ArticleMDM policy & practice2017
Using Collaborative Simulation Modeling to Develop a Web-Based Tool to Support Policy-Level Decision Making About Breast Cancer Screening Initiation Age.
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In one paragraph
Article in MDM policy & practice, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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8citing papers in PubMed, 1 pooled it
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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.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Reassessing the Benefits and Harms of Risk-Reducing Medication Considering the Persistent Risk of Breast Cancer Mortality in Estrogen Receptor-Positive Breast Cancer.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2023Pooled it
- Benefits and Harms of Mammography Screening in 75 + Women to Inform Shared Decision-making: a Simulation Modeling Study.Journal of general internal medicine · 2024Article
- Reflecting on 20 years of breast cancer modeling in CISNET: Recommendations for future cancer systems modeling efforts.PLoS computational biology · 2021Review
- The EU-TOPIA evaluation tool: An online modelling-based tool for informing breast, cervical, and colorectal cancer screening decisions in Europe.Preventive medicine reports · 2021Article
- Understanding Regional Variation in the Cost of Breast Cancer Screening Among Privately Insured Women in the United States.Medical care · 2021Article
- The Impact of Different Screening Model Structures on Cervical Cancer Incidence and Mortality Predictions: The Maximum Clinical Incidence Reduction (MCLIR) Methodology.Medical decision making : an international journal of the Society for Medical Decision Making · 2020Article
- Use and Costs of Breast Cancer Screening for Women in Their 40s in a US Population With Private Insurance.JAMA internal medicine · 2020Article
- Comparing CISNET Breast Cancer Models Using the Maximum Clinical Incidence Reduction Methodology.Medical decision making : an international journal of the Society for Medical Decision Making · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Elizabeth S BurnsideBreast Cancer Working Group of the Cancer Intervention and Surveillance Modeling Network (CISNET). Three independent modeling teams did this work from Dana-Farber Cancer Institute, Harvard Medical School (PI: Lee); Erasmus Medical Center (PI: de Koning); Harvard Medical School, University of Wisconsin (PI: Trentham-Dietz/Stout/Alagoz). Elizabeth Burnside, Jeanne Mandelblatt, Sandra Lee, and Aimee Near were the writing and coordinating committee for the project. From the Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin (ESB); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts (SJL, HH); Group Health Research Institute, Seattle, Washington (CB); Department of Oncology, Georgetown University Medical Center, and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC (JSM, AMN); Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin (OA, MAE); Department of Public Health, Erasmus MC, University Medical Center, Rotterdam, Netherlands (HJK, NTR, JJB); Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh (JYK); Department of Population Medicine, Harvard Medical School, and Harvard Pilgrim Health Care Institute, Boston, Massachusetts (NKS).
Sandra J LeeBreast Cancer Working Group of the Cancer Intervention and Surveillance Modeling Network (CISNET). Three independent modeling teams did this work from Dana-Farber Cancer Institute, Harvard Medical School (PI: Lee); Erasmus Medical Center (PI: de Koning); Harvard Medical School, University of Wisconsin (PI: Trentham-Dietz/Stout/Alagoz). Elizabeth Burnside, Jeanne Mandelblatt, Sandra Lee, and Aimee Near were the writing and coordinating committee for the project. From the Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin (ESB); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts (SJL, HH); Group Health Research Institute, Seattle, Washington (CB); Department of Oncology, Georgetown University Medical Center, and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC (JSM, AMN); Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin (OA, MAE); Department of Public Health, Erasmus MC, University Medical Center, Rotterdam, Netherlands (HJK, NTR, JJB); Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh (JYK); Department of Population Medicine, Harvard Medical School, and Harvard Pilgrim Health Care Institute, Boston, Massachusetts (NKS).
Carrie BennetteBreast Cancer Working Group of the Cancer Intervention and Surveillance Modeling Network (CISNET). Three independent modeling teams did this work from Dana-Farber Cancer Institute, Harvard Medical School (PI: Lee); Erasmus Medical Center (PI: de Koning); Harvard Medical School, University of Wisconsin (PI: Trentham-Dietz/Stout/Alagoz). Elizabeth Burnside, Jeanne Mandelblatt, Sandra Lee, and Aimee Near were the writing and coordinating committee for the project. From the Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin (ESB); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts (SJL, HH); Group Health Research Institute, Seattle, Washington (CB); Department of Oncology, Georgetown University Medical Center, and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC (JSM, AMN); Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin (OA, MAE); Department of Public Health, Erasmus MC, University Medical Center, Rotterdam, Netherlands (HJK, NTR, JJB); Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh (JYK); Department of Population Medicine, Harvard Medical School, and Harvard Pilgrim Health Care Institute, Boston, Massachusetts (NKS).
Aimee M NearBreast Cancer Working Group of the Cancer Intervention and Surveillance Modeling Network (CISNET). Three independent modeling teams did this work from Dana-Farber Cancer Institute, Harvard Medical School (PI: Lee); Erasmus Medical Center (PI: de Koning); Harvard Medical School, University of Wisconsin (PI: Trentham-Dietz/Stout/Alagoz). Elizabeth Burnside, Jeanne Mandelblatt, Sandra Lee, and Aimee Near were the writing and coordinating committee for the project. From the Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin (ESB); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts (SJL, HH); Group Health Research Institute, Seattle, Washington (CB); Department of Oncology, Georgetown University Medical Center, and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC (JSM, AMN); Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin (OA, MAE); Department of Public Health, Erasmus MC, University Medical Center, Rotterdam, Netherlands (HJK, NTR, JJB); Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh (JYK); Department of Population Medicine, Harvard Medical School, and Harvard Pilgrim Health Care Institute, Boston, Massachusetts (NKS).
Oguzhan AlagozBreast Cancer Working Group of the Cancer Intervention and Surveillance Modeling Network (CISNET). Three independent modeling teams did this work from Dana-Farber Cancer Institute, Harvard Medical School (PI: Lee); Erasmus Medical Center (PI: de Koning); Harvard Medical School, University of Wisconsin (PI: Trentham-Dietz/Stout/Alagoz). Elizabeth Burnside, Jeanne Mandelblatt, Sandra Lee, and Aimee Near were the writing and coordinating committee for the project. From the Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin (ESB); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts (SJL, HH); Group Health Research Institute, Seattle, Washington (CB); Department of Oncology, Georgetown University Medical Center, and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC (JSM, AMN); Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin (OA, MAE); Department of Public Health, Erasmus MC, University Medical Center, Rotterdam, Netherlands (HJK, NTR, JJB); Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh (JYK); Department of Population Medicine, Harvard Medical School, and Harvard Pilgrim Health Care Institute, Boston, Massachusetts (NKS).
Hui HuangBreast Cancer Working Group of the Cancer Intervention and Surveillance Modeling Network (CISNET). Three independent modeling teams did this work from Dana-Farber Cancer Institute, Harvard Medical School (PI: Lee); Erasmus Medical Center (PI: de Koning); Harvard Medical School, University of Wisconsin (PI: Trentham-Dietz/Stout/Alagoz). Elizabeth Burnside, Jeanne Mandelblatt, Sandra Lee, and Aimee Near were the writing and coordinating committee for the project. From the Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin (ESB); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts (SJL, HH); Group Health Research Institute, Seattle, Washington (CB); Department of Oncology, Georgetown University Medical Center, and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC (JSM, AMN); Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin (OA, MAE); Department of Public Health, Erasmus MC, University Medical Center, Rotterdam, Netherlands (HJK, NTR, JJB); Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh (JYK); Department of Population Medicine, Harvard Medical School, and Harvard Pilgrim Health Care Institute, Boston, Massachusetts (NKS).
Jeroen J van den BroekBreast Cancer Working Group of the Cancer Intervention and Surveillance Modeling Network (CISNET). Three independent modeling teams did this work from Dana-Farber Cancer Institute, Harvard Medical School (PI: Lee); Erasmus Medical Center (PI: de Koning); Harvard Medical School, University of Wisconsin (PI: Trentham-Dietz/Stout/Alagoz). Elizabeth Burnside, Jeanne Mandelblatt, Sandra Lee, and Aimee Near were the writing and coordinating committee for the project. From the Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin (ESB); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts (SJL, HH); Group Health Research Institute, Seattle, Washington (CB); Department of Oncology, Georgetown University Medical Center, and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC (JSM, AMN); Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin (OA, MAE); Department of Public Health, Erasmus MC, University Medical Center, Rotterdam, Netherlands (HJK, NTR, JJB); Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh (JYK); Department of Population Medicine, Harvard Medical School, and Harvard Pilgrim Health Care Institute, Boston, Massachusetts (NKS).
Joo Yeon KimBreast Cancer Working Group of the Cancer Intervention and Surveillance Modeling Network (CISNET). Three independent modeling teams did this work from Dana-Farber Cancer Institute, Harvard Medical School (PI: Lee); Erasmus Medical Center (PI: de Koning); Harvard Medical School, University of Wisconsin (PI: Trentham-Dietz/Stout/Alagoz). Elizabeth Burnside, Jeanne Mandelblatt, Sandra Lee, and Aimee Near were the writing and coordinating committee for the project. From the Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin (ESB); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts (SJL, HH); Group Health Research Institute, Seattle, Washington (CB); Department of Oncology, Georgetown University Medical Center, and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC (JSM, AMN); Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin (OA, MAE); Department of Public Health, Erasmus MC, University Medical Center, Rotterdam, Netherlands (HJK, NTR, JJB); Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh (JYK); Department of Population Medicine, Harvard Medical School, and Harvard Pilgrim Health Care Institute, Boston, Massachusetts (NKS).
Mehmet A ErgunBreast Cancer Working Group of the Cancer Intervention and Surveillance Modeling Network (CISNET). Three independent modeling teams did this work from Dana-Farber Cancer Institute, Harvard Medical School (PI: Lee); Erasmus Medical Center (PI: de Koning); Harvard Medical School, University of Wisconsin (PI: Trentham-Dietz/Stout/Alagoz). Elizabeth Burnside, Jeanne Mandelblatt, Sandra Lee, and Aimee Near were the writing and coordinating committee for the project. From the Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin (ESB); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts (SJL, HH); Group Health Research Institute, Seattle, Washington (CB); Department of Oncology, Georgetown University Medical Center, and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC (JSM, AMN); Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin (OA, MAE); Department of Public Health, Erasmus MC, University Medical Center, Rotterdam, Netherlands (HJK, NTR, JJB); Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh (JYK); Department of Population Medicine, Harvard Medical School, and Harvard Pilgrim Health Care Institute, Boston, Massachusetts (NKS).
Nicolien T van RavesteynBreast Cancer Working Group of the Cancer Intervention and Surveillance Modeling Network (CISNET). Three independent modeling teams did this work from Dana-Farber Cancer Institute, Harvard Medical School (PI: Lee); Erasmus Medical Center (PI: de Koning); Harvard Medical School, University of Wisconsin (PI: Trentham-Dietz/Stout/Alagoz). Elizabeth Burnside, Jeanne Mandelblatt, Sandra Lee, and Aimee Near were the writing and coordinating committee for the project. From the Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin (ESB); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts (SJL, HH); Group Health Research Institute, Seattle, Washington (CB); Department of Oncology, Georgetown University Medical Center, and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC (JSM, AMN); Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin (OA, MAE); Department of Public Health, Erasmus MC, University Medical Center, Rotterdam, Netherlands (HJK, NTR, JJB); Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh (JYK); Department of Population Medicine, Harvard Medical School, and Harvard Pilgrim Health Care Institute, Boston, Massachusetts (NKS).
Natasha K StoutBreast Cancer Working Group of the Cancer Intervention and Surveillance Modeling Network (CISNET). Three independent modeling teams did this work from Dana-Farber Cancer Institute, Harvard Medical School (PI: Lee); Erasmus Medical Center (PI: de Koning); Harvard Medical School, University of Wisconsin (PI: Trentham-Dietz/Stout/Alagoz). Elizabeth Burnside, Jeanne Mandelblatt, Sandra Lee, and Aimee Near were the writing and coordinating committee for the project. From the Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin (ESB); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts (SJL, HH); Group Health Research Institute, Seattle, Washington (CB); Department of Oncology, Georgetown University Medical Center, and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC (JSM, AMN); Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin (OA, MAE); Department of Public Health, Erasmus MC, University Medical Center, Rotterdam, Netherlands (HJK, NTR, JJB); Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh (JYK); Department of Population Medicine, Harvard Medical School, and Harvard Pilgrim Health Care Institute, Boston, Massachusetts (NKS).
Harry J de KoningBreast Cancer Working Group of the Cancer Intervention and Surveillance Modeling Network (CISNET). Three independent modeling teams did this work from Dana-Farber Cancer Institute, Harvard Medical School (PI: Lee); Erasmus Medical Center (PI: de Koning); Harvard Medical School, University of Wisconsin (PI: Trentham-Dietz/Stout/Alagoz). Elizabeth Burnside, Jeanne Mandelblatt, Sandra Lee, and Aimee Near were the writing and coordinating committee for the project. From the Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin (ESB); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts (SJL, HH); Group Health Research Institute, Seattle, Washington (CB); Department of Oncology, Georgetown University Medical Center, and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC (JSM, AMN); Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin (OA, MAE); Department of Public Health, Erasmus MC, University Medical Center, Rotterdam, Netherlands (HJK, NTR, JJB); Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh (JYK); Department of Population Medicine, Harvard Medical School, and Harvard Pilgrim Health Care Institute, Boston, Massachusetts (NKS).
Jeanne S MandelblattBreast Cancer Working Group of the Cancer Intervention and Surveillance Modeling Network (CISNET). Three independent modeling teams did this work from Dana-Farber Cancer Institute, Harvard Medical School (PI: Lee); Erasmus Medical Center (PI: de Koning); Harvard Medical School, University of Wisconsin (PI: Trentham-Dietz/Stout/Alagoz). Elizabeth Burnside, Jeanne Mandelblatt, Sandra Lee, and Aimee Near were the writing and coordinating committee for the project. From the Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin (ESB); Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts (SJL, HH); Group Health Research Institute, Seattle, Washington (CB); Department of Oncology, Georgetown University Medical Center, and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC (JSM, AMN); Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin (OA, MAE); Department of Public Health, Erasmus MC, University Medical Center, Rotterdam, Netherlands (HJK, NTR, JJB); Department of Health Policy and Management, Graduate School of Public Health, University of Pittsburgh, Pittsburgh (JYK); Department of Population Medicine, Harvard Medical School, and Harvard Pilgrim Health Care Institute, Boston, Massachusetts (NKS).
Funding
UW COMPREHENSIVE CANCER CENTER SUPPORTP30CA014520 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI Christian Capitini · 1985 to 2026
$142.6MRisk-based Imaging Strategies to Improve Breast Cancer Surveillance OutcomesP01CA154292 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Diana L Miglioretti · 2011 to 2026
$52.9MInstitutional Clinical and Translational Science AwardUL1TR000427 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2012 to 2016
$32.2MTrainingU54AI117924 · NIAID · UNIVERSITY OF WISCONSIN-MADISON · PI CRAVEN, MARK W. · 2014 to 2018
$11.3MComparative Modeling: Informing Breast Cancer Control Practice & PolicyU01CA152958 · NCI · GEORGETOWN UNIVERSITY · PI BERRY, DONALD A, DE KONING, HARRY J · 2010 to 2015
$7.6MVermont Screening Process Documentation UnitU54CA163303 · NCI · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI SPRAGUE, BRIAN L · 2011 to 2017
$6.4MInformatics Techniques to Optimize Mammography for Aging PopulationsR01CA165229 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI BURNSIDE, ELIZABETH S · 2012 to 2016
$1.7MMentoring And Research In Patient-Oriented Breast Cancer DiagnosisK24CA194251 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI BURNSIDE, ELIZABETH S · 2015 to 2019
$963kNCATS NIH HHS UL1 TR000427NCI NIH HHS HHSN261201100031CNCI NIH HHS K24 CA194251NCI NIH HHS P01 CA154292NCI NIH HHS P30 CA014520NCI NIH HHS R01 CA165229NCI NIH HHS U01 CA152958NCI NIH HHS U54 CA163303NIAID NIH HHS U54 AI117924
Abstract
backgroundThere are no publicly available tools designed specifically to assist policy makers to make informed decisions about the optimal ages of breast cancer screening initiation for different populations of US women.
objectiveTo use three established simulation models to develop a web-based tool called Mammo OUTPuT.
methodsThe simulation models use the 1970 US birth cohort and common parameters for incidence, digital screening performance, and treatment effects. Outcomes include breast cancers diagnosed, breast cancer deaths averted, breast cancer mortality reduction, false-positive mammograms, benign biopsies, and overdiagnosis. The Mammo OUTPuT tool displays these outcomes for combinations of age at screening initiation (every year from 40 to 49), annual versus biennial interval, lifetime versus 10-year horizon, and breast density, compared to waiting to start biennial screening at age 50 and continuing to 74. The tool was piloted by decision makers (n = 16) who completed surveys.
resultsThe tool demonstrates that benefits in the 40s increase linearly with earlier initiation age, without a specific threshold age. Likewise, the harms of screening increase monotonically with earlier ages of initiation in the 40s. The tool also shows users how the balance of benefits and harms varies with breast density. Surveys revealed that 100% of users (16/16) liked the appearance of the site; 94% (15/16) found the tool helpful; and 94% (15/16) would recommend the tool to a colleague.
conclusionsThis tool synthesizes a representative subset of the most current CISNET (Cancer Intervention and Surveillance Modeling Network) simulation model outcomes to provide policy makers with quantitative data on the benefits and harms of screening women in the 40s. Ultimate decisions will depend on program goals, the population served, and informed judgments about the weight of benefits and harms.
Indexed as
breast cancer screeningdecision makinghealth care policymammographysimulation modeling
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