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Using Collaborative Simulation Modeling to Develop a Web-Based Tool to Support Policy-Level Decision Making About

Elizabeth S Burnside1, Sandra J Lee1, Carrie Bennette1

  • 1Breast 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).

MDM Policy & Practice
|January 30, 2018
PubMed
Summary

A new web tool, Mammo OUTPuT, helps policymakers assess breast cancer screening in women aged 40-49. It quantifies benefits and harms of early screening initiation, aiding informed decision-making for diverse populations.

Keywords:
breast cancer screeningdecision makinghealth care policymammographysimulation modeling

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Area of Science:

  • Health Services Research
  • Preventive Medicine
  • Biostatistics

Background:

  • No existing tools aid policymakers in determining optimal breast cancer screening ages for diverse US women.
  • Informed decisions on screening initiation ages are crucial for public health policy.

Purpose of the Study:

  • To develop Mammo OUTPuT, a web-based decision-support tool for breast cancer screening policy.
  • To utilize three established simulation models to project screening outcomes.

Main Methods:

  • Simulation models based on the 1970 US birth cohort.
  • Incorporation of parameters for incidence, screening performance, and treatment effects.
  • Mammo OUTPuT tool displays outcomes for various screening initiation ages, intervals, horizons, and breast densities.

Main Results:

  • Benefits of screening in the 40s increase linearly with earlier initiation.
  • Harms of screening also increase monotonically with earlier initiation ages.
  • The tool illustrates how breast density influences the balance of benefits and harms.

Conclusions:

  • Mammo OUTPuT synthesizes Cancer Intervention and Surveillance Modeling Network (CISNET) simulation data.
  • Provides policymakers with quantitative insights into the benefits and harms of screening women in their 40s.
  • Facilitates informed judgments for ultimate screening policy decisions based on program goals and population served.