Models of breast cancer show that risk is set by events of early life: prevention efforts must shift focus

Cancer Epidemiol Biomarkers Prev. 1995 Jul-Aug;4(5):567-71.

Abstract

We have recently published a mathematical model of the etiology of breast cancer based on the data from the Nurses Health Study that extends the Pike model of breast cancer (see Appendix). The most salient feature of the model is that it identifies the years before the first birth of a child as the most crucial in establishing future risk of breast cancer. The extended model includes several additional details of reproductive risk factors, allowing us to quantify the relative importance of each of the reproductive risk factors and to estimate the effect of changes in key determinants of breast cancer. In this review, we present the evidence from both animal studies and epidemiological research that corroborate the critical importance of the exposures that occur before first birth. We argue that research and preventive interventions should now focus on youth. Population-wide prevention strategies are necessary because the inherited genetic risk for breast cancer accounts for no more than 10-15% of all breast cancer cases, leaving 85% of cases diagnosed among women who are not in this high-risk subgroup of the population. An example of a population-based intervention would be the promotion of increased physical activity among young girls that could result in the delay of menarche. An example of additional research that focuses on the importance of early life exposures would be an analysis of the relation between diet and other lifestyle factors during adolescence and the subsequent risk of breast cancer and studies of precursor lesions (atypical hyperplasia). Shifting the focus of breast cancer prevention to this age group is urgently needed.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.
  • Review

MeSH terms

  • Age Factors
  • Animals
  • Breast Neoplasms / etiology*
  • Breast Neoplasms / prevention & control*
  • Disease Models, Animal
  • Female
  • Humans
  • Life Style
  • Risk Factors