The AI model can identify individuals with the highest risk of pancreatic cancer up to three years prior to their formal diagnosis. A new study, led by researchers from Harvard Medical School, the University of Copenhagen, VA Boston Healthcare System, Dana-Farber Cancer Institute, and the Harvard T
Pancreatic cancer is a type of cancer that starts in the pancreas, a glandular organ located behind the stomach. It is known to be one of the most aggressive and lethal forms of cancer, with a five-year survival rate of only 9%.
Currently, there are no population-based tools to screen broadly for pancreatic cancer. Those with a family history and certain genetic mutations that predispose them to pancreatic cancer are screened in a targeted fashion. But such targeted screenings can miss other cases that fall outside of those categories, the researchers said.
“Many types of cancer, especially those hard to identify and treat early, exert a disproportionate toll on patients, families, and the healthcare system as a whole,” said study co-senior investigator Søren Brunak, professor of disease systems biology and director of research at the Novo Nordisk Foundation Center for Protein Research at the University of Copenhagen.
By comparison, pancreatic cancer is harder and more expensive to screen and test for. Physicians look mainly at family history and the presence of genetic mutations, which, while important indicators of future risk, often miss many patients. One particular advantage of the AI tool is that it could be used on any and all patients for whom health records and medical history are available, not just in those with a known family history or genetic predisposition for the disease.
About 44 percent of people diagnosed in the early stages of pancreatic cancer survive five years after diagnosis, but only 12 percent of cases are diagnosed that early. The survival rate drops to 2 to 9 percent in those whose tumors have grown beyond their site of origin, researchers estimate.
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