Toward Parity of Esteem for Cardiometabolic Health in Psychosis: Refining the Psychosis Metabolic Risk Calculator (PsyMetRiC) for Accuracy and Equity, and Developing Knowledge for Implementation and Impact

Background Psychotic disorders have a lifetime prevalence of ~1% and are associated with a 15-20y shortened life expectancy. The excess mortality is predominantly explained by cardiometabolic morbidity detectable by psychosis onset in young people - years earlier than typically observed in the general population. Therefore, general population-based risk prediction algorithms e.g., QRISK3, which are routinely used to help prevent adverse cardiometabolic outcomes, are inaccurate in young people with psychosis, underscoring the need for targeted tools for this at-risk group. PsyMetRiC, which I developed during my NIHR Doctoral Fellowship using best-practice methods, is the first cardiometabolic risk prediction algorithm tailored for young people with psychotic disorders. PsyMetRiC has been validated in the UK and internationally, and is on a clear path toward MHRA regulatory approval during 2024/25. PsyMetRiC now requires further testing in larger, representative samples to ensure it is accurate and equitable. Then, work is needed to ensure PsyMetRiC scores are interpretable, communicated appropriately, and generate impact through integration with best-practice interventions. This is what I plan to achieve during this Fellowship. Aims 1) Test and Refine PsyMetRiC to Maximise Accuracy and Equity; 2) Address the Interpretation, Communication, and Action Associated with PsyMetRiC; 3) Conduct a Feasibility Study and Process Evaluation of PsyMetRiC Methods In Year 1, I will test and refine PsyMetRiC using data from two of the largest linked UK electronic health record databases, QResearch and CPRD, supported by experts in risk prediction and digital equity/safety. The analytic sample will be 40-50x larger than samples previously available for PsyMetRiC, providing an unparalleled opportunity to maximise accuracy and equity. In Years 2-3, stakeholder groups will inform a range of acceptable PsyMetRiC scores representing 'higher risk', and a preliminary economic model will evaluate PsyMetRiC's potential cost-effectiveness at those thresholds. I will use semi-structured interviews to explore how PsyMetRiC scores should be communicated, followed by stakeholder groups to plan the co-production of a risk communication guide; plan the visual presentation of PsyMetRiC in clinical software; and decide how interventions should be delivered locally. Then, leveraging infrastructure from the NIHR Mental Health Translational Research Collaboration, The Mental Health Mission and EPIcare grant awards for digital mental health, PsyMetRiC will be integrated into clinical software. I will be supported by experts in health economics, qualitative research, and participatory methods. In Years 4-5, a feasibility study and mixed-methods process evaluation of PsyMetRiC supported by Birmingham Clinical Trials Unit will address key uncertainties, paving the way for me to seek funding for a definitive randomised clinical trial to evaluate PsyMetRiC's impact - a critical but often neglected step in risk prediction research - by the end of the Fellowship. Impact This Fellowship will transform our ability to manage cardiometabolic risk in this high-risk group. Benefits will be felt by patients; the NHS through cost-savings; and researchers through accurate trial stratification/selection. Equally, this Fellowship will provide me unparalleled opportunities to develop expertise in applied research and participatory methods, and provide me with a solid footing to establish independence as a future research leader.