Evidence map›Paper›PMID 38227031›Full record

ArticleJAMA2024

Analysis of Breast Cancer Mortality in the US-1975 to 2019.

Jennifer L Caswell-Jin, Liyang P Sun, Diego Munoz, Ying Lu, Yisheng Li, Hui Huang, John M Hampton, Juhee Song, Jinani Jayasekera, Clyde Schechter and 9 more

Open access · greenAbstract read
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 161 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
161citing papers in PubMed, 4 pooled it
69.6field-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

161 citing papers in PubMed, 4 syntheses or guidelines pooled it, 244 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Trial
  6. Article
  7. Cancer Among Asian Americans and Pacific Islanders, 1999-2020.Journal of racial and ethnic health disparities · 2026
    Article
  8. Observational
  9. Article
  10. Article
  11. Mapping the landscape of Chinese patent medicines in breast cancer: a multi-database bibliometric analysis (1991-2025).Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Article
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  14. Review
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101 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

19 authors at 9 institutions in 1 country.

Jennifer L Caswell-JinDepartment of Medicine, Stanford University School of Medicine, Stanford, California.
Liyang P SunDepartment of Biomedical Data Science, Stanford University School of Medicine, Stanford, California.
Diego MunozDepartment of Biomedical Data Science, Stanford University School of Medicine, Stanford, California.
Ying LuDepartment of Biomedical Data Science, Stanford University School of Medicine, Stanford, California.
Yisheng LiDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston.
Hui Huang
John M HamptonDepartment of Population Health Sciences and Carbone Cancer Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison.
Juhee SongDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston.
Jinani JayasekeraIntramural Research Program, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, Maryland.
Clyde SchechterDepartment of Family and Social Medicine, Albert Einstein College of Medicine, Bronx, New York.
Oguzhan AlagozDepartment of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison.
Natasha K StoutDepartment of Population Medicine, Harvard Medical School, Boston, Massachusetts.
Amy Trentham-DietzDepartment of Population Health Sciences and Carbone Cancer Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison.
Sandra J LeeDepartment of Data Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts.
Xuelin HuangDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston.
Jeanne S MandelblattDepartment of Oncology, Georgetown University Medical Center, Georgetown Lombardi Comprehensive Cancer Center, Washington, DC.
Donald A BerryDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston.
Allison W KurianDepartment of Medicine, Stanford University School of Medicine, Stanford, California.
Sylvia K PlevritisDepartment of Biomedical Data Science, Stanford University School of Medicine, Stanford, California.
Stanford University · USThe University of Texas MD Anderson Cancer Center · USUniversity of Wisconsin Carbone Cancer Center · USAlbert Einstein College of Medicine · USDana-Farber Cancer Institute · USGeorgetown Lombardi Comprehensive Cancer CenterHarvard University · USNational Institutes of Health · USUniversity of Wisconsin–Madison · US

Funding

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
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
Health Equity and Decision SciencesZIAMD000022 · NIMHD · NATIONAL INSTITUTE ON MINORITY HEALTH AND HEALTH DISPARITIES · PI JAYASEKERA, JINANI · 2023 to 2025
$962k
NCI NIH HHS U01 CA199218NCI NIH HHS U01 CA253911
6 · The paper itself

Abstract

Importance: Breast cancer mortality in the US declined between 1975 and 2019. The association of changes in metastatic breast cancer treatment with improved breast cancer mortality is unclear. Objective: To simulate the relative associations of breast cancer screening, treatment of stage I to III breast cancer, and treatment of metastatic breast cancer with improved breast cancer mortality. Design, Setting, and Participants: Using aggregated observational and clinical trial data on the dissemination and effects of screening and treatment, 4 Cancer Intervention and Surveillance Modeling Network (CISNET) models simulated US breast cancer mortality rates. Death due to breast cancer, overall and by estrogen receptor and ERBB2 (formerly HER2) status, among women aged 30 to 79 years in the US from 1975 to 2019 was simulated. Exposures: Screening mammography, treatment of stage I to III breast cancer, and treatment of metastatic breast cancer. Main Outcomes and Measures: Model-estimated age-adjusted breast cancer mortality rate associated with screening, stage I to III treatment, and metastatic treatment relative to the absence of these exposures was assessed, as was model-estimated median survival after breast cancer metastatic recurrence. Results: The breast cancer mortality rate in the US (age adjusted) was 48/100 000 women in 1975 and 27/100 000 women in 2019. In 2019, the combination of screening, stage I to III treatment, and metastatic treatment was associated with a 58% reduction (model range, 55%-61%) in breast cancer mortality. Of this reduction, 29% (model range, 19%-33%) was associated with treatment of metastatic breast cancer, 47% (model range, 35%-60%) with treatment of stage I to III breast cancer, and 25% (model range, 21%-33%) with mammography screening. Based on simulations, the greatest change in survival after metastatic recurrence occurred between 2000 and 2019, from 1.9 years (model range, 1.0-2.7 years) to 3.2 years (model range, 2.0-4.9 years). Median survival for estrogen receptor (ER)-positive/ERBB2-positive breast cancer improved by 2.5 years (model range, 2.0-3.4 years), whereas median survival for ER-/ERBB2- breast cancer improved by 0.5 years (model range, 0.3-0.8 years). Conclusions and Relevance: According to 4 simulation models, breast cancer screening and treatment in 2019 were associated with a 58% reduction in US breast cancer mortality compared with interventions in 1975. Simulations suggested that treatment for stage I to III breast cancer was associated with approximately 47% of the mortality reduction, whereas treatment for metastatic breast cancer was associated with 29% of the reduction and screening with 25% of the reduction.

Indexed as

Breast NeoplasmsAdultAgedBreastEarly Detection of CancerErb-b2 Receptor Tyrosine KinasesFemaleHistory, 20th CenturyHistory, 21st CenturyHumansMammographyMiddle AgedMortalityReceptors, EstrogenUnited StatesERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesReceptors, Estrogen

Identifiers

PMID38227031
PMCPMC10792466
OpenAlexW4390919342

What OpenQuestion holds

Textmetadata
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.