A groundbreaking online tool designed to personalize diabetes treatment may significantly improve management for millions of individuals living with type 2 diabetes, according to new research.
Developed by researchers at the University of Exeter, the tool uses routine clinical data such as body mass index (BMI), cholesterol levels, and HbA1c measurements to recommend the most effective medication for each patient. This marks a potential leap forward in personalized medicine for diabetes, as the model allows healthcare providers to select from five major classes of drugs, including DPP-4 inhibitors, GLP-1R agonists, sulfonylureas, SGLT2 inhibitors, and thiazolidinediones.
Type 2 diabetes affects over three million people in England, and proper medication is critical to managing blood sugar levels and preventing complications like kidney disease and nerve damage. However, a study found that fewer than 20% of diabetes patients in England are receiving the most appropriate medication for their condition.
The tool, which was developed and tested using data from one million UK patients, demonstrated promising results. Published findings in The Lancet show that patients prescribed drugs suggested by the model experienced significant improvements in managing their blood sugar levels. In fact, they showed a 38% lower risk of poor blood sugar control over five years, along with reduced risks of complications affecting the heart and kidneys.
Dr. John Dennis, associate professor at the University of Exeter and lead researcher, emphasized that this approach represents a major breakthrough in treating diabetes. “For the first time, our model enables quick identification of the best treatment, reducing risks associated with the condition,” he said.
Importantly, the tool’s simplicity is a key strength. It uses routine health measurements such as weight, sex, and blood tests, meaning it can be implemented without additional costs or complex procedures. Professor Andrew Hattersley, a colleague at Exeter, pointed out that the model can be seamlessly integrated into existing clinical practices.
Despite its potential, the study also highlighted the current underutilization of effective treatments. According to the research, only 17.8% of new type 2 diabetes treatments in England were optimal, according to the model’s predictions, underscoring the tool’s potential to enhance treatment strategies at a national level.
The model is currently being tested on a wider scale with 22,500 patients in Scotland, with plans for broader implementation if successful. Dr. Elizabeth Robertson, director of research at Diabetes UK, stressed that if the tool proves effective in clinical practice, it could transform diabetes care, helping countless individuals achieve better blood sugar control and reducing the risk of severe complications.
With diabetes affecting more than 4.6 million people in the UK, including 1.3 million with undiagnosed type 2 diabetes, the tool could represent one of the most significant advances in care for the condition in over a decade.
Dr. Adam Babbs, head of translation at the Medical Research Council, which funded the research, noted the vast potential of precision medicine to address the variations in how patients respond to treatments, ultimately improving patient outcomes and streamlining healthcare resources.
As the tool progresses through trials, the global impact on type 2 diabetes care could be substantial, offering hope for more effective, personalized treatment strategies for millions worldwide.
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