM or MBCT. Only the ADM model (discrimination performance AUC=.68) predicted relapse better than baseline depression severity (AUC=.54; one-tailed DeLong's test z=2.8, p=.003). Individuals with the poorest ADM prognoses who switched to MBCT had better outcomes compared to those who maintained ADM (48% vs. 70% relapse, respectively; superior survival times [z=-2.7, p=.008]). For individuals with moderate-to-good ADM prognosis, both treatments resulted in similar likelihood of relapse. If replicated, the results suggest that predictive modeling can inform clinical decision-making around relapse prevention in recurrent depression.

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Type d'étude: Prognostic_studies / Risk_factors_studies Langue: En Journal: Clin Psychol Sci Année: 2023 Type de document: Article Pays d'affiliation: États-Unis d'Amérique

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Type d'étude: Prognostic_studies / Risk_factors_studies Langue: En Journal: Clin Psychol Sci Année: 2023 Type de document: Article Pays d'affiliation: États-Unis d'Amérique