Evidence map›Paper›PMID 30509329›Full record

ArticleBreast cancer research : BCR2018

Risk prediction for estrogen receptor-specific breast cancers in two large prospective cohorts.

Kuanrong Li, Garnet Anderson, Vivian Viallon, Patrick Arveux, Marina Kvaskoff, Agnès Fournier, Vittorio Krogh, Rosario Tumino, Maria-Jose Sánchez, Eva Ardanaz and 25 more

Open access · goldAbstract readValidation Study
In one paragraph

Article in Breast cancer research : BCR, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 3 pooled it
1.4field-weighted citation impact, top 15% 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

21 citing papers in PubMed, 3 syntheses or guidelines pooled it, 40 citations in OpenAlex.

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  14. Performance of polygenic risk scores for cancer prediction in a racially diverse academic biobank.Genetics in medicine : official journal of the American College of Medical Genetics · 2022
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  17. A Validated Risk Prediction Model for Breast Cancer in US Black Women.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2021
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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

35 authors at 20 institutions in 13 countries.

Kuanrong LiNutritional Methodology and Biostatistics Group, Nutrition and Metabolism Section, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon Cedex 08, France.
Garnet AndersonPublic Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, USA.
Vivian ViallonNutritional Methodology and Biostatistics Group, Nutrition and Metabolism Section, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon Cedex 08, France.
Patrick ArveuxBreast and Gynaecologic Cancer Registry of Côte d'Or, Georges-François Leclerc Comprehensive Cancer Care Centre, Dijon, France.
Marina KvaskoffCESP, INSERM U1018, Univ. Paris-Sud, UVSQ, Université Paris-Saclay, Villejuif, France.
Agnès FournierCESP, INSERM U1018, Univ. Paris-Sud, UVSQ, Université Paris-Saclay, Villejuif, France.
Vittorio KroghEpidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Rosario TuminoCancer Registry and Histopathology Department, "Civic-M. P.Arezzo" Hospital, ASP, Ragusa, Italy.
Maria-Jose SánchezEscuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria ibs. GRANADA, Hospitales Universitarios de Granada/ Universidad de Granada, Granada, Spain.
Eva ArdanazCIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
María-Dolores ChirlaqueCIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Antonio AgudoUnit of Nutrition and Cancer. Cancer Epidemiology Research Program, Catalan Institute of Oncology-IDIBELL. L'Hospitalet de Llobregat, Barcelona, Spain.
David C MullerDepartment of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London, UK.
Todd SmithDepartment of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London, UK.
Ioanna TzoulakiDepartment of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London, UK.
Timothy J KeyCancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Bas Bueno-de-MesquitaDepartment of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London, UK.
Antonia TrichopoulouHellenic Health Foundation, Athens, Greece.
Christina BamiaHellenic Health Foundation, Athens, Greece.
Philippos OrfanosHellenic Health Foundation, Athens, Greece.
Rudolf KaaksDivision of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany.
Anika HüsingDivision of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany.
Renée T FortnerDivision of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany.
Anne Zeleniuch-JacquotteDepartment of Population Health, New York University School of Medicine, New York, USA.
Malin SundDepartment of Surgical and Perioperative Sciences, Umeå University, Umeå, Sweden.
Christina C DahmSection for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark.
Kim OvervadSection for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark.
Dagfinn AuneDepartment of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London, UK.
Elisabete WeiderpassDepartment of Research, Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo, Norway.
Isabelle RomieuNutritional Epidemiology Group, Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France.
Elio RiboliDepartment of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London, UK.
Marc J GunterNutritional Epidemiology Group, Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France.
Laure DossusBiomarkers Group, Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France.
Ross PrenticePublic Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, USA.
Pietro FerrariNutritional Methodology and Biostatistics Group, Nutrition and Metabolism Section, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372, Lyon Cedex 08, France. ferrarip@iarc.fr.
Centre International de Recherche sur le Cancer · FRImperial College London · GBGerman Cancer Research Center · DEHellenic Health Foundation · GRUniversité Paris-Sud · FRAalborg University Hospital · DKAarhus University · DKAndalusian School of Public Health · ESAzienda Usl 8 Arezzo · ITCentre de recherche en Epidémiologie et Santé des Populations · FRCentro de Investigación Biomédica en Red de Epidemiología y Salud Pública · ESFondazione IRCCS Istituto Nazionale dei Tumori · ITFred Hutch Cancer Center · USHeidelberg University · DEInstitut d'Investigació Biomédica de Bellvitge · ESKarolinska Institutet · SENational and Kapodistrian University of Athens · GRNavarre Institute of Health Research · ESNew York University · USOslo Nye Høyskole · NO

Funding

Cancer Research UK 14136Cancer Research UK 16491Cancer Research UK C570/A16491Medical Research Council 1000143Medical Research Council C8221/A19170Medical Research Council MR/M012190/1NHLBI NIH HHS HHSN268201600001CNHLBI NIH HHS HHSN268201600002CNHLBI NIH HHS HHSN268201600003CNHLBI NIH HHS HHSN268201600004CNHLBI NIH HHS HHSN268201600018CWorld Health Organization 001
6 · The paper itself

Abstract

backgroundFew published breast cancer (BC) risk prediction models consider the heterogeneity of predictor variables between estrogen-receptor positive (ER+) and negative (ER-) tumors. Using data from two large cohorts, we examined whether modeling this heterogeneity could improve prediction.

methodsWe built two models, for ER+ (Model

resultsParity, number of full-term pregnancies, age at first full-term pregnancy and body height were only associated with ER+ tumors. Menopausal status, age at menarche and at menopause, hormone replacement therapy, postmenopausal body mass index, and alcohol intake were homogeneously associated with ER+ and ER- tumors. Internal validation yielded a C-statistic of 0.64 for Model

conclusionsModeling heterogeneous epidemiological risk factors might yield little improvement in BC risk prediction. Nevertheless, a model specifically predictive of ER+ tumor risk could be more applicable than an omnibus model in risk assessment for chemoprevention.

Indexed as

Models, BiologicalAntineoplastic AgentsBreast NeoplasmsFemaleFollow-Up StudiesHumansIncidenceMiddle AgedPrognosisProspective StudiesReceptors, EstrogenRisk AssessmentRisk FactorsAntineoplastic AgentsReceptors, EstrogenBreast cancerEPICEstrogen receptorProspective cohortRisk predictionWHI

Identifiers

PMID30509329
PMCPMC6276150
OpenAlexW2903281976

What OpenQuestion holds

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LicenceCC BY
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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.