Background & aims: The use of computer-aided detection (CAD) increases the adenoma detection rates (ADRs) during colorectal cancer (CRC) screening/surveillance. This study aimed to evaluate the requirements for CAD to be cost-effective and the impact of CAD on adenoma detection by endoscopists with different ADRs.
Methods: We developed a semi-Markov microsimulation model to compare the effectiveness of traditional colonoscopy (mean ADR, 26%) to colonoscopy with CAD (mean ADR, 37%). CAD was modeled as having a $75 per-procedure cost. Extensive 1-way sensitivity and threshold analysis were performed to vary cost and ADR of CAD. Multiple scenarios evaluated the potential effect of CAD on endoscopists' ADRs. Outcome measures were reported in incremental cost-effectiveness ratios, with a willingness-to-pay threshold of $100,000/quality-adjusted life year.
Results: When modeling CAD improved ADR for all endoscopists, the CAD cohort had 79 and 34 fewer lifetime CRC cases and deaths, respectively, per 10,000 persons. This scenario was dominant with a cost savings of $143 and incremental effectiveness of 0.01 quality-adjusted life years. Threshold analysis demonstrated that CAD would be cost-effective up to an additional cost of $579 per colonoscopy, or if it increases ADR from 26% to at least 30%. CAD reduced CRC incidence and mortality when limited to improving ADRs for low-ADR endoscopists (ADR <25%), with 67 fewer CRC cases and 28 CRC deaths per 10,000 persons compared with traditional colonoscopy.
Conclusions: As CAD is implemented clinically, it needs to improve mean ADR from 26% to at least 30% or cost less than $579 per colonoscopy to be cost-effective when compared with traditional colonoscopy. Further studies are needed to understand the impact of CAD when used in community practice.
Keywords: Adenoma Detection Rate; Artificial Intelligence; Computer-Aided Detection; Screening Colonoscopy.
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