Evidence map›Paper›PMID 31539079›Full record

ArticleJAMA network open2019

Association of Untargeted Urinary Metabolomics and Lung Cancer Risk Among Never-Smoking Women in China.

Wei Jie Seow, Xiao-Ou Shu, Jeremy K Nicholson, Elaine Holmes, Douglas I Walker, Wei Hu, Qiuyin Cai, Yu-Tang Gao, Yong-Bing Xiang, Steven C Moore and 11 more

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
2.1field-weighted citation impact, top 12% of its field
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

30 citing papers in PubMed, 46 citations in OpenAlex.

  1. Trial
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  6. [Applications and Advances of Metabolomics in Lung Cancer Research].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2025
    Review
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  15. Characteristics of Cancer Epidemiology Studies That Employ Metabolomics: A Scoping Review.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023
    Article
  16. Review
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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

21 authors at 8 institutions in 5 countries.

Wei Jie SeowSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
Xiao-Ou ShuDivision of Epidemiology, Department of Medicine, Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center, Nashville, Tennessee.
Jeremy K NicholsonBiomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council-National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom.
Elaine HolmesBiomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council-National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom.
Douglas I WalkerDepartment of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York.
Wei HuDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland.
Qiuyin CaiDivision of Epidemiology, Department of Medicine, Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center, Nashville, Tennessee.
Yu-Tang GaoDepartment of Epidemiology, Shanghai Cancer Institute, Shanghai, China.
Yong-Bing XiangDepartment of Epidemiology, Shanghai Cancer Institute, Shanghai, China.
Steven C MooreDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland.
Bryan A BassigDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland.
Jason Y Y WongDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland.
Jinming ZhangDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland.
Bu-Tian JiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland.
Claire L BoulangéBiomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council-National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom.
Manuja KaluarachchiBiomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council-National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom.
Anisha WijeyesekeraBiomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council-National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom.
Wei ZhengDivision of Epidemiology, Department of Medicine, Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center, Nashville, Tennessee.
Paul ElliottBiomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council-National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom.
Nathaniel RothmanDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland.
Qing LanDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland.
National Cancer Institute · USNational Institute for Health Research · GBNational Institutes of Health · USVanderbilt University Medical Center · USMedical Research Council · GBShanghai Cancer Institute · CNIcahn School of Medicine at Mount Sinai · USImperial College London · GB

Funding

Shanghai Womens Health StudyUM1CA182910 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ZHENG, WEI · 2014 to 2018
$5.9M
Medical Research Council MR/S019669/1NCI NIH HHS UM1 CA182910
6 · The paper itself

Abstract

Importance: Chinese women have the highest rate of lung cancer among female never-smokers in the world, and the etiology is poorly understood. Objective: To assess the association between metabolomics and lung cancer risk among never-smoking women. Design, Setting, and Participants: This nested case-control study included 275 never-smoking female patients with lung cancer and 289 never-smoking cancer-free control participants from the prospective Shanghai Women's Health Study recruited from December 28, 1996, to May 23, 2000. Validated food frequency questionnaires were used for the collection of dietary information. Metabolomic analysis was conducted from November 13, 2015, to January 6, 2016. Data analysis was conducted from January 6, 2016, to November 29, 2018. Exposures: Untargeted ultra-high-performance liquid chromatography-tandem mass spectrometry and nuclear magnetic resonance metabolomic profiles were characterized using prediagnosis urine samples. A total of 39 416 metabolites were measured. Main Outcomes and Measures: Incident lung cancer. Results: Among the 564 women, those who developed lung cancer (275 participants; median [interquartile range] age, 61.0 [52-65] years) and those who did not develop lung cancer (289 participants; median [interquartile range] age, 62.0 [53-66] years) at follow-up (median [interquartile range] follow-up, 10.9 [9.0-11.7] years) were similar in terms of their secondhand smoke exposure, history of respiratory diseases, and body mass index. A peak metabolite, identified as 5-methyl-2-furoic acid, was significantly associated with lower lung cancer risk (odds ratio, 0.57 [95% CI, 0.46-0.72]; P < .001; false discovery rate = 0.039). Furthermore, this peak was weakly correlated with self-reported dietary soy intake (ρ = 0.21; P < .001). Increasing tertiles of this metabolite were associated with lower lung cancer risk (in comparison with first tertile, odds ratio for second tertile, 0.52 [95% CI, 0.34-0.80]; and odds ratio for third tertile, 0.46 [95% CI, 0.30-0.70]), and the association was consistent across different histological subtypes and follow-up times. Additionally, metabolic pathway analysis found several systemic biological alterations that were associated with lung cancer risk, including 1-carbon metabolism, nucleotide metabolism, oxidative stress, and inflammation. Conclusions and Relevance: This prospective study of the untargeted urinary metabolome and lung cancer among never-smoking women in China provides support for the hypothesis that soy-based metabolites are associated with lower lung cancer risk in never-smoking women and suggests that biological processes linked to air pollution may be associated with higher lung cancer risk in this population.

Indexed as

MetabolomicsAir Pollution, IndoorCase-Control StudiesChinaEnvironmental ExposureFemaleHumansInflammationLung NeoplasmsMiddle AgedNutritional Physiological PhenomenaOdds RatioOxidative StressProspective StudiesSoybean ProteinsSoybean Proteins

Identifiers

PMID31539079
PMCPMC6755532
OpenAlexW2973680343

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.