ArticleJournal of medical Internet research2025
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.
Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Comparative Efficacy of Different AI Systems for Polyp Detection by Size During Colonoscopy: Systematic Review and Network Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Effectiveness of an artificial intelligence-assisted training program on cleaning competency among hospital environmental service staff.BMC health services research · 2026Trial
- Assessing the Value for Money of AI-Assisted Technologies for Older Adults: Scoping Review of Economic Evaluations.Journal of medical Internet research · 2026Article
- Closing Editorial: Toward Safe, Equitable, and Intelligent Healthcare.Healthcare (Basel, Switzerland) · 2026Article
- Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundColorectal 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.
objectiveThis 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.
methodsThis 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.
resultsCompared 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).
conclusionsFor 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.