Title: Depression in primary care: Development and validation of a prognostic model to predict relapse and evaluation of relapse prevention interventions
Funder: Department of Health and Social Care

Abstract: Background: Approximately 50% of patients will relapse after a first episode of depression (70% and 90% after a second and third episode respectively). There is evidence to suggest that the severity of depression and resistance to treatment increases with each successive episode of relapse, highlighting the potential benefits of intervening to prevent relapse and improve overall disease trajectory. There is uncertainty about what other factors (biological, psychological or social) might be associated with an increased risk of relapse. Research is needed to establish the factors associated with an increased risk of relapse in a primary care setting. The ability to stratify patients after successful treatment, according to their risk of relapse, could allow the improved targeting of relapse prevention interventions and ultimately improve patient outcomes.Aim: This project aims to support clinicians and services to enable them to identify patients successfully treated for depression who are at increased risk of relapse, and to allow more targeted provision of relapse prevention interventions.Objectives: a) To identify factors associated with raised risk of relapse following an episode of depression; b) To develop and validate a prognostic model for patients with depression to allow risk stratification and targeting of relapse prevention strategies; c) To develop a decision analytic model to guide the allocation of relapse prevention interventions in a primary care setting; d) To establish patient, clinician and decision-maker perspectives to assess the acceptability and feasibility of implementing relapse prevention interventions in primary care.Methods: Workstream 1 will include a systematic review looking at known predictors of relapse in depression. A large dataset from 6 RCTs (n=2969) will be used to form a retrospective cohort of patients who have received a low-intensity psychosocial treatment for depression in primary care. Patients who relapsed post-treatment will be identified and logistic regression will be used to assess the extent to which individual clinical predictors were associated with relapse. This information will be used to develop a prognostic model to predict risk of relapse in individual patients. The model will be validated using a separate dataset that followed up patients and assessed relapse rates after completing CBT. Workstream 2 will use information from a mixed treatment comparison of relapse prevention interventions and data relating to costs to inform the development of a decision analytic model to guide targeting of relapse prevention interventions in primary care. Focus groups and interviews with stakeholders will provide additional information about the acceptability and feasibility of interventions and patient preferences.Anticipated impact and dissemination: This project will produce new knowledge about predictors of relapse in depression and a prognostic model for predicting risk of relapse. This could form the basis for a clinical tool to be implemented in general practice to aid clinicians in risk stratification and providing focused relapse prevention interventions. This project will also produce a decision analytic model and new knowledge about patient and professional perspectives of relapse prevention interventions to guide the implementation of these interventions in primary care.

Lay abstract: BackgroundDepression is now the leading cause of disability in the world. People with depression often do not receive the healthcare they need to get well and stay well. The majority of patients are treated by general practitioners (GPs) supported by the prescription of antidepressant medication (the most common treatment) or referral for talking therapies, for example, cognitive behavioural therapy which focuses on a person's thought and behaviours.At least half of people with depression will become unwell again (relapse) after they have finished their initial treatment. The risk of relapse increases the greater the number of separate episodes of depression a person experiences. This is an important problem, not only for patients, but for their relatives, carers and society in general because when patients relapse they are often not able to work and live their lives as they would like. At the moment, there is not much evidence about which patients are more likely than others to have a relapse, which makes it difficult for GPs to focus their efforts and know which patients should be receiving a 'relapse prevention treatment'.Aim of researchThe aim of this research is to identify the factors that make patients more likely to relapse after receiving treatment for depression and create a tool that identifies patients at increased risk of relapse who can then be offered treatment to prevent relapse. The research also aims to find out which treatment should be offered to which patients, taking into account the benefits to patients as well as the cost to the NHS as a whole.Design and methodsFirst, a review of all of the existing research will be undertaken to find out what we know about the factors making a patient more likely to relapse. In addition, information from a large number of patients who participated in trials of treatments for depression in primary care will be studied to identify common factors in those who have relapsed. A mathematical model will be developed that predicts the likelihood of an individual patient with depression that is now treated relapsing in the future.Then, information about how well the different treatments work and at what cost, as well as input from patients, healthcare professionals and those involved in providing care to patients will be gathered to help guide the decision as to which patients will benefit most from which treatment while being most cost-effective for the NHS.Patient and public involvementPatients and healthcare professionals believe that this is an important area of research. This summary has been written in collaboration with a group of people with lived experience of depression whom I consulted throughout the design of this project. They have agreed to remain involved in the project and will provide advice on all stages of the research.DisseminationThe results of this work will be published in scientific journals and presented at conferences. I will ensure that the results of the study are also made available through patient groups and charitable publications, guided by input from the patient involvement panel.

Research activity codes: 4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: MENTAL HEALTH