Researchers announced a new experimental blood test capable of detecting ovarian cancer at an early stage in patients with vague symptoms that are often misdiagnosed using current methods. Ovarian cancer is the fifth leading cause of cancer-related deaths among women, largely due to late diagnosis after the disease has spread, making treatment more difficult. Over 90% of early-stage patients experience symptoms that can be confused with benign conditions such as bloating, abdominal pain, and digestive problems. According to the researchers published in Cancer Research Communications, there were no reliable blood tests for these patients, and invasive exams usually do not detect early-stage ovarian tumors. Using machine learning tools, the researchers identified several biomarkers from a wide range of molecules and processes in the body, which can be combined into a single test that detects all subtypes of the disease at all stages.

The test was trialed at a major medical center on blood samples from about 400 women with potential ovarian cancer symptoms, showing 92% accuracy in identifying those with any stage of ovarian cancer and 88% accuracy in detecting stage one or two. Oriana Papin Zoghbi, CEO of AOA Dx based in Denver, Colorado, developing the new test, said the results show promising potential to help “make faster, more accurate decisions for women needing urgent clarity during the difficult diagnostic process.”