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Collaborative modeling of the benefits and harms associated with different U.S. Breast cancer screening strategies

  • Jeanne S. Mandelblatt*
  • , Natasha K. Stout
  • , Clyde B. Schechter
  • , Jeroen J. Van Den Broek
  • , Diana L. Miglioretti
  • , Martin Krapcho
  • , Amy Trentham-Dietz
  • , Diego Munoz
  • , Sandra J. Lee
  • , Donald A. Berry
  • , Nicolien T. Van Ravesteyn
  • , Oguzhan Alagoz
  • , Karla Kerlikowske
  • , Anna N.A. Tosteson
  • , Aimee M. Near
  • , Amanda Hoeffken
  • , Yaojen Chang
  • , Eveline A. Heijnsdijk
  • , Gary Chisholm
  • , Xuelin Huang
  • Hui Huang, Mehmet Ali Ergun, Ronald Gangnon, Brian L. Sprague, Sylvia Plevritis, Eric Feuer, Harry J. De Koning, Kathleen A. Cronin
*Corresponding author for this work
  • Georgetown University
  • Harvard University
  • Albert Einstein College of Medicine
  • Erasmus University Rotterdam
  • University of California at Davis
  • Information Management Services, Inc.
  • University of Wisconsin-Madison
  • Stanford University
  • University of Texas MD Anderson Cancer Center
  • Department of Veterans Affairs
  • Dartmouth College
  • Dana-Farber Cancer Institute
  • University of Vermont
  • National Institutes of Health

Research output: Contribution to journalArticlepeer-review

248 Citations (Scopus)

Abstract

Background: Controversy persists about optimal mammography screening strategies. Objective: To evaluate screening outcomes, taking into account advances in mammography and treatment of breast cancer. Design: Collaboration of 6 simulation models using national data on incidence, digital mammography performance, treatment effects, and other-cause mortality. Setting: United States. Patients: Average-risk U.S. female population and subgroups with varying risk, breast density, or comorbidity. Intervention: Eight strategies differing by age at which screening starts (40, 45, or 50 years) and screening interval (annual, biennial, and hybrid [annual for women in their 40s and biennial thereafter]). All strategies assumed 100% adherence and stopped at age 74 years. Measurements: Benefits (breast cancer-specific mortality reduction, breast cancer deaths averted, life-years, and qualityadjusted life-years); number of mammograms used; harms (false-positive results, benign biopsies, and overdiagnosis); and ratios of harms (or use) and benefits (efficiency) per 1000 screens. Results: Biennial strategies were consistently the most efficient for average-risk women. Biennial screening from age 50 to 74 years avoided a median of 7 breast cancer deaths versus no screening; annual screening from age 40 to 74 years avoided an additional 3 deaths, but yielded 1988 more false-positive results and 11 more overdiagnoses per 1000 women screened. Annual screening from age 50 to 74 years was inefficient (similar bene-fits, but more harms than other strategies). For groups with a 2-to 4-fold increased risk, annual screening from age 40 years had similar harms and benefits as screening average-risk women biennially from 50 to 74 years. For groups with moderate or severe comorbidity, screening could stop at age 66 to 68 years. Limitation: Other imaging technologies, polygenic risk, and nonadherence were not considered. Conclusion: Biennial screening for breast cancer is efficient for average-risk populations. Decisions about starting ages and intervals will depend on population characteristics and the decision makers' weight given to the harms and benefits of screening.

Original languageEnglish
Pages (from-to)215-225
Number of pages11
JournalAnnals of Internal Medicine
Volume164
Issue number4
DOIs
Publication statusPublished - 16 Feb 2016
Externally publishedYes

Funding

FundersFunder number
National Cancer InstituteU01CA152958

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

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