Development and validation of a prognostic model to predict relapse in adults with remitted depression in primary care: secondary analysis of pooled individual participant data from multiple studies

Andrew S Moriarty; Lewis W Paton; Kym I E Snell; Lucinda Archer; Richard D Riley; Joshua E J Buckman; Carolyn A Chew Graham; Simon Gilbody; Shehzad Ali; Stephen Pilling; Nick Meader; Bob Phillips; Peter A Coventry; Jaime Delgadillo; David A Richards; Chris Salisbury; Dean McMillan

doi:10.1136/bmjment-2024-301226

Development and validation of a prognostic model to predict relapse in adults with remitted depression in primary care: secondary analysis of pooled individual participant data from multiple studies

BMJ Ment Health. 2024 Oct 28;27(1):e301226. doi: 10.1136/bmjment-2024-301226.

Authors

Andrew S Moriarty¹, Lewis W Paton², Kym I E Snell³, Lucinda Archer³, Richard D Riley³, Joshua E J Buckman^{4

5}, Carolyn A Chew Graham⁶, Simon Gilbody⁷, Shehzad Ali⁸, Stephen Pilling^{4

9}, Nick Meader¹⁰, Bob Phillips¹¹, Peter A Coventry¹², Jaime Delgadillo¹³, David A Richards^{14

15}, Chris Salisbury¹⁶, Dean McMillan²

Affiliations

¹ Hull York Medical School and Department of Health Sciences, University of York, York, Yorkshire, UK [email protected].
² Hull York Medical School and Department of Health Sciences, University of York, York, Yorkshire, UK.
³ Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
⁴ Research Department of Clinical, Educational and Health Psychology, University College London, London, UK.
⁵ iCope-Camden and Islington Psychological Therapies Services, Camden and Islington NHS Foundation Trust, London, UK.
⁶ School of Medicine, Keele University, Keele, Staffordshire, UK.
⁷ Hull York Medical School and Department of Health Sciences, University of York, York, UK.
⁸ Schulich School of Medicine & Dentistry, Western University, London, Great Britain, Canada.
⁹ Camden and Islington NHS Foundation Trust, London, UK.
¹⁰ Population Health Sciences Institute, University of Newcastle upon Tyne, Newcastle upon Tyne, UK.
¹¹ Hull York Medical School, University of York, York, Yorkshire, UK.
¹² Department of Health Sciences, University of York, York, Yorkshire, UK.
¹³ Department of Psychology, The University of Sheffield, Sheffield, UK.
¹⁴ Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
¹⁵ Department of Health and Caring Sciences, Western Norway University of Applied Sciences, Bergen, Hordaland, Norway.
¹⁶ Centre for Academic Primary Care, University of Bristol, Bristol, UK.

Abstract

Background: Relapse of depression is common and contributes to the overall associated morbidity and burden. We lack evidence-based tools to estimate an individual's risk of relapse after treatment in primary care, which may help us more effectively target relapse prevention.

Objective: The objective was to develop and validate a prognostic model to predict risk of relapse of depression in primary care.

Methods: Multilevel logistic regression models were developed, using individual participant data from seven primary care-based studies (n=1244), to predict relapse of depression. The model was internally validated using bootstrapping, and generalisability was explored using internal-external cross-validation.

Findings: Residual depressive symptoms (OR: 1.13 (95% CI: 1.07 to 1.20), p<0.001) and baseline depression severity (OR: 1.07 (1.04 to 1.11), p<0.001) were associated with relapse. The validated model had low discrimination (C-statistic 0.60 (0.55-0.65)) and miscalibration concerns (calibration slope 0.81 (0.31-1.31)). On secondary analysis, being in a relationship was associated with reduced risk of relapse (OR: 0.43 (0.28-0.67), p<0.001); this remained statistically significant after correction for multiple significance testing.

Conclusions: We could not predict risk of depression relapse with sufficient accuracy in primary care data, using routinely recorded measures. Relationship status warrants further research to explore its role as a prognostic factor for relapse.

Clinical implications: Until we can accurately stratify patients according to risk of relapse, a universal approach to relapse prevention may be most beneficial, either during acute-phase treatment or post remission. Where possible, this could be guided by the presence or absence of known prognostic factors (eg, residual depressive symptoms) and targeted towards these.

Trial registration number: NCT04666662.

Keywords: Adult psychiatry; Data Interpretation, Statistical; Depression.

Publication types

Randomized Controlled Trial
Validation Study

MeSH terms

Adult
Aged
Depression / diagnosis
Depression / epidemiology
Depression / psychology
Depressive Disorder / diagnosis
Depressive Disorder / epidemiology
Depressive Disorder / psychology
Female
Humans
Male
Middle Aged
Primary Health Care*
Prognosis
Recurrence*
Secondary Prevention

Associated data

ClinicalTrials.gov/NCT04666662