Evidence map›Paper›PMID 29318276›Full record

ArticleJAMA2018

Association of Screening and Treatment With Breast Cancer Mortality by Molecular Subtype in US Women, 2000-2012.

Sylvia K Plevritis, Diego Munoz, Allison W Kurian, Natasha K Stout, Oguzhan Alagoz, Aimee M Near, Sandra J Lee, Jeroen J van den Broek, Xuelin Huang, Clyde B Schechter and 13 more

Erratum issuedOpen access · bronzeAbstract read
In one paragraph

Article in JAMA, 2018. 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 159 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
159citing papers in PubMed, 11 pooled it
13.8field-weighted citation impact, top 1% 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

159 citing papers in PubMed, 11 syntheses or guidelines pooled it, 296 citations in OpenAlex.

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  7. Experience of women with breast cancer undergoing chemotherapy: a systematic review of qualitative research.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2021
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  11. Systematic Review of the Cost Effectiveness of Breast Cancer Prevention, Screening, and Treatment Interventions.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2020
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99 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

23 authors at 12 institutions in 2 countries.

Sylvia K PlevritisDepartments of Radiology and Biomedical Data Science, School of Medicine, Stanford University, Stanford, California.
Diego MunozDepartments of Radiology and Biomedical Data Science, School of Medicine, Stanford University, Stanford, California.
Allison W KurianDepartments of Medicine and Health Research and Policy, School of Medicine, Stanford University, Stanford, California.
Natasha K StoutDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts.
Oguzhan AlagozDepartment of Industrial and Systems Engineering, University of Wisconsin-Madison.
Aimee M NearDepartment of Oncology, Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC.
Sandra J LeeDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts.
Jeroen J van den BroekDepartment of Public Health, Erasmus MC University Medical Center, Rotterdam, the Netherlands.
Xuelin HuangDepartment of Biostatistics, University of Texas MD Anderson Cancer Center, Houston.
Clyde B SchechterDepartments of Family and Social Medicine and Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York.
Brian L SpragueDepartment of Surgery, College of Medicine, University of Vermont, Burlington.
Juhee SongDepartment of Biostatistics, University of Texas MD Anderson Cancer Center, Houston.
Harry J de KoningDepartment of Public Health, Erasmus MC University Medical Center, Rotterdam, the Netherlands.
Amy Trentham-DietzCarbone Cancer Center, University of Wisconsin-Madison.
Nicolien T van RavesteynDepartment of Public Health, Erasmus MC University Medical Center, Rotterdam, the Netherlands.
Ronald GangnonCarbone Cancer Center, University of Wisconsin-Madison.
Young ChandlerDepartment of Oncology, Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC.
Yisheng LiDepartment of Biostatistics, University of Texas MD Anderson Cancer Center, Houston.
Cong XuDepartments of Radiology and Biomedical Data Science, School of Medicine, Stanford University, Stanford, California.
Mehmet Ali ErgunDepartment of Industrial and Systems Engineering, University of Wisconsin-Madison.
Hui HuangDepartment of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts.
Donald A BerryDepartment of Biostatistics, University of Texas MD Anderson Cancer Center, Houston.
Jeanne S MandelblattDepartment of Oncology, Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC.
Stanford University · USThe University of Texas MD Anderson Cancer Center · USErasmus MC · NLUniversity of Wisconsin–Madison · USGeorgetown University Medical Center · USAlbert Einstein College of Medicine · USDana-Farber Cancer Institute · USGeorgetown University · USHarvard Pilgrim Health Care · USHarvard University · USUniversity of Vermont · USUniversity of Wisconsin Carbone Cancer Center · US

Funding

Risk-based Imaging Strategies to Improve Breast Cancer Surveillance OutcomesP01CA154292 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Diana L Miglioretti · 2011 to 2026
$52.9M
Center for Clinical and Translational Sciences (CCTS)UL1TR000371 · NCATS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI MCPHERSON, DAVID D · 2012 to 2016
$13.4M
Comparative Modeling: Informing Breast Cancer Control Practice and PolicyU01CA199218 · NCI · GEORGETOWN UNIVERSITY · PI BERRY, DONALD A, DE KONING, HARRY J · 2015 to 2019
$9.0M
Comparative Modeling: Informing Breast Cancer Control Practice & PolicyU01CA152958 · NCI · GEORGETOWN UNIVERSITY · PI BERRY, DONALD A, DE KONING, HARRY J · 2010 to 2015
$7.6M
Vermont Screening Process Documentation UnitU54CA163303 · NCI · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI SPRAGUE, BRIAN L · 2011 to 2017
$6.4M
NCATS NIH HHS UL1 TR000371NCI NIH HHS P01 CA154292NCI NIH HHS U01 CA152958NCI NIH HHS U01 CA199218NCI NIH HHS U54 CA163303
6 · The paper itself

Abstract

Importance: Given recent advances in screening mammography and adjuvant therapy (treatment), quantifying their separate and combined effects on US breast cancer mortality reductions by molecular subtype could guide future decisions to reduce disease burden. Objective: To evaluate the contributions associated with screening and treatment to breast cancer mortality reductions by molecular subtype based on estrogen-receptor (ER) and human epidermal growth factor receptor 2 (ERBB2, formerly HER2 or HER2/neu). Design, Setting, and Participants: Six Cancer Intervention and Surveillance Network (CISNET) models simulated US breast cancer mortality from 2000 to 2012 using national data on plain-film and digital mammography patterns and performance, dissemination and efficacy of ER/ERBB2-specific treatment, and competing mortality. Multiple US birth cohorts were simulated. Exposures: Screening mammography and treatment. Main Outcomes and Measures: The models compared age-adjusted, overall, and ER/ERBB2-specific breast cancer mortality rates from 2000 to 2012 for women aged 30 to 79 years relative to the estimated mortality rate in the absence of screening and treatment (baseline rate); mortality reductions were apportioned to screening and treatment. Results: In 2000, the estimated reduction in overall breast cancer mortality rate was 37% (model range, 27%-42%) relative to the estimated baseline rate in 2000 of 64 deaths (model range, 56-73) per 100 000 women: 44% (model range, 35%-60%) of this reduction was associated with screening and 56% (model range, 40%-65%) with treatment. In 2012, the estimated reduction in overall breast cancer mortality rate was 49% (model range, 39%-58%) relative to the estimated baseline rate in 2012 of 63 deaths (model range, 54-73) per 100 000 women: 37% (model range, 26%-51%) of this reduction was associated with screening and 63% (model range, 49%-74%) with treatment. Of the 63% associated with treatment, 31% (model range, 22%-37%) was associated with chemotherapy, 27% (model range, 18%-36%) with hormone therapy, and 4% (model range, 1%-6%) with trastuzumab. The estimated relative contributions associated with screening vs treatment varied by molecular subtype: for ER+/ERBB2-, 36% (model range, 24%-50%) vs 64% (model range, 50%-76%); for ER+/ERBB2+, 31% (model range, 23%-41%) vs 69% (model range, 59%-77%); for ER-/ERBB2+, 40% (model range, 34%-47%) vs 60% (model range, 53%-66%); and for ER-/ERBB2-, 48% (model range, 38%-57%) vs 52% (model range, 44%-62%). Conclusions and Relevance: In this simulation modeling study that projected trends in breast cancer mortality rates among US women, decreases in overall breast cancer mortality from 2000 to 2012 were associated with advances in screening and in adjuvant therapy, although the associations varied by breast cancer molecular subtype.

Indexed as

Early Detection of CancerMammographyModels, StatisticalBreast NeoplasmsErb-b2 Receptor Tyrosine KinasesFemaleHumansMortalityReceptors, EstrogenUnited StatesERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesReceptors, Estrogen

Identifiers

PMID29318276
PMCPMC5833658
OpenAlexW2783801120

What OpenQuestion holds

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Registered trials

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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.