NHS hospitals are rolling out an AI-powered blood test designed to screen women for womb cancer before they undergo invasive diagnostic procedures. The test targets postmenopausal women who present with heavy bleeding, a common symptom that prompts referral for further investigation.
Around 90,000 postmenopausal women in England receive GP referrals annually for womb cancer checks following heavy bleeding complaints. Only about 10,000 of these women actually have womb cancer, meaning the vast majority undergo invasive procedures unnecessarily. The AI blood test could filter out low-risk patients before they enter the invasive screening pathway, reducing both patient burden and healthcare costs.
The blood test works by analyzing biomarkers that indicate cancer risk. AI algorithms trained on existing patient data can identify patterns associated with malignancy, allowing clinicians to prioritize women most likely to have cancer for immediate invasive examination. Those with low risk scores could either skip invasive checks entirely or have them delayed pending symptom progression.
This approach addresses a real clinical problem. Endometrial biopsy, the standard invasive diagnostic tool, causes discomfort and carries infection risks. Women undergoing unnecessary procedures face anxiety, recovery time, and potential complications. By using a simple blood draw as a gatekeeper, the NHS can improve patient experience while maintaining diagnostic accuracy.
Several NHS hospital trusts have begun implementing the blood test in preparation for wider deployment. Early results reportedly show strong accuracy in distinguishing cancer from benign causes of bleeding, though specific performance metrics weren't disclosed in available information.
The initiative reflects growing NHS interest in AI-assisted triage. Blood tests offer scalability and accessibility compared to invasive procedures. If this test proves cost-effective in real-world NHS settings, it could serve as a model for similar screening programs in other cancer types where excessive referrals strain diagnostic capacity.
The rollout timing remains unclear,