Evidence map›Paper›PMID 37205649›Full record

ArticlePloS one2023

A complex systems model of breast cancer etiology: The Paradigm II Model.

Robert A Hiatt, Lee Worden, David Rehkopf, Natalie Engmann, Melissa Troester, John S Witte, Kaya Balke, Christian Jackson, Janice Barlow, Suzanne E Fenton and 9 more

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Making evidence go further: Advancing synergy between agent-based modeling and randomized control trials.Proceedings of the National Academy of Sciences of the United States of America · 2024
    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

19 authors.

Robert A HiattDepartment of Epidemiology and Biostatistics, School of Medicine, University of California San Francisco, San Francisco, California, United States of America.ORCID 0000-0001-7174-8436
Lee WordenFrancis I. Proctor Foundation for Research in Ophthalmology, University of California San Francisco, San Francisco, California, United States of America.ORCID 0000-0001-9799-0183
David RehkopfDepartment of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California, United States of America.
Natalie EngmannGenentech, Inc. South San Francisco, San Francisco, California, United States of America.
Melissa TroesterDepartment of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
John S WitteDepartment of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California, United States of America.
Kaya BalkeHelen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California, United States of America.
Christian JacksonDepartment of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California, United States of America.ORCID 0000-0003-2039-3051
Janice BarlowZero Breast Cancer (retired), San Rafael, California, United States of America.
Suzanne E FentonDivision of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, North Carolina, United States of America.
Sarah GehlertSuzanne Dworak-Peck School, University of Southern California, Los Angeles, United States of America.
Ross A HammondBrown School, Washington University, St Louis, Missouri, United States of America.
George KaplanUniversity of Michigan (retired), Ann Arbor, Michigan, United States of America.
John KornakDepartment of Epidemiology and Biostatistics, School of Medicine, University of California San Francisco, San Francisco, California, United States of America.
Krisida NishiokaSchool of Law, University of California, Berkeley, Berkeley, California, United States of America.
Thomas McKoneSchool of Public Health, University of California, Berkeley, (Emeritus), Berkeley, California, United States of America.
Martyn T SmithDivision of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, California, United States of America.
Leonardo TrasandeDepartment of Pediatrics, NYU Grossman School of Medicine, New York City, New York, United States of America.
Travis C PorcoDepartment of Epidemiology and Biostatistics, School of Medicine, University of California San Francisco, San Francisco, California, United States of America.

Funding

UNC-CH CENTER FOR ENVIRONMENTAL HEALTH &SUSCEPTIBILITYP30ES010126 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Stephanie Engel · 2001 to 2026
$36.3M
Translational Research Support CoreP30ES025128 · NIEHS · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI Sue Fenton · 2015 to 2026
$18.3M
NIEHS NIH HHS P30 ES010126NIEHS NIH HHS P30 ES025128
6 · The paper itself

Abstract

backgroundComplex systems models of breast cancer have previously focused on prediction of prognosis and clinical events for individual women. There is a need for understanding breast cancer at the population level for public health decision-making, for identifying gaps in epidemiologic knowledge and for the education of the public as to the complexity of this most common of cancers. METHODS AND

findingsWe developed an agent-based model of breast cancer for the women of the state of California using data from the U.S. Census, the California Health Interview Survey, the California Cancer Registry, the National Health and Nutrition Examination Survey and the literature. The model was implemented in the Julia programming language and R computing environment. The Paradigm II model development followed a transdisciplinary process with expertise from multiple relevant disciplinary experts from genetics to epidemiology and sociology with the goal of exploring both upstream determinants at the population level and pathophysiologic etiologic factors at the biologic level. The resulting model reproduces in a reasonable manner the overall age-specific incidence curve for the years 2008-2012 and incidence and relative risks due to specific risk factors such as BRCA1, polygenic risk, alcohol consumption, hormone therapy, breastfeeding, oral contraceptive use and scenarios for environmental toxin exposures.

conclusionsThe Paradigm II model illustrates the role of multiple etiologic factors in breast cancer from domains of biology, behavior and the environment. The value of the model is in providing a virtual laboratory to evaluate a wide range of potential interventions into the social, environmental and behavioral determinants of breast cancer at the population level.

Indexed as

Breast NeoplasmsAlcohol DrinkingFemaleHumansIncidenceNutrition SurveysRisk Factors

Identifiers

PMID37205649
PMCPMC10198497

What OpenQuestion holds

Textmetadata
LicenceCC0
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.