Evidence map›Paper›PMID 38687505›Full record

ArticleJAMA2024

Collaborative Modeling to Compare Different Breast Cancer Screening Strategies: A Decision Analysis for the US Preventive Services Task Force.

Amy Trentham-Dietz, Christina Hunter Chapman, Jinani Jayasekera, Kathryn P Lowry, Brandy M Heckman-Stoddard, John M Hampton, Jennifer L Caswell-Jin, Ronald E Gangnon, Ying Lu, Hui Huang and 25 more

Abstract readComparative Study
In one paragraph

Article in JAMA, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

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  11. Real-world data and evidence: pioneering frontiers in precision oncology.Journal of Zhejiang University. Science. B · 2025
    Review
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  17. A Scoping Review on Calibration Methods for Cancer Simulation Models.Medical decision making : an international journal of the Society for Medical Decision Making · 2025
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

35 authors.

Amy Trentham-DietzDepartment of Population Health Sciences and Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison.
Christina Hunter ChapmanDepartment of Radiation Oncology and Center for Innovations in Quality, Safety, and Effectiveness, Baylor College of Medicine, Houston, Texas.
Jinani JayasekeraHealth Equity and Decision Sciences (HEADS) Research Laboratory, Division of Intramural Research at the National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, Maryland.
Kathryn P LowryUniversity of Washington School of Medicine, Seattle.
Brandy M Heckman-StoddardDivision of Cancer Prevention, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
John M HamptonDepartment of Population Health Sciences and Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison.
Jennifer L Caswell-JinDepartment of Medicine, Stanford University School of Medicine, Stanford, California.
Ronald E GangnonDepartment of Population Health Sciences and Carbone Cancer Center, School of Medicine and Public Health, University of Wisconsin-Madison.
Ying LuStanford University, Stanford, California.
Hui HuangDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts.
Sarah SteinHarvard Pilgrim Health Care Institute, Boston, Massachusetts.
Liyang SunStanford University, Stanford, California.
Eugenio J Gil QuessepErasmus MC-University Medical Center, Rotterdam, the Netherlands.
Yuanliang YangUniversity of Texas MD Anderson Cancer Center, Houston.
Yifan LuDepartment of Industrial and Systems Engineering and Carbone Cancer Center, University of Wisconsin-Madison.
Juhee SongUniversity of Texas MD Anderson Cancer Center, Houston.
Diego F MuñozStanford University, Stanford, California.
Yisheng LiUniversity of Texas MD Anderson Cancer Center, Houston.
Allison W KurianDepartments of Medicine and Epidemiology and Population Health, Stanford University, Stanford, California.
Karla KerlikowskeDepartments of Medicine and Epidemiology and Biostatistics, University of California San Francisco.
Ellen S O'MearaKaiser Permanente Washington Health Research Institute, Seattle, Washington.
Brian L SpragueDepartment of Surgery, University of Vermont, Burlington.
Anna N A TostesonDartmouth Institute for Health Policy and Clinical Practice and Departments of Medicine and Community and Family Medicine, Dartmouth Geisel School of Medicine, Hanover, New Hampshire.
Eric J FeuerDivision of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Donald BerryUniversity of Texas MD Anderson Cancer Center, Houston.
Sylvia K PlevritisDepartments of Biomedical Data Science and Radiology, Stanford University, Stanford, California.
Xuelin HuangUniversity of Texas MD Anderson Cancer Center, Houston.
Harry J de KoningErasmus MC-University Medical Center, Rotterdam, the Netherlands.
Nicolien T van RavesteynErasmus MC-University Medical Center, Rotterdam, the Netherlands.
Sandra J LeeDepartment of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts.
Oguzhan AlagozDepartment of Industrial and Systems Engineering and Carbone Cancer Center, University of Wisconsin-Madison.
Clyde B SchechterAlbert Einstein College of Medicine, Bronx, New York.
Natasha K StoutHarvard Pilgrim Health Care Institute, Boston, Massachusetts.
Diana L MigliorettiKaiser Permanente Washington Health Research Institute, Seattle, Washington.
Jeanne S MandelblattDepartments of Oncology and Medicine, Georgetown University Medical Center, and Georgetown Lombardi Comprehensive Institute for Cancer and Aging Research at Georgetown University Lombardi Comprehensive Cancer Center, Washington, DC.

Funding

UW COMPREHENSIVE CANCER CENTER SUPPORTP30CA014520 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI AMY TRENTHAM-DIETZ · 1985 to 2026
$142.6M
Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Steven D Leach · 1985 to 2026
$91.3M
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
Comparative Modeling of Precision Breast Cancer Control Across the Translational Continuum - SupplementU01CA253911 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI ALAGOZ, OGUZHAN, DE KONING, HARRY J · 2020 to 2025
$10.6M
Health Equity and Decision SciencesZIAMD000022 · NIMHD · NATIONAL INSTITUTE ON MINORITY HEALTH AND HEALTH DISPARITIES · PI JAYASEKERA, JINANI · 2023 to 2025
$962k
NCI NIH HHS P01 CA154292NCI NIH HHS P30 CA014520NCI NIH HHS P30 CA023108NCI NIH HHS U01 CA253911
6 · The paper itself

Abstract

Importance: The effects of breast cancer incidence changes and advances in screening and treatment on outcomes of different screening strategies are not well known. Objective: To estimate outcomes of various mammography screening strategies. Design, Setting, and Population: Comparison of outcomes using 6 Cancer Intervention and Surveillance Modeling Network (CISNET) models and national data on breast cancer incidence, mammography performance, treatment effects, and other-cause mortality in US women without previous cancer diagnoses. Exposures: Thirty-six screening strategies with varying start ages (40, 45, 50 years) and stop ages (74, 79 years) with digital mammography or digital breast tomosynthesis (DBT) annually, biennially, or a combination of intervals. Strategies were evaluated for all women and for Black women, assuming 100% screening adherence and "real-world" treatment. Main Outcomes and Measures: Estimated lifetime benefits (breast cancer deaths averted, percent reduction in breast cancer mortality, life-years gained), harms (false-positive recalls, benign biopsies, overdiagnosis), and number of mammograms per 1000 women. Results: Biennial screening with DBT starting at age 40, 45, or 50 years until age 74 years averted a median of 8.2, 7.5, or 6.7 breast cancer deaths per 1000 women screened, respectively, vs no screening. Biennial DBT screening at age 40 to 74 years (vs no screening) was associated with a 30.0% breast cancer mortality reduction, 1376 false-positive recalls, and 14 overdiagnosed cases per 1000 women screened. Digital mammography screening benefits were similar to those for DBT but had more false-positive recalls. Annual screening increased benefits but resulted in more false-positive recalls and overdiagnosed cases. Benefit-to-harm ratios of continuing screening until age 79 years were similar or superior to stopping at age 74. In all strategies, women with higher-than-average breast cancer risk, higher breast density, and lower comorbidity level experienced greater screening benefits than other groups. Annual screening of Black women from age 40 to 49 years with biennial screening thereafter reduced breast cancer mortality disparities while maintaining similar benefit-to-harm trade-offs as for all women. Conclusions: This modeling analysis suggests that biennial mammography screening starting at age 40 years reduces breast cancer mortality and increases life-years gained per mammogram. More intensive screening for women with greater risk of breast cancer diagnosis or death can maintain similar benefit-to-harm trade-offs and reduce mortality disparities.

Indexed as

Breast NeoplasmsEarly Detection of CancerMammographyAdultAgedAge FactorsDecision Support TechniquesFalse Positive ReactionsFemaleHumansIncidenceMass ScreeningMedical OveruseMiddle AgedModels, StatisticalPractice Guidelines as Topic

Identifiers

PMID38687505
PMCPMC11995725

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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.