Evidence map›Paper›PMID 37273970›Full record

ArticleJournal of the Canadian Association of Gastroenterology2023

Cost-effectiveness of Artificial Intelligence-Aided Colonoscopy for Adenoma Detection in Colon Cancer Screening.

Alan N Barkun, Daniel von Renteln, Hamid Sadri

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the Canadian Association of Gastroenterology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 5 pooled it
9.2field-weighted citation impact, top 2% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 5 syntheses or guidelines pooled it, 40 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 1 country.

Alan N BarkunDivision of Gastroenterology, McGill University Health Center, Montreal, Quebec, Canada.
Daniel von RentelnDivision of Gastroenterology, the University of Montreal Hospital and University of Montreal Hospital Research Center, Montreal, Quebec, Canada.
Hamid SadriDepartment of Health Economics and Outcomes Research, Medtronic Canada, Brampton, Ontario, Canada.ORCID https://orcid.org/0000-0003-2004-7060
McGill University Health Centre · CAMedtronic (Canada) · CAUniversité de Montréal · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: Artificial intelligence-aided colonoscopy significantly improves adenoma detection. We assessed the cost-effectiveness of the GI Genius technology, an artificial intelligence-aided computer diagnosis for polyp detection (CADe), in improving colorectal cancer outcomes, adopting a Canadian health care perspective. Methods: A Markov model with 1-year cycles and a lifetime horizon was used to estimate incremental cost-effectiveness ratio comparing CADe to conventional colonoscopy polyp detection amongst patients with a positive faecal immunochemical test. Outcomes were life years (LYs) and quality-adjusted life years (QALY) gained. The analysis applied costs associated with health care resource utilization, including procedures and follow-ups, from a provincial payer's perspective using 2022 Canadian dollars. Effectiveness and cost data were sourced from the literature and publicly available databases. Extensive probabilistic and deterministic sensitivity analyses were performed, assessing model robustness. Results: Life years and QALY gains for the CADe and conventional colonoscopy groups were 19.144 versus 19.125 and 17.137 versus 17.113, respectively. CADe and conventional colonoscopies' overall per-case costs were $2990.74 and $3004.59, respectively. With a willingness-to-pay pre-set at $50,000/QALY, the incremental cost-effectiveness ratio was dominant for both outcomes, showing that CADe colonoscopy is cost-effective. Deterministic sensitivity analysis confirmed that the model was sensitive to the incidence risk ratio of adenoma per colonoscopy for large adenomas. Probabilistic sensitivity analysis showed that the CADe strategy was cost-effective in up to 73.4% of scenarios. Conclusion: The addition of CADe solution to colonoscopy is a dominant, cost-effective strategy when used in faecal immunochemical test-positive patients in a Canadian health care setting.

Indexed as

Adenoma detectionArtificial-intelligenceCADeColonoscopyColorectal cancer

Identifiers

PMID37273970
PMCPMC10235593
OpenAlexW4362706287

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.