Evidence map›Paper›PMID 38915970›Full record

ArticleCureus2024

Cost-Utility Analysis of Berberine Chemoprevention for Colorectal Cancer After Polypectomy.

Shuai Yuan, Tian Zhang, Yingyu Wu, Yun Lu, Feng Chang, Yumei Zhu

Abstract read
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Shuai YuanSchool of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, CHN.
Tian ZhangSchool of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, CHN.
Yingyu WuSchool of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, CHN.
Yun LuSchool of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, CHN.
Feng ChangSchool of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, CHN.
Yumei ZhuSchool of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, CHN.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Chemoprevention, such as berberine, has been developed as an alternative or complementary strategy to colonoscopy surveillance and has shown promise in reducing the morbidity and mortality of colorectal cancer. This study aims to evaluate the cost-effectiveness of berberine for postpolypectomy patients from the US third-party payer. Methods A Markov microsimulation model was developed to compare the cost and efficacy of berberine to no intervention, colonoscopy, and the combination of berberine and colonoscopy in postpolypectomy patients. Results After simulating 1 million patients, the study found that colonoscopy alone had a mean cost of $16,391 and mean quality-adjusted life-years (QALYs) of 16.03 per patient, whereas adding berberine slightly reduced the mean cost to $15,609 with a mean QALY of 16.05, making it a dominant strategy. Berberine therapy alone was less effective than colonoscopy alone, with a higher mean cost of $37,480 and a mean QALY of 15.32 per patient. However, berberine therapy was found to be a dominant strategy over no intervention. Conclusions Adding berberine to colonoscopy is the most cost-saving and effective approach for postpolypectomy patients. For patients who refuse or have limited access to colonoscopy, berberine alone is likely to be a dominant strategy compared to no intervention.

Indexed as

berberinechemopreventioncolorectal adenomascolorectal cancercost-effectivenesspolypectomy

Identifiers

PMID38915970
PMCPMC11194466

What OpenQuestion holds

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Registered trials

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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.