Researchers have developed a simple blood test that can accurately detect ovarian cancer at its early stages, potentially greatly improving care and outcomes for affected women. The test looks for two different blood markers in women showing symptoms such as pelvic pain and bloating, then uses machine learning to identify patterns difficult for humans to detect. Experts hope the UK’s National Health Service will adopt the test after regulatory approval. The UK records about 7,500 new ovarian cancer cases annually, mostly in women over 50. Currently, diagnosis relies on a combination of exams, blood tests, and sometimes biopsies, but the disease is often detected too late for effective treatment. Symptoms like bloating may not always be obvious, while other signs include persistent abdominal or pelvic pain, feeling full quickly after eating, and frequent urination.

The blood test, developed by AODx, detects substances secreted by cancer into the bloodstream even in early stages. Cancer cells release parts into the blood containing small fat-like molecules called lipids, along with certain proteins. AODx states this lipid-protein combination forms a biological fingerprint of ovarian cancer. The test uses an algorithm tested on thousands of patient samples to detect subtle patterns in these lipids and proteins indicating ovarian cancer. Alex Fisher, COO and co-founder of AODx, said the test can detect the disease “at early stages, with greater accuracy than current tools.”