AI Tool Shows Promise for Identifying Lung Cancer with Simple Blood Test
Researchers from the Johns Hopkins Kimmel Cancer Center and other institutions have used artificial intelligence to develop and validate a liquid biopsy that may help identify lung cancer earlier. Johns Hopkins' website has the news.
A study showed that the artificial intelligence technology could “identify people more likely to have lung cancer based on DNA fragment patterns in the blood.” This new technology could “potentially boost lung cancer screening and reduce death rates, according to computer modeling by the team.” According to the study’s corresponding author, Victor E. Velculescu, M.D., Ph.D., they basically have a “simple blood test that could be done in a doctor’s office that would tell patients whether they have potential signs of lung cancer and should get a follow-up CT scan.”
Only about 6-10% of eligible individuals – people between ages 50 and 80 who have a smoking history – follow through on screening for lung cancer as it stands. Velculescu explains that people may be “reticent to follow through on screening…due to the time it takes to arrange and go to an appointment, and the low doses of radiation they are exposed to from the scan.”
The test Velculescu and his colleagues developed is trained to “identify the specific patterns of DNA fragments seen in the blood” of people with lung cancer versus those without. Based on an analysis of 382 people with and without cancer, “the test has a negative predictive value of 99.8%, meaning that only 2 in 1,000 individuals tested may be missed and have lung cancer.” Further, if the test “boosted the rate of lung cancer screening to 50% within five years, it could quadruple the number of lung cancers detected and increase the proportion of cancers detected early — when they are most treatable — by about 10%. That could prevent about 14,000 cancer deaths over five years.”
Matt MacKenzie | Associate Editor
Matt is Associate Editor for Healthcare Purchasing News.