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September 28, 2025Journal of Medical Internet Research4 citationsOpen Access

The Cost-Effectiveness of AI-Assisted Colonoscopy as a Primary or Secondary Screening Test in a Population-Based Colorectal Cancer Screening Program: Markov Modeling–Based Cost Effectiveness Analysis

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MWMartin C. S. WongJHJunjie HuangTLThomas Y. Lam

Key Points

  • AI-assisted colonoscopy strategy showed the lowest incremental cost-effectiveness ratio, making it the most cost-effective screening method.
  • Compared to no screening, the AI-assisted colonoscopy yielded significant reductions in cancer-related life years lost and higher CRC cases prevented.
  • The analysis utilized Markov modeling to evaluate various screening strategies for colorectal cancer in a hypothetical Asian population.
  • AI-assisted colonoscopy significantly dominated conventional colonoscopy in terms of cost-effectiveness, reaffirming its potential clinical advantages.

Abstract

Background Colorectal cancer (CRC) is the third most common cancer worldwide and poses a heavy burden on health care systems. Early screening for CRC through colonoscopy can effectively reduce both the incidence and mortality associated with CRC. However, the sensitivity of conventional colonoscopy is limited by the level of experience of physicians. Recently, artificial intelligence (AI) –assisted colonoscopy has been shown to have higher sensitivity in detecting CRC and mitigating the limitations concerning physician experience, but few studies have evaluated the cost-effectiveness of AI-assisted colonoscopy in CRC screening. Objective This study aimed to evaluate the cost-effectiveness of various CRC screening strategies, including no screening, fecal immunochemical test (FIT) positive result followed by a conventional colonoscopy, FIT positive result followed by AI-assisted colonoscopy, direct colonoscopy, and direct AI-assisted colonoscopy. Methods This study modeled a hypothetical population based on current clinical practice in Asia, where CRC screening typically begins at the age of 50 years. The cost-effectiveness of various population-based CRC screening strategies, including AI-assisted colonoscopy, was evaluated by comparing incremental cost-effectiveness ratios (ICERs) and outcome measures such as cancer-related life years lost, number of CRC cases prevented, life years saved, and total cost per life year saved. Data from the international literature and the government gazette were accessed to calculate relevant cost and performance estimates. The data were entered into a decision analysis algorithm based on a Markov model. Results Compared to no screening strategy, the ICERs of FIT+colonoscopy (FIT followed by conventional colonoscopy if the FIT result is positive), FIT+AI-assisted colonoscopy (FIT followed by AI-assisted colonoscopy if the FIT result is positive), colonoscopy alone, and AI-assisted colonoscopy were US 138, 539, US 122, 539, US 203, 929, and US 180, 444, respectively. When compared with FIT+colonoscopy, the FIT+AI-assisted colonoscopy strategy resulted in fewer cancer-related life years lost (5355 y vs 5327 y), a higher number and proportion of CRC cases prevented (120 vs 132 and 3. 7% vs 4. 1%), more life years saved (280 y vs 308 y), and lower total cost per life year saved (US 944, 008 vs US 854, 367). FIT+AI-assisted colonoscopy, which had the lowest ICER (US 122, 539) dominated all other strategies, particularly compared to FIT+colonoscopy, with an ICER of –US 36, 462. Among primary screening methods, AI-assisted colonoscopy dominated conventional colonoscopy (ICER –US 39, 040). Conclusions For an Asian population, FIT followed by AI-assisted colonoscopy represented the most cost-effective CRC screening strategy. It had the lowest ICER and the lowest additional cost among all 4 evaluated strategies.

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Cite This Study

Wong et al. (2025) studied this question.

synapsesocial.com/papers/68d909fc41e1c178a14f5b8ahttps://doi.org/10.2196/67762
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