PCN115 Economic Evaluation of Artificial Intelligence-Assisted Colonoscopy for Routine Screening of Low- to High-Risk Colorectal Cancer Patients in the United Kingdom

Abstract

An increase in adenoma detection rates (ADRs) in routine colonoscopy screening has been shown to decrease the incidence and subsequent mortality rates of colorectal cancer (CRC). The application of artificial intelligence (AI)-assisted colonoscopy in recent clinical trials has demonstrated significant increase in ADRs compared to standard colonoscopy (SC). Thus, this study evaluates the long-term clinical- and cost-effectiveness of using AI-assisted colonoscopy versus SC. A Markov model simulating the natural history for low- to high-risk CRC patients (N=1,000) was developed from the UK healthcare perspective. The model tracked patients from the age of 50 years through screening, stages of CRC at diagnosis, disease progression, remission, and death. Clinical efficacy and cost inputs were obtained from NHS Reference Costs and literature sources. Outcomes included life-years gained, CRCs prevented, costs and health care resources adverted, quality-adjusted life years (QALYs) and incremental cost-effectiveness ratio (ICER). A discount rate of 3.5% was used in the calculations. A range of sensitivity analyses were conducted to test the robustness of the economic model. Price sensitivity analysis was also conducted to provide value-based pricing ranges of AI-assisted colonoscopy at different willingness-to-pay (WTP) thresholds. The adoption of AI-assisted colonoscopy compared to SC was expected to reduce long-term risks of interval CRC by 0.27%. The average life-years and QALYs gained were 0.004 and 0.008, respectively. Price sensitivity analysis demonstrated AI software to be cost-effective at a WTP threshold of £20,000–£30,000/QALY. The parameters with the largest impact on the ICER were the cost of AI software, transition probabilities for disease progression and ADRs. This is the first published economic analysis of AI-assisted colonoscopy in the UK. These results suggest that AI-assisted colonoscopy could be cost-effective. However, there is value in reducing the uncertainty around these cost-effectiveness estimates to better inform future screening policy.