Researchers from the Johns Hopkins Kimmel Cancer Center and other institutions have developed and validated a liquid biopsy test using artificial intelligence (AI) to help identify lung cancer earlier.
The new study published in Cancer Discovery demonstrated that the new blood test could help accelerate lung cancer screening while reducing death rates.
Currently the leading cause of global cancer incidence and death worldwide, lung cancer accounts for an estimated two million diagnoses and 1.8 million deaths annually.
For the last five years, researchers have developed a test to detect patterns of DNA fragments found in patients with lung cancer.
Participants with and without cancer who met the criteria for low-dose computed tomography (CT) were recruited to receive the blood test to determine which patients were most at risk and would benefit from a follow-up CT screening to help overcome issues regarding appointments, such as the time it takes to arrange and go to an appointment, as well as low-dose exposure to radiation.
The AI software was trained to identify the specific patterns of DNA fragments seen in the blood of 576 people with or without lung cancer, which was then verified to work in a second group of 382 people with and without cancer.
The team found that the test has a negative predictive value of 99.8%, meaning that only two in every 1,000 people may be missed and have lung cancer.
The team plans to seek approval from the US Food and Drug Administration for lung cancer screening and plans to determine whether a similar approach could be used to detect other types of cancer.
Victor Velculescu, professor of oncology and co-director, cancer genetics and epigenetics programme, Johns Hopkins Kimmel Cancer Center, commented: “The test is inexpensive and could be done at a very large scale.
“We believe it will make lung cancer screening more accessible and help many more people get screened. This will lead to more cancers being detected and treated early.”

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