Towards an evidence-based decision tool to guide relapse prediction and prevention of depression in primary care

Talk Code: 
1B.8
Presenter: 
Andrew Moriarty
Twitter: 
Co-authors: 
Moriarty AS1, Paton LW2, Meader M3, Snell KIE4, Riley RD4, Gilbody S1, McMillan D1, Chew-Graham CA5,
Author institutions: 
1 Department of Health Sciences and Hull York Medical School, University of York 2 Department of Health Sciences, University of York 3 Centre for Reviews and Dissemination, University of York 4 Centre for Prognosis Research, School of Medicine, Keele University 5 School of Medicine, Keele University, Keele, UK

The problem

Most people with depression are managed in primary care. After a first episode, approximately half of patients will experience a relapse. Those who experience a relapse are more likely to experience a further relapse than those who do not. There is uncertainty about what other factors are associated with an increased risk of relapse (some established factors include adverse childhood events, previous episodes of depression and residual symptoms). Combining several prognostic factors within a multivariable prognostic model can result in improved individualised risk predictions.

The Approach

This programme of work aims to develop a primary care-based decision tool to help assess individual patients’ risk of relapse and to guide the allocation of relapse prevention interventions in practice. We build on our recent Cochrane review, which found a lack of evidence-based relapse prediction models for depression. We aim to, first, develop a novel prognostic model to predict risk of relapse within 6-8 months after reaching remission. We will do this by using penalised logistic regression with an IPD meta-analysis dataset drawn from seven primary care-based RCTs and one longitudinal cohort study. We are also undertaking a further Cochrane review to compare interventions for preventing relapse in a primary care setting. Finally, interviews with patients and primary care professionals, as well as on-going PPI, will aim to understand stakeholder perspectives on depression relapse, risk prediction and interventions in clinical practice.

Findings

This work is ongoing.

Implications

The longer-term goal of this study is to develop a clinical tool, to be implemented in general practice, to support clinicians in identifying patients at increased risk of relapse. This could allow for more effective allocation of relapse prevention interventions. Ultimately, we aim to improve clinical outcomes and quality of life for patients, as well as facilitating more targeted use of NHS resources in primary care.

 

Funding acknowledgement: 
This report is independent research supported by the National Institute for Health Research (NIHR Doctoral Research Fellowship, Dr Andrew Moriarty, DRF-2018-11-ST2-044). The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health and Social Care.