Evidence map›Paper›PMID 39779803›Full record

ArticleScientific reports2025

Blood metal levels predict digestive tract cancer risk using machine learning in a U.S. cohort.

Chenyuan Shi, Hanfeng Jiang, Fangzhou Zhao, Yigang Zhang, Haoming Chen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

  1. An Exploration of Machine Learning Methods in Human Biomonitoring.International journal of environmental research and public health · 2026
    Review
  2. Evidence for Genotype-Specific Optimal Blood Lead Levels for Cancer Risk:International journal of molecular sciences · 2026
    Article
  3. Article
  4. Article
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

5 authors.

Chenyuan Shi *Department of Emergency Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China.
Hanfeng Jiang *School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China.
Fangzhou Zhao *School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China.
Yigang ZhangDepartment of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China. zhangyg0021@163.com.
Haoming ChenSchool of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China. chenhaoming@njust.edu.cn.

Funding

The Young Scholars Fostering Fund of the First Affiliated Hospital of Nanjing Medical University 2023
6 · The paper itself

Abstract

backgroundEnvironmental metal exposure has been implicated in the development of digestive tract cancers, although the specific associations remain poorly defined. This study aimed to investigate the relationship between blood metal levels and the risk of digestive tract cancers among U.S. adults.

methodsData from the National Health and Nutrition Examination Survey (NHANES) 2011-2018, including 13,467 participants aged 20 years and older, were analyzed. Nine blood metals were measured. Multivariable logistic regression, restricted cubic spline models, and subgroup analyses were employed to assess the associations between metal levels and cancer risk. Additionally, a Random Forest (RF) model was used for cancer risk prediction.

resultsAmong the participants, 9 had esophagus cancer (EC), 11 had gastric cancer (GC), and 83 had colorectal cancer (CRC). Compared to healthy controls, EC patients exhibited significantly higher blood levels of potassium (K, 4.40 vs. 4.00 mmol/L), cadmium (Cd, 12.46 vs. 2.49 µg/L), and lead (Pb, 0.09 vs. 0.05 µg/L). GC patients had elevated Pb levels (0.08 vs. 0.05 µg/L), while CRC patients showed higher concentrations of Cd (3.11 vs. 2.49 µg/L) and Pb (0.06 vs. 0.04 µg/L). Logistic regression analysis revealed significant associations between higher K (odds ratio [OR] = 7.58, 95% CI: 3.48-16.48, P < 0.0001), Cd (OR = 1.06, 95% CI: 1.04-1.08, P < 0.0001), and Pb (OR = 7.60, 95% CI: 3.26-17.72, P < 0.0001) levels and EC risk. Pb was also significantly associated with GC (OR = 5.26, 95% CI: 2.11-13.10, P < 0.001). The RF model showed an accuracy of 76% in predicting cancer risk, with SHapley Additive exPlanations (SHAP) analysis highlighting Cd and iron (Fe) as key contributors.

conclusionsThe study reveals a positive association between certain blood metals and digestive tract cancer risk, suggesting that limiting exposure to these metals may serve as a potential preventive measure.

Indexed as

Machine LearningAdultAgedCadmiumCohort StudiesEnvironmental ExposureEsophageal NeoplasmsFemaleHumansLeadMaleMetalsMiddle AgedNutrition SurveysRisk FactorsStomach NeoplasmsCadmiumLeadMetalsBlood metalColorectal CancerEsophagus cancerGastric cancerMachine learningRandom Forest

Identifiers

PMID39779803
PMCPMC11711503

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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.