The Development and Internal Evaluation of a Predictive Model to Identify for Whom Mindfulness-Based Cognitive Therapy Offers Superior Relapse Prevention for Recurrent Depression Versus Maintenance Antidepressant Medication

Author:

Cohen Zachary D.1,DeRubeis Robert J.2,Hayes Rachel3,Watkins Edward R.4ORCID,Lewis Glyn56,Byng Richard67,Byford Sarah8,Crane Catherine9,Kuyken Willem9,Dalgleish Tim1011,Schweizer Susanne1213ORCID

Affiliation:

1. Department of Psychiatry, University of California Los Angeles

2. Department of Psychology, University of Pennsylvania

3. National Institute for Health Research (NIHR) Applied Research Collaboration (ARC) South West Peninsula, University of Exeter

4. Sir Henry Wellcome Mood Disorder Center, University of Exeter

5. Division of Psychiatry, Faulty of Brain Sciences, University College London

6. Community Primary Care Research Group, University of Plymouth

7. National Institute of Health Research Collaboration for Leadership in Applied Health Research and Care, South West Peninsula, England

8. Health Service and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience, King’s College London

9. Department of Psychiatry, Medical Sciences Division, University of Oxford

10. Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge

11. Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, England

12. Department of Psychology, University of Cambridge

13. School of Psychology, University of New South Wales

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 previously published data ( 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: area under the curve [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 with individuals who maintained ADM (48% vs. 70% relapse, respectively; superior survival times, z = −2.7, p = .008). For individuals with moderate to good ADM prognoses, 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.

Funder

Medical Research Council

Wellcome Trust

MQ

National Institute for Health Research

Publisher

SAGE Publications

Subject

Clinical Psychology

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