Impact of adjuvant therapy and mammography on U.S. mortality from 1975 to 2000: comparison of mortality results from the cisnet breast cancer base case analysis

J Natl Cancer Inst Monogr. 2006:(36):112-21. doi: 10.1093/jncimonographs/lgj015.


The CISNET breast cancer program is a consortium of seven research groups modeling the impact of various cancer interventions on the national trends of breast cancer incidence and mortality. Each of the modeling groups participated in a CISNET breast cancer base case analysis with the objective of assessing the impact of mammography and adjuvant therapy on breast cancer mortality between 1975 and 2000. The comparative modeling approach used to address this question allowed for a unique view into the process of modeling. Results shown here expand on those recently reported in the New England Journal of Medicine (Berry et al., N Engl J Med 2005;353:1784-92) by presenting mortality impact in several different ways to facilitate comparisons between models. Comparisons of each group's results in the context of modeling assumptions made during the process gave insight into how specific model assumptions may have affected the results. The median estimate for the percent decline in breast cancer mortality due to mammography was 15% (range of 8%-23%), and the median estimate for the percent decline in mortality due to adjuvant treatment was 19% (range of 12%-21%). A detailed discussion of the differences in modeling approaches and how those differences may have influenced the mortality results concludes the chapter.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Aged
  • Antineoplastic Combined Chemotherapy Protocols / therapeutic use*
  • Breast Neoplasms / diagnosis
  • Breast Neoplasms / drug therapy
  • Breast Neoplasms / mortality*
  • Case-Control Studies
  • Chemotherapy, Adjuvant / statistics & numerical data*
  • Computer Simulation
  • Female
  • Humans
  • Incidence
  • Mammography / statistics & numerical data*
  • Middle Aged
  • Models, Statistical*
  • Predictive Value of Tests
  • Sensitivity and Specificity
  • Survival Rate
  • United States / epidemiology