Modeling the impact of population screening on breast cancer mortality in the United States

Breast. 2011 Oct;20 Suppl 3(Suppl 3):S75-81. doi: 10.1016/S0960-9776(11)70299-5.

Abstract

Objective: Optimal US screening strategies remain controversial. We use six simulation models to evaluate screening outcomes under varying strategies.

Methods: The models incorporate common data on incidence, mammography characteristics, and treatment effects. We evaluate varying initiation and cessation ages applied annually or biennially and calculate mammograms, mortality reduction (vs. no screening), false-positives, unnecessary biopsies and over-diagnosis.

Results: The lifetime risk of breast cancer death starting at age 40 is 3% and is reduced by screening. Screening biennially maintains 81% (range 67% to 99%) of annual screening benefits with fewer false-positives. Biennial screening from 50-74 reduces the probability of breast cancer death from 3% to 2.3%. Screening annually from 40 to 84 only lowers mortality an additional one-half of one percent to 1.8% but requires substantially more mammograms and yields more false-positives and over-diagnosed cases.

Conclusion: Decisions about screening strategy depend on preferences for benefits vs. potential harms and resource considerations.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Breast Neoplasms / diagnosis*
  • Breast Neoplasms / mortality*
  • Early Detection of Cancer / mortality
  • Early Detection of Cancer / statistics & numerical data
  • Female
  • Humans
  • Incidence
  • Mammography / mortality
  • Mammography / statistics & numerical data*
  • Mass Screening / mortality
  • Mass Screening / statistics & numerical data*
  • Middle Aged
  • Models, Statistical*
  • Reproducibility of Results
  • Risk Assessment
  • Sensitivity and Specificity
  • Survival Analysis
  • United States