Title: Improving prediction of psychosis in ARMS using a clinically useful prognostic tool: IPPACT
Funder: Department of Health and Social Care

Abstract: Scientific Abstract Research Questions: •Can a refined prognostic tool improve prediction of psychosis in individuals with an At Risk Mental State (ARMS)? •Can use of this tool lead to more cost-effective management of ARMS individuals? Target Group: Individuals aged 16-35 identified as being at high risk of psychotic disorder as defined by ARMS criteria Setting: Secondary NHS services Technology: A prognostic tool that includes factors shown to be predictive of psychosis in ARMS. Risk factors will be weighted according to their predictive ability. Comparator: We will compare the effectiveness of the new prognostic tool in predicting transition to psychosis to usual practice. Outcomes: • A validated, refined prognostic tool that is co-designed by service users and NHS staff and so is feasible, acceptable and suitable for routine use in the NHS. The tool aims to improve the ability to detect those most at risk for transition above the current rate of about 15- 22% after 12 months. • Health economic modelling of stratified care depending on risk of psychosis, to explore the potential cost effectiveness of implementing the new prognostic tool into routine practice. Study Design: 1. Phase 1: Evidence synthesis. This will include an individual patient data (IPD) meta-analysis of factors associated with transition to psychosis in ARMS, and a systematic review of ARMS prognostic models. Following this, input from service users and NHS clinicians about the acceptability and feasibility of possible measures to include in the tool will be used to co-design the tool. 2. Phase 2: Model development. State-of-the-art analyses informed by findings from Phase 1 will be used to develop a refined prognostic model that maximises prognostic accuracy of psychosis transition in ARMS. The model will undergo internal validation. 3. Phase 3: External model validation. A prospective cohort study with 12-month follow-up will be used to externally validate the prognostic tool. Participants will be individuals attending secondary care NHS services who meet ARMS criteria. We can feasibly recruit 798 participants with an anticipated attrition rate of 30% leaving a target follow-up of 558 participants. With an estimated 20% transition rate over 12 months we will have over 100 events in our validation dataset in line with recommended practice for prognostic modelling. Analyses will assess how closely the probability of transition predicted by our model agrees with the observed probability. Health economic analysis will model the effects of targeting those most at risk with more intensive treatments and using less intensive management in those least at risk. Dissemination will include developing an online Risk Calculator to be hosted on an NHS website. Impact: Research to better stratify ARMS patients according to levels of risk of psychosis could lead to more efficient use of NHS resources. Thus those at highest risk could be offered cognitive therapy, while lower risk patients could be offered less costly and less intensive regular mental state monitoring. Our team has extensive expertise in IPD meta-analysis, prognostic modelling, health economics, epidemiology and clinical research including Yung, who developed the ARMS criteria.

Lay abstract: Psychotic disorders, including schizophrenia, affect about 3% of the population worldwide. They can be severe and disabling and associated with high personal, social and economic costs. They tend to have their first onset in adolescence or late adulthood, meaning that many years may be lived with illness. In the mid-1990s researchers investigated if psychosis could be prevented by detecting early signs and symptoms. Criteria were developed that identify individuals at high risk of developing a first episode of psychosis – the At Risk Mental State (ARMS) criteria. From this, a specialised interview – the Comprehensive Assessment of At Risk Mental States (CAARMS) – was created to assess these criteria. About 15 - 22% of people identified as ARMS develop psychosis within 12 months – a risk about 400 times that that of the general population. Having this knowledge in advance presents the opportunity to prevent or delay the onset of psychosis in high risk individuals. However, most individuals meeting the ARMS criteria will not develop psychosis. Despite this, the National Institute for Health and Care Excellence (NICE) recommends the same treatment for all ARMS people– cognitive behavioural therapy (CBT). This means that some young people may be having unnecessary treatment (those who would not have developed psychosis). It also means that the NHS may be using a costly treatment, CBT, in people who may not need it. Additionally, some people may be told that they are at high risk of psychosis when they are not, creating possible fear and stigma. Therefore, we need to improve our ability to predict psychosis within the ARMS group. This is the aim of this study. Our proposed research involves 3 phases. First, we will collate and analyse all the existing data about risk factors for psychosis in ARMS patients. Our colleagues from around the world have agreed to share their ARMS data with us and this will allow us to do powerful analyses to gain a thorough understanding of the risk factors and how they interact with each other. Second, we will use this information to develop a new “prognostic tool”. This tool will include risk factors that we identify in Phase 1 that are most strongly associated with risk of psychosis. We will work with NHS staff and patients to ensure that any measures in the tool are easy to carry out so the tool can be used routinely in the NHS. Finally, we will test our prognostic tool in ARMS individuals by administering the tool in addition to the CAARMS when people first seek help from the NHS. We will follow them up 12 months later to see if they have developed psychosis or not. We will analyse the data to see if the prognostic tool can distinguish between those at highest and lowest risk of developing psychosis. We will also examine the possible economic effects of providing more intense but costly treatments to those at highest risk and more affordable management of those at lowest risk. Our team includes experts in complex data analyses, creating prognostic tools, health economics, early intervention policy and clinical staff with expertise in early psychosis and ARMS, including Prof Yung, who developed the ARMS criteria and the CAARMS interview.

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