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Researchers at the ARC Centre of Excellence in Population Ageing Research (CEPAR) and collaborators have developed a simulation model that offers an important tool for the economic evaluation of treatments and interventions for type 1 diabetes.
CEPAR researchers Professor Philip Clarke, Dr An Tran-Duy, Dr Josh Knight and Professor Andrew Palmer, in collaboration with a multi-university team in Australia, Sweden, the UK and the US, have developed the first comprehensive model that is based entirely on a nationwide population of type 1 diabetes in Sweden. The model can be used to project the occurrence of major complications over the lifetime of patients and estimate life expectancy as well as complication-free survival time of the patients.
“Our model offers an important tool to assess cost-effectiveness of, and inform decisions on, treatment strategies for type 1 diabetes,” says Dr An Tran-Duy, lead author of the paper which was published in Diabetes Care, one of the world’s top journals in Endocrinology, Diabetes and Metabolism.
“It has long been recognised that there is a need to develop risk stratification models specifically for patients with this disease. The lack of an appropriate simulation model based entirely on large clinical data from patients with type 1 diabetes has been a major gap until now,” says Professor Philip Clarke, Director of Oxford University’s Health Economics Research Centre.
Using large data from the Swedish National Diabetes Register, the researchers developed the model and identified a large number of inter-relationships between risk factors, complications history, and occurrence of the complications.
The study reveals that patients with type 1 diabetes have a much lower life expectancy compared with the general population. Specifically, the mean life expectancy of Swedish patients with the disease is approximately 13 years lower compared to the sex- and age-matched people from the general population.
Professor Clarke says the new model is a major advance over existing simulation models and hopes the model will help governments and industries in evaluating the benefits of type 1 diabetes treatments.
“It can predict risk factor progression, impact of risk factors on the occurrence of an event, and the dependencies between the occurrences of events,” he says.
“The development of our model is timely given that new technologies for patients with type 1 diabetes are emerging. In many countries, access to new technologies requires a demonstration that these interventions represent value for money, and this will require increasing use of simulation models to quantify the benefits of interventions in terms of relevant outcomes”, the researchers indicate.
An Tran-Duy, Josh Knight, Andrew J. Palmer, Dennis Petrie, Tom W.C. Lung, William H. Herman, Björn Eliasson, Ann-Marie Svensson, Philip M. Clarke (2020): A Patient-Level Model to Estimate Lifetime Health Outcomes of Patients With Type 1 Diabetes. Diabetes Care Jun 2020, dc192249; DOI: 10.2337/dc19-2249.