A new tool developed by researchers at the University of Nottingham in the United Kingdom can identify the risk of lung cancer ten years before the disease begins. The technology’s function is to provide results that are useful in screening tests at an early stage, saving treatment costs and increasing the chances of patients recovering.
oh can be predicted Issued by Press Lancet Respiratory Medicine. Working with members of the University of Oxford, English researchers tested the tool using the health records of around 19 million adults in the UK.
- Lung cancer is the second most common cancer in the world.
- This is the cancer that claims the most victims.
- It comes in two forms: non-small cell and small cell lung cancer.
We set out to develop a tool that could be used to identify people at high risk of developing lung cancer based on data already recorded in their medical records. When we tested this tool on individual subjects, it appeared to be better at identifying patients who developed lung cancer than some other approaches. This will help inform the prioritization of people for targeted lung cancer screening in the UK, allowing diagnoses to be made at an earlier stage.
Carol Coupland, co-author of the study.
During the development of the project, the researchers used two separate health record datasets using the QResearch Database, a tool that contains the anonymized health records of more than 35 million patients in the UK – people of all ages. , races and social groups.
It was used to identify 13 million people between the ages of 25 and 84. In all, 73,800 had a positive diagnosis of cancer. In addition, other potential factors such as smoking, age, body mass index, race, and health conditions were also analyzed.
After developing the tool, the researchers used separate health records called the Clinical Practice Research Datalink (CPRD) to test its functionality. oh can be predicted At 5-, 6-, and 10-year time points, we were able to identify people who developed lung cancer more accurately than currently recommended risk prediction methods.
Featured Image: BH Thorax
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