Evidence map›Paper›PMID 23417335›Full record

ArticleBreast cancer research and treatment2013

Variation in tumor natural history contributes to racial disparities in breast cancer stage at diagnosis.

Nataliya G Batina, Amy Trentham-Dietz, Ronald E Gangnon, Brian L Sprague, Marjorie A Rosenberg, Natasha K Stout, Dennis G Fryback, Oguzhan Alagoz

Open access · greenAbstract read
In one paragraph

Article in Breast cancer research and treatment, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

20 citing papers in PubMed, 33 citations in OpenAlex.

  1. Article
  2. A Scoping Review on Calibration Methods for Cancer Simulation Models.Medical decision making : an international journal of the Society for Medical Decision Making · 2025
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  3. Review
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  10. Review
  11. The University of Wisconsin Breast Cancer Epidemiology Simulation Model: An Update.Medical decision making : an international journal of the Society for Medical Decision Making · 2018
    Article
  12. Article
  13. Effect of Time to Diagnostic Testing for Breast, Cervical, and Colorectal Cancer Screening Abnormalities on Screening Efficacy: A Modeling Study.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2018
    Article
  14. Article
  15. Using Active Learning for Speeding up Calibration in Simulation Models.Medical decision making : an international journal of the Society for Medical Decision Making · 2016
    Article
  16. What Predicts an Advanced-Stage Diagnosis of Breast Cancer? Sorting Out the Influence of Method of Detection, Access to Care, and Biologic Factors.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2016
    Article
  17. Cancer Models and Real-world Data: Better Together.Journal of the National Cancer Institute · 2016
    Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Nataliya G BatinaDepartment of Industrial and Systems Engineering, University of Wisconsin, 1513 University Avenue, Madison, WI 53706, USA.
Amy Trentham-Dietz
Ronald E Gangnon
Brian L Sprague
Marjorie A Rosenberg
Natasha K Stout
Dennis G Fryback
Oguzhan Alagoz
University of Wisconsin–Madison · USHarvard University · USUniversity of Vermont · USUniversity of Wisconsin Carbone Cancer Center · US

Funding

UW COMPREHENSIVE CANCER CENTER SUPPORTP30CA014520 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI AMY TRENTHAM-DIETZ · 1985 to 2026
$142.6M
Statistical Coordinating Center for the Breast Cancer Surveillance ConsortiumU01CA086076 · NCI · KAISER FOUNDATION HEALTH PLAN OF WASHINGTON · PI MIGLIORETTI, DIANA L · 2000 to 2011
$8.5M
Comparative Modeling: Informing Breast Cancer Control Practice & PolicyU01CA152958 · NCI · GEORGETOWN UNIVERSITY · PI BERRY, DONALD A, DE KONING, HARRY J · 2010 to 2015
$7.6M
IMPROVING THE QUALITY OF MAMMOGRAPHIC INTERPRETATIONU01CA063731 · NCI · KAISER FOUNDATION HEALTH PLAN OF WASHINGTON · PI BUIST, DIANA SM · 1994 to 2011
$6.7M
VERMONT BREAST CANCER SURVEILLANCE SYSTEMU01CA070013 · NCI · UNIVERSITY OF VERMONT &ST AGRIC COLLEGE · PI GELLER, BERTA M · 1995 to 2011
$6.7M
UTILITY AND OUTCOMES FROM MAMMOGRAPHY IN NORTH CAROLINAU01CA070040 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI YANKASKAS, BONNIE C · 1995 to 2011
$6.4M
San Francisco Mammography Registry-A Research SourceU01CA063740 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KERLIKOWSKE, KARLA M · 1994 to 2011
$6.2M
STRATEGIC STUDIES IN BREAST CANCER SURVEILLANCEU01CA086082 · NCI · DARTMOUTH COLLEGE · PI ONEGA, TRACY · 2000 to 2011
$4.9M
REFERRAL PATTERNS AND COST ANALYSIS OF SCREENING MAMMOGRAPHY--FOLLOW-UP/BIOPSYU01CA063736 · NCI · COOPER INSTITUTE · PI CUTTER, GARY · 1994 to 2004
$2.7M
NEW MEXICO MAMMOGRAPHY PROJECTU01CA069976 · NCI · UNIVERSITY OF NEW MEXICO · PI ROSENBERG, ROBERT D · 1995 to 2005
$2.7M
SIMULATING BREAST CANCER IN WISCONSINU01CA088211 · NCI · UNIVERSITY OF WISCONSIN MADISON · PI FRYBACK, DENNIS G. · 2000 to 2004
$862k
Using the UWBCS to Assess Racial Disparities in Breast Cancer Incidence & SurvivaR03CA130727 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI ALAGOZ, OGUZHAN · 2007 to 2008
$139k
NCI NIH HHS HHSN261201100031CNCI NIH HHS P30 CA014520NCI NIH HHS R01CA088211NCI NIH HHS R03 CA130727NCI NIH HHS R03CA130727NCI NIH HHS U01 CA063731NCI NIH HHS U01 CA063736NCI NIH HHS U01 CA063740NCI NIH HHS U01 CA069976NCI NIH HHS U01 CA070013NCI NIH HHS U01 CA070040NCI NIH HHS U01 CA086076NCI NIH HHS U01 CA086082NCI NIH HHS U01 CA088211NCI NIH HHS U01 CA152958NCI NIH HHS U01CA152958NCI NIH HHS U01CA63731NCI NIH HHS U01CA63736NCI NIH HHS U01CA63740NCI NIH HHS U01CA69976NCI NIH HHS U01CA70013NCI NIH HHS U01CA70040NCI NIH HHS U01CA86076NCI NIH HHS U01CA86082
6 · The paper itself

Abstract

Black women tend to be diagnosed with breast cancer at a more advanced stage than whites and subsequently experience elevated breast cancer mortality. We sought to determine whether there are racial differences in tumor natural history that contribute to these disparities. We used the University of Wisconsin Breast Cancer Simulation Model, a validated member of the National Cancer Institute's Cancer Intervention and Surveillance Modeling Network, to evaluate the contribution of racial differences in tumor natural history to observed disparities in breast cancer incidence. We fit eight natural history parameters in race-specific models by calibrating to the observed race- and stage-specific 1975-2000 U.S. incidence rates, while accounting for known racial variation in population structure, underlying risk of breast cancer, screening mammography utilization, and mortality from other causes. The best fit models indicated that a number of natural history parameters must vary between blacks and whites to reproduce the observed stage-specific incidence patterns. The mean of the tumor growth rate parameter was 63.6 % higher for blacks than whites (0.18, SE 0.04 vs. 0.11, SE 0.02). The fraction of tumors considered highly aggressive based on their tendency to metastasize at a small size was 2.2 times greater among blacks than whites (0.41, SE 0.009 vs. 0.019, SE 0.008). Based on our simulation model, breast tumors in blacks grow faster and are more likely to metastasize earlier than tumors in whites. These differences suggest that targeted prevention and detection strategies that go beyond equalizing access to mammography may be needed to eliminate breast cancer disparities.

Indexed as

Black or African AmericanBreast NeoplasmsCalibrationFemaleHealthcare DisparitiesHumansIncidenceModels, BiologicalNeoplasm StagingSEER ProgramTumor BurdenUnited StatesWhite People

Identifiers

PMID23417335
PMCPMC3610865
OpenAlexW2080822340

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.