Health & Medicine, UK (Commonwealth Union) – Scientists from the Oxford University, Nuffield Department of Primary Care Health Sciences have produced a new tool that can forecast an individual’s risks of developing oesophageal cancer 10 years ahead.
Oesophageal cancer is a prevalent type of cancer that affects the elongated tube responsible for transporting food from the throat to the stomach. Standing as the eighth most common cancer worldwide, this tool employs expansive patient databases and advanced computational methods. It is named ‘CanPredict (oesophageal)’ and holds the potential to transform lives by pinpointing individuals at a heightened risk of this cancer, thereby enabling targeted screenings and timely interventions.
Appearing recently in ‘The Lancet Regional Health – Europe’ it unveils the culmination of efforts by a collaborative team of researchers hailing from the Universities of Oxford, Cambridge, and Nottingham. Their breakthrough creation, ‘CanPredict (oesophageal)’, not only forecasts the likelihood of oesophageal cancer within a ten-year span but also identifies individuals with elevated risk levels, prompting the need for further screening. This proactive approach could potentially lead to earlier diagnoses and ultimately better patient outcomes. While methods like endoscopy exist for oesophageal cancer detection, they are often reserved for symptomatic patients or those already categorized as high risk.
Professor Julia Hippisley-Cox, a practicing GP and the lead researcher affiliated with the Nuffield Department of Primary Care Health Sciences at the University of Oxford, underscores the transformative potential of the CanPredict tool: Further indicated that given the current absence of a widespread screening initiative within the NHS, the development of an innovative strategy to enable early detection remains of utmost importance. CanPredict offers a tailored approach, honing in on those most urgently in need, and pinpointing patients who are at risk of oesophageal cancer. She also indicated that it holds the promise of facilitating earlier cancer diagnoses, a critical juncture where treatment options are more likely to be available.
Researchers indicated that to provide a sense of scale, utilizing CanPredict to monitor solely the top 20% of individuals at high risk results in the identification of more than 3 out of 4 anticipated cases (76%) of oesophageal cancer diagnoses expected over the next ten years.
Oesophageal cancer holds significant global health implications and frequently evades detection until its advanced stages, underscoring the critical importance of early recognition. This novel algorithm has the potential to reshape the approach to the disease for primary care practitioners and healthcare systems at large. For instance, it could be integrated into the workflow of a GP practice, performed periodically to identify high-risk patients, thereby obviating the necessity for these patients to attend consultations, as indicated in the study.
The development of this innovative tool involved an analysis of anonymized medical records encompassing more than 12 million patients from GP practices contributing to the QResearch database throughout England. This comprehensive dataset yielded over 16,000 instances of oesophageal cancer. The researchers integrated significant variables such as age, lifestyle behaviors, medical history, and medication usage into the CanPredict algorithm.
After its formulation, CanPredict underwent rigorous testing. It was evaluated in separate sets of QResearch practices involving over 4 million patients, as well as the Clinical Practice Research Database encompassing more than 2.5 million patients. Throughout the testing phase, CanPredict effectively forecasted an individual’s risk of oesophageal cancer within the subsequent decade. Notably, it surpassed existing models designed to estimate the risk of oesophageal cancer.
Winnie Mei, co-author who is also Research Fellow in Medical Statistics and Epidemiology from the University of Oxford, Nuffield Department of Primary Care Health Sciences, says ‘Our study bridges a significant gap in primary care. By identifying high-risk patients earlier, we can potentially offer them life-saving interventions. This tool is a testament to the power of combining technology with medical research.’
