At a glance:
- By EKATERINA PESHEVA
- An AI tool identified people at the highest risk for pancreatic cancer up to three years before actual diagnosis.
- The findings point to the promise of AI for mass screening to help expedite the diagnosis of an aggressive disease often identified with serious delays.
- Pancreatic cancer is one of the deadliest cancers in the world and its toll is projected to increase.
An artificial intelligence tool has successfully identified people at the highest risk for pancreatic cancer up to three years before diagnosis using solely the patients' medical records, according to new research led by investigators at Harvard Medical School and the University of Copenhagen, in collaboration with VA Boston Healthcare System, Dana-Farber Cancer Institute, and the Harvard T.H. Chan School of Public Health.
The findings, published May 8 in Nature Medicine, suggest that AI-based population screening could be valuable in finding those at elevated risk for the disease and could expedite the diagnosis of a condition found all too often at advanced stages when treatment is less effective and outcomes are dismal, the researchers said. Pancreatic cancer is one of the deadliest cancers in the world, and its toll projected to increase.
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.
"One of the most important decisions clinicians face day to day is who is at high risk for a disease, and who would benefit from further testing, which can also mean more invasive and more expensive procedures that carry their own risks," said study co-senior investigator Chris Sander, faculty member in the Department of Systems Biology in the Blavatnik Institute at HMS. "An AI tool that can zero in on those at highest risk for pancreatic cancer who stand to benefit most from further tests could go a long way toward improving clinical decision-making."
Applied at scale, Sander added, such an approach could expedite detection of pancreatic cancer, lead to earlier treatment, and improve outcomes and prolong patients' life spans.
"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.
"AI-based screening is an opportunity to alter the trajectory of pancreatic cancer, an aggressive disease that is notoriously hard to diagnose early and treat promptly when the chances for success are highest," Brunak said.
In the new study, the AI algorithm was trained on two separate data sets totaling 9 million patient records from Denmark and the United States. The researchers "asked" the AI model to look for telltale signs based on the data contained in the records.
