A simple blood test could flag lung cancer years earlier than current methods, potentially catching over 2,500 additional early-stage cases in the UK each year. Lung cancer kills 34,800 people annually in the UK, largely because more than 70% of cases are diagnosed at stage III or IV, when five-year survival plummets to below 16%. Current screening relies on low-dose CT scans, which are resource-intensive and reach only 40% of eligible people in England. The OXcan test uses seven protein biomarkers linked to tumour growth and inflammation, analysed via a standard blood sample and interpreted by an explainable machine-learning model. In initial validation, it achieved 82% sensitivity and 85% specificity. If the test performs as expected in this 10,000-person NHS trial, it could reduce demand for CT scans by 84% and save the health service over £40 million annually. It would also allow clinicians to safely skip scans for very low-risk individuals, while better stratifying those with ambiguous lung nodules. The result would be a scalable, minimally invasive triage tool that improves screening uptake, especially in underserved groups, and shifts diagnoses toward earlier, more treatable stages.
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Background: Lung cancer is the leading cause of cancer mortality globally, responsible for 34,800 deaths annually in the UK and accounting for over 20% of all cancer-related deaths. Over 70% of cases are diagnosed at late stages (III/IV), where five-year survival drops to 16% and 4.3% respectively, placing a substantial burden on patients and the healthcare system. Early detection significantly improves outcomes; stage I/II lung cancers have a five-year survival rate of 56% and require less intensive treatment. Low dose CT(LDCT) is the current gold standard for lung cancer screening (LCS) in high-risk populations; however, its implementation is challenged by infrastructural demands, workforce shortages, incidental findings, and limited coverage currently at only 40% in England. Existing demographic based clinical risk tools such as PLCOm2012 and LLPv2 have limited sensitivity (<80%) and miss a substantial proportion of resectable cancers. Recent advances in proteomics and machine learning indicate that molecular biomarkers offer a promising route for non-invasive, scalable, and more accurate risk stratification. OXcan have developed a biomarker panel, which was identified using proximity extension assay (PEA)-based proteomics and explainable machine learning (XAI) models, followed by technical and clinical validation using Luminex xMAP® multiplex immunoassays. The seven selected biomarkers are linked to key lung cancer pathways, including angiogenesis, inflammation, and tumour proliferation. The test achieved strong performance in independent validation (AUC=0.92; sensitivity=82%; specificity=85%). Aims and Objectives: This study aims to clinically validate the OXcan blood test to: Evaluate its performance in classifying LDCT outcomes and lung cancer diagnosis. Identify very low risk individuals who may not require LDCT. Stratify individuals with indeterminate LDCT findings (e.g., pulmonary nodules). Demonstrate its potential to enhance LDCT screening efficiency and population health outcomes. Deliverables include successful recruitment and follow-up of 10,000 participants, clinical performance evaluation, health economic modelling, dissemination of results and commercialisation strategy enabling UK market launch. Methods: 10,000 high-risk participants aged 55–74 will be recruited prospectively through the Cheshire & Merseyside NHS LCS programme. Blood samples will be collected and analysed using the Luminex platform. Predictive models will be applied to classify results, which will be compared with LDCT and cancer outcomes. Performance metrics (sensitivity, specificity, PPV, NPV) will be assessed. A parallel economic analysis will evaluate cost-effectiveness (Incremental Cost-Effectiveness Ratio) and quality-adjusted life years (QALYs) from an NHS and social care perspective. Stakeholder engagement and market access activities will inform commercialisation and adoption of the blood test. Anticipated Impact and Dissemination: The OXcan blood test is a scalable, minimally invasive tool that may identify over 2500 additional early-stage lung cancers annually, reduce LDCT demand by 84%, and deliver over £40 million/year in healthcare savings. It addresses NHS resource constraints, with the potential to improve screening uptake (particularly in underserved groups) and reduce radiation exposure risk. Dissemination will include peer-reviewed publications, policy briefs, public-facing materials co-designed with patient and public involvement groups, and engagement with national screening bodies. Pilot implementation within NHS services will follow to facilitate widespread adoption.
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