Evidence map›Paper›PMID 39378119›Full record

ArticleInternational journal of cancer2025

Perturbations in the blood metabolome up to a decade before prostate cancer diagnosis in 4387 matched case-control sets from the European Prospective Investigation into Cancer and Nutrition.

Zoe S Grenville, Urwah Noor, Sabina Rinaldi, Marc J Gunter, Pietro Ferrari, Claudia Agnoli, Pilar Amiano, Alberto Catalano, María Dolores Chirlaque, Sofia Christakoudi and 18 more

Abstract read
In one paragraph

Article in International journal of cancer, 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

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

4 citing papers in PubMed.

  1. Review
  2. Review
  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

28 authors.

Zoe S GrenvilleCancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, UK.ORCID 0000-0002-8185-5929
Urwah NoorCancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, UK.
Sabina RinaldiNutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France.
Marc J GunterNutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France.
Pietro FerrariNutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France.
Claudia AgnoliEpidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumouri, Milan, Italy.
Pilar AmianoCIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain.
Alberto CatalanoCentre for Biostatistics, Epidemiology, and Public Health, Department of Clinical and Biological Sciences, University of Turin, Orbassano, Italy.ORCID 0000-0003-2597-2060
María Dolores ChirlaqueCIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain.
Sofia ChristakoudiDepartment of Epidemiology and Biostatistics, White City Campus, Imperial College, London, UK.ORCID 0000-0001-9219-4436
Marcela GuevaraInstituto de Salud Pública y Laboral de Navarra, Pamplona, Spain.
Matthias JohanssonNutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France.
Rudolf KaaksDepartment of Cancer Epidemiology, German Cancer research Center (DKFZ), Heidelberg, Germany.
Verena KatzkeDepartment of Cancer Epidemiology, German Cancer research Center (DKFZ), Heidelberg, Germany.
Giovanna MasalaClinical Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy.
Anja OlsenThe Danish Cancer Institute, Copenhagen, Denmark.
Keren PapierCancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, UK.
Maria-Jose SánchezCentro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Matthias B SchulzeDepartment of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany.
Anne TjønnelandThe Danish Cancer Institute, Copenhagen, Denmark.
Tammy Y N TongCancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, UK.
Rosario TuminoHyblean Association for Epidemiology Research, AIRE ONLUS, Ragusa, Italy.
Elisabete WeiderpassInternational Agency for Research on Cancer, World Health Organization, Lyon, France.ORCID 0000-0003-2237-0128
Raul Zamora-RosUnit of Nutrition and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain.ORCID 0000-0002-6236-6804
Timothy J KeyCancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, UK.
Karl Smith-ByrneCancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, UK.
Julie A SchmidtCancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, UK.ORCID 0000-0002-7733-8750
Ruth C TravisCancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, UK.

Funding

Cancer Research UK 29017Cancer Research UK C8221/A29017Cancer Research UK C8221/A30904World Health Organization 001
6 · The paper itself

Abstract

Measuring pre-diagnostic blood metabolites may help identify novel risk factors for prostate cancer. Using data from 4387 matched case-control pairs from the European Prospective Investigation into Cancer and Nutrition (EPIC) study, we investigated the associations of 148 individual metabolites and three previously defined metabolite patterns with prostate cancer risk. Metabolites were measured by liquid chromatography-mass spectrometry. Multivariable-adjusted conditional logistic regression was used to estimate the odds ratio per standard deviation increase in log metabolite concentration and metabolite patterns (OR1SD) for prostate cancer overall, and for advanced, high-grade, aggressive. We corrected for multiple testing using the Benjamini-Hochberg method. Overall, there were no associations between specific metabolites or metabolite patterns and overall, aggressive, or high-grade prostate cancer that passed the multiple testing threshold (padj <0.05). Six phosphatidylcholines (PCs) were inversely associated with advanced prostate cancer diagnosed at or within 10 years of blood collection. metabolite patterns 1 (64 PCs and three hydroxysphingomyelins) and 2 (two acylcarnitines, glutamate, ornithine, and taurine) were also inversely associated with advanced prostate cancer; when stratified by follow-up time, these associations were observed for diagnoses at or within 10 years of recruitment (OR

Indexed as

MetabolomeProstatic NeoplasmsAgedBiomarkers, TumorCarnitineCase-Control StudiesEuropeHumansMaleMetabolomicsMiddle AgedPhosphatidylcholinesProspective StudiesRisk FactorsacylcarnitineBiomarkers, TumorCarnitinePhosphatidylcholinescancer biomarkersEuropean prospective investigation into cancer and nutrition (EPIC)metabolomicsprospective cohortprostate cancer

Identifiers

PMID39378119
PMCPMC11701393

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.