Transforming Early Cancer Detection outside Secondary Care Through Emerging Diagnostic Technologies

Abstract Background Early cancer diagnosis is a major health-system priority, particularly for cancers presenting with vague, non-specific symptoms. Current screening programmes remain limited to selected cancers with more site-specific symptoms. Innovative diagnostic technologies may offer opportunities for earlier detection outside secondary care settings. This horizon scan aimed to identify and characterise emerging technologies for the early detection of cancers with generic symptoms for potential use in primary care, community or home-based settings. Methods A horizon scanning and evidence synthesis approach was used. Searches were conducted from 2020 in Embase, clinical trial registries, supplemented by relevant systematic reviews, then screened against predefined eligibility criteria to support early cancer detection. Data was extracted on study and/or clinical trial details, technology type, developers, sample or data source, cancer type, and technology readiness level. Findings were summarised descriptively. Results After deduplication, 5,293 records were screened, including 4,791 studies and 502 clinical trial protocols. Data extraction was completed for 196 studies, identifying 169 technologies, with 67 targeting generic cancer detection. Most technologies were biomarker-based (n=36), followed by other technologies (n=19), and AI and digital technologies (n=12). Technologies ranged from TRL-2 to TRL-7, with most technologies at TRL-4, indicating early laboratory-stage validation. Blood, plasma and serum were the most common sample types, suggesting stronger suitability for GP or community settings than home testing. A small number of technologies used saliva or urine samples, which may be more compatible with home-based testing. Research activity was concentrated around lung, colorectal, pancreatic, liver, oesophageal and multi-cancer detection. Thirty-one clinical trials for generic cancer detection were identified. Conclusions The emerging landscape for generic cancer detection is active but largely early-stage. Biomarker-based and AI-enabled technologies show potential to support earlier diagnosis outside secondary care, although evidence gaps remain around clinical validity, implementation, equity, follow-up pathways and health-system readiness.