Title: Estimating the value of population stratification in prediabetes: development and validation of a new patient-level economic model
Funder: Department of Health and Social Care

Abstract: Research Question To use individual participant data (IPD) from multiple therapeutic studies to develop and validate a new economic model to inform health policy in prediabetes Background Existing economic models of prediabetes are underdeveloped, insufficiently accounting for prediabetes variation and unable to evaluate stratified care using modern biomarkers. A new prediabetes model has potential to improve the comparability and accuracy of economic value assessment for new interventions across prediabetes subtypes, using accepted modelling methods, structure, and parameterisation to provide a common framework to evaluate multiple interventions. Aims This project will develop and validate a new economic model to support further population stratification in prediabetes. The objectives are to: Harmonise twelve trial and prospective observational datasets in prediabetes populations to estimate prediabetes progression Develop an economic simulation model from risk factor progression equations and parametric survival models derived from single & pooled individual participant data (IPD) from five randomised trials Validate and calibrate the simulation model using seven external observational datasets, and UK/China Kadoorie Biobanks Apply the reference model to two case studies in stratified prediabetes careMethods After pooling IPD from randomised trials, I will estimate progression to diabetes, related complications, and death across prediabetes subtypes. I will build parametric proportional hazards survival models for each event based on both time-invariant and time-varying clinical risk factors, and time-varying event history. Progression of time-varying clinical risk factors will be predicted independently using autoregressive panel regression. I will also investigate a joint modelling approach to model longitudinal risk factor progression and survival models simultaneously, using a common underlying random effects structure. I will then construct a patient-level economic simulation which calculates annual incidence of events based on individual patient characteristics until death. Existing high-quality UK data will inform changes in health costs and health-related quality of life associated with each event. I will validate and calibrate the model by comparing predicted and observed cumulative incidence of events and estimating model discrimination in external observational data-sources, including biobank data. I will then apply the model to case studies evaluating the cost-effectiveness of: Targeted follow-up to deliver earlier intensified treatment for fast-progressors Metformin provision to patients with impaired glucose toleranceNICE stakeholders will guide model development, validation and application to case studies to maximise the model's relevance for contemporary UK health policymaking. Impact & Dissemination A validated patient-level economic reference model will improve the accuracy of cost-effectiveness estimates for prediabetes interventions, and aid patient stratification. I will expand existing patient communication tools to provide information on prediabetes risks by subtype. I will also develop a software version of the economic model to assess novel prediabetes interventions, which will be freely licensed to international public institutions and charities and launched at a 50-person stakeholder event at the end of my fellowship. I will present my research within clinical and health economic journal outputs and conferences, and enter my model into the Mount Hood Diabetes Challenge. I will also use my network of collaborators with international policy links to reach wider audiences of diabetes policymakers.

Lay abstract: Background Many people have high blood sugar below the level classified as diabetes. This is known as prediabetes. Harmful effects of diabetes, including heart, kidney and eye damage, are known to occur in people with prediabetes. Evidence shows that different types of prediabetes progress at different speeds. Some people with prediabetes develop type-2 diabetes very quickly. Others don't develop diabetes at all, and some return to having normal sugar levels. The risk of other harmful effects of diabetes also varies between types of prediabetes. New research is allowing us to identify more types of prediabetes. However, the 5 million English adults with prediabetes all currently receive the same NHS treatment. To know whether the NHS should treat people differently, we need to know more about people's length and quality of life with different types of prediabetes. If this is very different between high and low-risk types of prediabetes, it could be worthwhile for the NHS to offer people different types of care. Aims I will build a model to estimate lifetime healthcare costs and quality of life for patients with different types of prediabetes. The model will allow policymakers to quickly and accurately assess the effect of new interventions on the lifetime costs and quality of life of patients with different types of prediabetes. This will improve patients' access to interventions which are good value-for-money, and help target treatment to high-risk groups. The model will also focus research and development efforts to design new interventions for each different type of prediabetes, which will have greater effect on improving all patients' long-term quality of life. Design and methods used I will combine information from five randomised trials which collected data in well-defined types of prediabetes. I will estimate how long each patient takes to develop diabetes and its harmful effects, accounting for their personal risk factors. By checking and improving these estimates using different data, I'll be able to compare how often diabetes and its harmful effects occur in each type of prediabetes. Diabetes and its harmful effects influence patients' quality of life, and the costs of their NHS care during their lifetime. By using this information, the model can show policymakers how new interventions which change patients' chances of experiencing future events, will affect long-term quality of life and costs for patients with different types of prediabetes. Using the model, I'll show the value of two targeted care strategies in high-risk groups. Patient and Public Involvement I had 1:1 and group meetings with eight PPI representatives to understand diabetes patients' research priorities, and how I can address these in my model design and case studies. As well as wanting improved NHS management of prediabetes, patients wanted better information about the future quality of life they might expect in their type of prediabetes. They also wanted to know how to best improve their own quality of life within their prediabetes type. I'll create new patient resources to show this. Two PPI members have joined my research advisory group to provide ongoing support to my analysis design and methods. Dissemination Throughout the project, I'll work with UK policymakers at NICE to develop the model, and to demonstrate the value of better targeted diabetes prevention. As well as publishing papers, I'll take part in the Mount Hood Diabetes Challenge and present at academic conferences. I'll also work with a software developer to produce a version of the model which can be widely used. This will be available free-of-charge to charities and governments globally. At the end of the project, I will launch the software at a workshop for policymakers, diabetes groups and patients.

Research activity codes: 7.1 INDIVIDUAL CARE NEEDS
Health categories: METABOLIC AND ENDOCRINE