How AI Can Predict Pancreatic Cancer Risk 3 Years Before Diagnosis
Image by Brat Co. / Stocksy
May 19, 2023
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How AI detects cancer risk
For a study published earlier this month, researchers at Harvard Medical School (HMS) and the University of Copenhagen gave an AI tool access to 9 million patient records3 across the Danish medical system and U.S. VA hospitals. They trained to tool to read diagnostic codes and identify patterns between cancer diagnosis and other preexisting diagnoses. Then, it gave the tool a new set of medical records and asked it to identify each patient’s risk of pancreatic cancer within three months, six months, one year, two years, and three years.
When assessing short-term risk, the tool flagged more obvious diagnostic codes, like unspecified jaundice, diseases of biliary tract, abdominal and pelvic pain, weight loss, and neoplasms of digestive organs, which researchers say could actually be symptoms of already present cancer. But when asked to assess long-term risk, the tool identified diagnoses that are not directly related, like Type 2 and insulin-independent diabetes.
Researchers believe the tool is more accurate than current population-wide estimates and at least as accurate as genetic testing, which is currently given only to those already identified as high risk.
In one part of the experiment, researchers gave the tool an example real-world population of 1 million patients and asked it to identify the 1,000 patients with the highest risk of pancreatic cancer. Of the 1,000 it chose, 320 of them went on to get pancreatic cancer. And while some of the chosen patients would have been identified as high risk by their doctors, researchers believe at least 70 of those would have been newly identified as high risk by the AI tool.
Why early detection is key
Our current system relies on individual doctors to refer patients for a series of expensive and invasive tests (think a CT scan, MRI, biopsy, or endoscopic ultrasound). People usually undergo testing because of a family history of genetic mutations or symptoms that appear only once the disease has progressed.
This new tool provides a relatively inexpensive (and entirely noninvasive) way for patient files to be automatically flagged as high-risk, providing the opportunity for patients—some of whom may not have been identified as high-risk by their doctors—to be tested. Chris Sander, Ph.D., a faculty member in the Department of Systems Biology in the Blavatnik Institute at HMS, said in a news release that such a system could lead to earlier detection and treatment and ultimately, lengthen patients’ lives.
As it currently stands, most people don’t get a pancreatic cancer diagnosis until their cancer is in stage 4 and their chance of living another five years is only 1 to 3%. But for those diagnosed with pancreatic cancer in its early stages, when surgery is still an option, the five-year survival rate grows to 44%, with up to 10% of patients ultimately cured. Currently, only about 12% of cases are caught this early. But it stands to reason that a system that identifies risk factors up to three years before diagnosis would give patients a better shot at early detection.
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The takeaway
Pancreatic cancer is deadly and hard to diagnose when it’s early enough to treat. A new AI-powered tool was able to comb medical records and identify those at a higher risk for the cancer. While the tool is still in early stages, it’s an exciting development that could ultimately improve treatment options available to those with pancreatic cancer.
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