An outcomes model for type 2 diabetes

Type 2 diabetes is an increasingly common chronic disease which can cause a wide range of serious complications including heart disease and blindness. We propose improving and making widely accessible a model which simulates the likely course of the disease for patients, given their particular characteristics such as blood pressure, current age and time since diagnosis. The model is based on information from patients in the United Kingdom Prospective Diabetes Study, a landmark study of diabetes treatment. It has already been found to give more accurate predictions than other diabetes models, and is being used by researchers in many countries. Some elements now need to be updated, and it needs to be made more user-friendly. Our model will then give patients and their doctors valuable information on current prognosis and the benefits of therapy. The usefulness of the model to other researchers will also be greatly enhanced.

The prevalence of Type 2 diabetes is increasing, and it is associated with a wide range of serious complications including heart disease and blindness. Because of its potentially long duration, simulation models are particularly valuable in understanding and estimating the lifetime risk of complications and the effects of modifying risk factors. The United Kingdom Prospective Diabetes Study Outcomes Model is a well-established and validated model based on patient-level data from this landmark study of diabetes treatment. It has already been found to compare favourably with other diabetes models in predictive comparions, and is being used by academic researchers, reimbursement and other public agencies and industry in many countries. This research proposal has three elements: first to implement a set of model improvements and updates, in particular focusing on changes in fatality rates following diabetes-related complications and changes in death from other causes; second, to undertake a wide-ranging set of external validations, comparing model predictions of event rates given baseline characteristics and risk factor changes against observed event rates in a large number of recent trials; and third to significantly improve the usability and accessibility of the model, both for the research community and so that patients and their doctors can readily use it to obtain valuable information on current prognosis and the benefits of therapy.