ArticleFrontiers in public health2025
Integrating geospatial and environmental factors in colorectal cancer epidemiology: a regional study.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Gut microbiota signatures and machine learning-based candidate feature prioritization in advanced colorectal cancer.Archives of microbiology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Colorectal cancer poses a major health challenge in Gansu Province, being one of the top causes of both incidence and mortality among gastrointestinal cancers. This study aims to analyze the epidemiological patterns of colorectal cancer in Gansu Province, while exploring potential associations with environmental determinants. Method: We analyzed clinical records of all colorectal cancer cases from 2013 to 2023, retrieved from hospital information systems across 87 counties in Gansu Province, encompassing municipal, district, county, and township-level medical institutions. A thorough analysis was conducted employing various methods, including Joinpoint regression, spatial autocorrelation, spatiotemporal scanning, and Geo-detector analysis, using specialized software (Joinpoint 5.0, ArcGIS 10.8, and SaTScan). Our study explored the relationship between colorectal cancer incidence in Gansu Province and 14 Environmental factors. Result: The results indicate a steady rise in colorectal cancer incidence over the 11-year period and the highest age-standardized incidence rates of colorectal cancer occurred in Jinchuan, Chengguan, Suzhou, Baiyin, and Liangzhou districts, contrasting sharply with the significantly lower rates documented in Liangdang, Kang, Heshui, Huining, Zhengning, and Cheng counties. Spatial and spatiotemporal analyses identified several significant high- and low-risk clusters of colorectal cancer throughout Gansu Province, demonstrating both spatial and temporal variability in disease distribution. The Geo-detector indicated that colorectal cancer incidence was significantly linked to the distribution of climatic conditions (precipitation and temperature), ecological factor, and certain air pollutants. Multivariate spatial analysis was used to further explore the relationship between environmental factors and the incidence of colorectal cancer. Conclusion: Our research highlighted notable spatial variability in colorectal cancer incidence across Gansu Province, with geospatial and spatiotemporal analyses uncovering high-risk clusters and important environmental factors.
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.