Evidence map›Paper›PMID 39593118›Full record

ArticleBreast cancer research : BCR2024

Plasma prolactin and postmenopausal breast cancer risk: a pooled analysis of four prospective cohort studies.

Jacob K Kresovich, Catherine Guranich, Serena Houghton, Jing Qian, Micheal E Jones, Maegan E Boutot, Mitch Dowsett, A Heather Eliassen, Montserrat Garcia-Closas, Peter Kraft and 11 more

Abstract read
In one paragraph

Article in Breast cancer research : BCR, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
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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.

Jacob K KresovichDepartment of Cancer Epidemiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, 33612, USA. Jacob.kresovich@moffitt.org.
Catherine GuranichDepartment of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, 01003, USA.
Serena HoughtonDepartment of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, 01003, USA.
Jing QianDepartment of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, 01003, USA.
Micheal E JonesDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP, UK.
Maegan E BoutotDepartment of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, 01003, USA.
Mitch DowsettRoyal Marsden Hospital, London, SW3 6JJ, UK.
A Heather EliassenDepartments of Nutrition and Epidemiology, Harvard TH Chan School of Public Health and Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Montserrat Garcia-ClosasDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP, UK.
Peter KraftDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, 20850, USA.
Aaron NormanDivision of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, 55905, USA.
Michael PollakDepartments of Oncology, Internal Medicine, and Pharmacology, McGill University, Montreal, QC, Canada.
Sabina RinaldiInternational Agency for Research on Cancer, (IARC/WHO), Lyon, France.
Bernard RosnerChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Minouk J SchoemakerDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP, UK.
Christopher ScottDivision of Clinical Trials and Statistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, 55905, USA.
Anthony J SwerdlowDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP, UK.
Roger L MilneCancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia.
Shelley S TworogerDepartment of Cancer Epidemiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, 33612, USA.
Celine M VachonDivision of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, 55905, USA.
Susan E HankinsonDepartment of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, 01003, USA.

Funding

Long Term Multidisciplinary Study of Cancer in Women: The Nurses Health StudyUM1CA186107 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI ELIASSEN, A. HEATHER, STAMPFER, MEIR · 2014 to 2023
$22.3M
Endogenous hormones and postmenopausal breast cancer: Etiologic insights and improving risk predictionR01CA207369 · NCI · UNIVERSITY OF MASSACHUSETTS AMHERST · PI HANKINSON, SUSAN E · 2017 to 2021
$4.5M
A Mayo Cohort Study of Mammographic Breast DensityR01CA097396 · NCI · MAYO CLINIC ROCHESTER · PI VACHON, CELINE M · 2003 to 2007
$3.1M
NCI NIH HHS R01 CA097396NCI NIH HHS R01 CA207369NCI NIH HHS UM1 CA186107NIH HHS R01 CA186107NIH HHS R01 CA207369NIH HHS R01 CA97396Wellcome Trust 209057World Health Organization 001
6 · The paper itself

Abstract

backgroundProlactin, a hormone produced by the pituitary gland, regulates breast development and may contribute to breast cancer etiology. However, most epidemiologic studies of prolactin and breast cancer have been restricted to single, often small, study samples with limited exploration of effect modification.

methodsThe Biomarkers in Breast Cancer Risk Prediction consortium includes 8,279 postmenopausal women sampled from four prospective cohort studies, of whom 3,441 were diagnosed with invasive breast cancer after enrollment. Prolactin concentrations were measured for all study participants on plasma samples collected when all women were postmenopausal and before any breast cancer diagnosis using ELISA assays. Pooled, unconditional logistic regression models, adjusted for confounders, estimated odd ratios (OR) for associations of prolactin and postmenopausal breast cancer risk overall and stratified by breast cancer risk factors.

resultsHigher plasma prolactin concentrations were positively associated with postmenopausal breast cancer risk (> 13.2 ng/mL vs. < 7.9 ng/mL, OR: 1.20, 95% CI: 1.06, 1.36; P-trend < 0.001). Although associations did not appear to vary by time since blood draw or most breast cancer risk factors, associations were primarily observed in current users of postmenopausal hormones at blood draw (> 13.2 ng/mL vs. < 7.9 ng/mL, current users, OR: 1.58, 95% CI: 1.27, 1.96, P-trend < 0.001; non-current users, OR: 1.08, 95% CI: 0.93, 1.27, P-trend = 0.11; P-heterogeneity = 0.06).

conclusionProlactin may be a risk factor for postmenopausal breast cancer, particularly in the context of postmenopausal hormone use. Investigations of prolactin interactions with other hormonal factors may further inform breast cancer etiology.

Indexed as

Breast NeoplasmsPostmenopauseProlactinAgedBiomarkers, TumorFemaleHumansMiddle AgedOdds RatioProspective StudiesRisk FactorsBiomarkers, TumorProlactinBreast cancerCohort studyConsortiumPostmenopausal breast cancerProlactin

Identifiers

PMID39593118
PMCPMC11590566

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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.