ArticleFrontiers in microbiology2025
Intestinal microbiota as biomarkers for different colorectal lesions based on colorectal cancer screening participants in community.
Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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
4 citing papers in PubMed.
- Deciphering Post-surgery Gut Microbial Dynamics in Colorectal Cancer through Multi-cohort Machine Learning.Current microbiology · 2026Article
- Clinical applications of gut microbiome for non-invasive diagnosis of colorectal neoplasia.Journal of gastroenterology · 2026Article
- Gut Microbiota and Colorectal Cancer: Is Microbial Dysbiosis in Carcinogenesis an Emerging Risk Factor?Cureus · 2026Review
- Metagenomic Signatures of Colorectal Cancer in the Jordanian Population: A Regional Case-Control Analysis Using 16S rRNA Profiling.Microorganisms · 2025Article
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
Introduction: The dysregulation of intestinal microbiota has been implicated in the pathogenesis of colorectal cancer (CRC). However, the utilization of intestinal microbiota for identify the lesions in different procedures in CRC screening populations remains limited. Methods: A total of 529 high-risk individuals who underwent CRC screening were included, comprising 13 advanced adenomas (Aade), 5 CRC, 59 non-advanced adenomas (Nade), 129 colon polyps (Pol), 99 cases of colorectal inflammatory disease (Inf), and 224 normal controls (Nor). 16S rRNA gene sequencing was used to profile the intestinal microbiota communities. The Gut Microbiota Health Index (GMHI) and average variation degree (AVD) were employed to assess the health status of the different groups. Results: Our findings revealed that the Nor group exhibited significantly higher GMHIs and the lowest AVD compared to the four Lesion groups. The model incorporating 13 bacterial genera demonstrated optimal efficacy in distinguishing CRC and Aade from Nor, with an area under the curve (AUC) of 0.81 and a 95% confidence interval (CI) of 0.72 to 0.89. Specifically, the 55 bacterial genera combination model exhibited superior performance in differentiating CRC from Nor (AUC 0.98; 95% CI, 0.96-1), the 25 bacterial genera combination showed superior performance in distinguishing Aade from Nor (AUC 0.95). Additionally, the 27 bacterial genera combination demonstrated superior efficacy in differentiating Nade from Nor (AUC 0.82). The 13 bacterial genera combination exhibited optimal performance in distinguishing Inf from Nor (AUC 0.71). Discussion: Our study has identified specific microbial biomarkers that can differentiate between colorectal lesions and healthy individuals. The intestinal microbiota markers identified may serve as valuable tools in community-based CRC screening programs.
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.