Evidence map›Paper›PMID 42245725›Full record

ArticleFrontiers in oncology2026

Fecal hemoglobin concentration as a risk stratification tool for advanced colorectal neoplasm in a community-based screening program.

Xiaocong Zhang, Kai Gu, Yangming Gong, Chunxiao Wu, Yi Pang, Mengyin Wu, Yan Shi

Abstract read
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Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Xiaocong ZhangDivision of Noncommunicable Diseases and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Kai GuDivision of Noncommunicable Diseases and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Yangming GongDivision of Noncommunicable Diseases and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Chunxiao WuDivision of Noncommunicable Diseases and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Yi PangDivision of Noncommunicable Diseases and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Mengyin WuDivision of Noncommunicable Diseases and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Yan ShiDivision of Noncommunicable Diseases and Injury, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Compared with traditional binary classification, the quantitative fecal immunochemical test (qFIT) provides detailed fecal hemoglobin (f-Hb) concentrations, which facilitate more refined risk stratification for advanced colorectal neoplasm; however, this approach remains underexplore. Methods: Based on the Shanghai colorectal cancer (CRC) screening program, 7,097 residents were enrolled. Participants who completed both qFIT and colonoscopy were included in the analysis. Odds ratios (ORs) and 95% confidence intervals (CIs) derived from logistic regression models were used to evaluate the association between f-Hb concentration and the risk of advanced neoplasm. Subgroup analyses by age and sex were conducted for further risk stratification. Results: The median f-Hb concentration was significantly higher in participants with advanced neoplasm (71 ng/mL; interquartile range[IQR]: 20-412 ng/mL) compared with those without neoplasm (19 ng/mL; IQR: 11-41.5 ng/mL) (P<0.001). The proportion of advanced neoplasm increased with rising f-Hb concentration. Logistic regression analysis revealed that, compared with participants with f-Hb <50 ng/mL, 2.91-fold, 3.92-fold, and 24.21-fold increased risks of advanced neoplasm were observed for those with f-Hb of 50-99 ng/mL, 100-799 ng/mL, and ≥800 ng/mL, respectively. According to sex, age, and f-Hb concentration, 16 categories were identified. Risk stratification was based on ORs as follows: reference, normal risk; 1 to <3, low risk; 3 to <10, moderate risk; and ≥10, high risk. Using this criterion, 674 (71.25%), 138 (14.59%), 103 (10.89%), and 31 (3.28%) participants were classified into the normal-, low-, moderate-, and high-risk groups, respectively. Conclusions: F-Hb concentration is predictive of the severity of colorectal neoplasm and may be used for risk stratification of advanced neoplasm.

Indexed as

advanced colorectal neoplasmcolorectal cancerfecal immunochemical testrisk stratificationscreening

Identifiers

PMID42245725
PMCPMC13229734

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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.