Evidence map›Paper›PMID 36650550›Full record

ArticleBreast cancer research : BCR2023

A prospective case-cohort analysis of plasma metabolites and breast cancer risk.

Victoria L Stevens, Brian D Carter, Eric J Jacobs, Marjorie L McCullough, Lauren R Teras, Ying Wang

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Breast cancer research : BCR, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.5field-weighted citation impact, top 11% 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

17 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Review
  3. Observational
  4. Review
  5. Article
  6. Observational
  7. Article
  8. Article
  9. Article
  10. Physical activity, metabolites, and breast cancer associations.Journal of the National Cancer Institute · 2025
    Article
  11. Article
  12. Plasma metabolomics profiles and breast cancer risk.Breast cancer research : BCR · 2024
    Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Victoria L StevensDepartment of Population Sciences, American Cancer Society, 3380 Chastain Meadows Pkwy NW Suite 200, Kennesaw, GA, 30144, USA.
Brian D CarterDepartment of Population Sciences, American Cancer Society, 3380 Chastain Meadows Pkwy NW Suite 200, Kennesaw, GA, 30144, USA.
Eric J JacobsDepartment of Population Sciences, American Cancer Society, 3380 Chastain Meadows Pkwy NW Suite 200, Kennesaw, GA, 30144, USA.
Marjorie L McCulloughDepartment of Population Sciences, American Cancer Society, 3380 Chastain Meadows Pkwy NW Suite 200, Kennesaw, GA, 30144, USA.
Lauren R TerasDepartment of Population Sciences, American Cancer Society, 3380 Chastain Meadows Pkwy NW Suite 200, Kennesaw, GA, 30144, USA.
Ying WangDepartment of Population Sciences, American Cancer Society, 3380 Chastain Meadows Pkwy NW Suite 200, Kennesaw, GA, 30144, USA. Ying.wang@cancer.org.
American Cancer Society · USScientific Systems (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast cancer incidence rates have not declined despite an improvement in risk prediction and the identification of modifiable risk factors, suggesting the need to identify novel risk factors and etiological pathways involved in this cancer. Metabolomics has emerged as a promising tool to find circulating metabolites associated with breast cancer risk.

methodsUntargeted metabolomic analysis was done on prediagnostic plasma samples from a case-cohort study of 1695 incident breast cancer cases and a 1983 women subcohort drawn from Cancer Prevention Study 3. The associations of 868 named metabolites (per one standard deviation increase) with breast cancer were determined using Prentice-weighted Cox proportional hazards regression modeling.

resultsA total of 11 metabolites were associated with breast cancer at false discovery rate (FDR) < 0.05 with the majority having inverse association [ranging from RR = 0.85 (95% CI 0.80-0.92) to RR = 0.88 (95% CI 0.82-0.94)] and one having a positive association [RR = 1.14 (95% CI 1.06-1.23)]. An additional 50 metabolites were associated at FDR < 0.20 with inverse associations ranging from RR = 0.88 (95% CI 0.81-0.94) to RR = 0.91 (95% CI 0.85-0.98) and positive associations ranging from RR = 1.13 (95% CI 1.05-1.22) to RR = 1.11 (95% CI 1.02-1.20). Several of these associations validated the findings of previous metabolomic studies. These included findings that several progestogen and androgen steroids were associated with increased risk of breast cancer in postmenopausal women and four phospholipids, and the amino acids glutamine and asparagine were associated with decreased risk of this cancer in pre- and postmenopausal women. Several novel associations were also identified, including a positive association for syringol sulfate, a biomarker for smoked meat, and 3-methylcatechol sulfate and 3-hydroxypyridine glucuronide, which are metabolites of xenobiotics used for the production of pesticides and other products.

conclusionsOur study validated previous metabolite findings and identified novel metabolites associated with breast cancer risk, demonstrating the utility of large metabolomic studies to provide new leads for understanding breast cancer etiology. Our novel findings suggest that consumption of smoked meats and exposure to catechol and pyridine should be investigated as potential risk factors for breast cancer.

Indexed as

Breast NeoplasmsCatecholsCohort StudiesFemaleHumansProspective StudiesRisk FactorsXenobiotics3-methylcatechol sulfateCatecholsXenobioticsBreast cancerMetabolitesMetabolomicsProspective study

Identifiers

PMID36650550
PMCPMC9847033
OpenAlexW4316814313

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.