Aid Scan Tools, based on diagnostic prediction models, aim to assist general practitioners in identifying potential cancer cases. However, their actual impact on diagnosis speed, patient quality of life, and survival rates remains uncertain. This article delves into the evidence surrounding the validation, clinical effectiveness, and cost-effectiveness of these tools in primary care.
Examining the Effectiveness of Aid Scan Tools
Two systematic reviews were conducted to assess the clinical effectiveness and the development, validation, and accuracy of cancer diagnostic prediction models used by general practitioners. The first review analyzed five studies, varying in design and quality, focusing on three different diagnostic tools. The findings revealed no conclusive evidence linking the use of these tools to improved patient outcomes. The second review encompassed 43 studies, examining prediction models at various stages of development for 14 different cancer types, including multiple cancers. Most of these studies centered around QCancer® (ClinRisk Ltd, Leeds, UK) and general risk assessment tools.
Cost-Effectiveness and Current Usage in the UK
A decision-analytic model was employed to explore the cost-effectiveness of these tools in colorectal cancer, comparing outcomes and costs between strategies that utilized the tools and those that didn’t. Due to the lack of studies demonstrating clinical outcomes, QCancer and risk assessment tools were compared against fecal immunochemical testing. The model indicated that the cost-effectiveness of these diagnostic tools hinges on demonstrating tangible patient survival benefits. Key uncertainties included the sensitivity of fecal immunochemical testing and the specificity of QCancer and risk assessment tools in low-risk populations.
A survey of 4600 general practitioners in the UK aimed to gauge the availability and use of cancer decision support tools. The results showed that such tools were available in 36.6% of practices and likely used in 16.7%. No significant difference was found in 2-week-wait referral rates between practices with and without access to QCancer or risk assessment tools.
Limitations and Future Directions
The current evidence base for aid scan tools is limited. Many diagnostic prediction models lack external validation, and data on current UK practice, clinical outcomes of diagnostic strategies, and quality-of-life impacts are scarce. The survey faced limitations due to low response rates.
Further research is crucial to validate existing models, particularly risk assessment tools. Assessing the impact of these tools on time to diagnosis and treatment, stage at diagnosis, and overall health outcomes is essential. Understanding how general practitioners interact with these tools in consultations could shed light on implementation barriers and potential for improved clinical effectiveness. Continued research and development in this area are vital to harnessing the full potential of aid scan tools in cancer diagnosis.
