A new blood test could identify ovarian cancer at early stages and may boost treatment outcomes for women, pending regulatory approval. The approach screens for two sets of blood markers in people with symptoms such as pelvic pain and bloating, and uses machine learning to pick up patterns that humans find hard to spot. Experts say it could be adopted by the NHS in future, subject to regulatory clearance. There are about 7,500 new UK cases each year, typically in women over 50. Ovarian cancer is usually diagnosed through a mix of scans and blood tests, and sometimes biopsies, but it is often detected late when treatment is harder.

Developed by AOA Dx, the test looks for what cancer releases into the bloodstream. Cancer cells shed fragments loaded with lipid-like molecules and certain proteins. The combination of these lipids and proteins is described by the company as a molecular fingerprint for ovarian cancer. An algorithm trained on thousands of patient samples is used to recognise subtle patterns across these markers that indicate the disease. “The test can detect the disease at early stages and with greater accuracy than current tools,” said Alex Fisher, chief operating officer and co-founder of AOA Dx. Dr Abigail McElhinny, the company’s chief science officer, added: “By using machine learning to combine multiple biomarker types, we’ve developed a diagnostic tool that detects ovarian cancer across the molecular complexity of the disease in sub-types and stages. This platform offers a great opportunity to improve the early diagnosis of ovarian cancer potentially resulting in better patient outcomes and lower costs to the healthcare system.”

A study led by researchers at the University of Manchester and the University of Colorado and published in Cancer Research Communications tested 832 samples using the platform. In Colorado samples, the test accurately detected ovarian cancer across all stages 93% of the time, and 91% in early stages. In Manchester samples, accuracy was 92% across all stages and 88% in early stages. Emma Crosbie, professor at the University of Manchester and honorary consultant in gynaecological oncology at Manchester University NHS Foundation Trust, said the platform has the potential to significantly improve patient care and outcomes for women diagnosed with ovarian cancer. “We are eager to continue advancing this important research through additional prospective trials to further validate and expand our understanding of how this could be integrated into existing healthcare systems.”