Is mammography screening beneficial: An individual-based stochastic model for breast cancer incidence and mortality

PLoS Comput Biol. 2020 Jul 6;16(7):e1008036. doi: 10.1371/journal.pcbi.1008036. eCollection 2020 Jul.

Abstract

The benefits of mammography screening have been controversial, with conflicting findings from various studies. We hypothesize that unmeasured heterogeneity in tumor aggressiveness underlies these conflicting results. Based on published data from the Canadian National Breast Screening Study (CNBSS), we develop and parameterize an individual-based mechanistic model for breast cancer incidence and mortality that tracks five stages of breast cancer progression and incorporates the effects of age on breast cancer incidence and all-cause mortality. The model accurately reproduces the reported outcomes of the CNBSS. By varying parameters, we predict that the benefits of mammography depend on the effectiveness of cancer treatment and tumor aggressiveness. In particular, patients with the most rapidly growing or potentially largest tumors have the highest benefit and least harm from the screening, with only a relatively small effect of age. However, the model predicts that confining mammography to populations with a high risk of acquiring breast cancer increases the screening benefit only slightly compared with the full population.

Publication types

  • Randomized Controlled Trial
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Algorithms
  • Breast Neoplasms / diagnostic imaging*
  • Breast Neoplasms / mortality*
  • Computational Biology
  • Early Detection of Cancer*
  • Female
  • Follow-Up Studies
  • Humans
  • Incidence
  • Mammography*
  • Middle Aged
  • Models, Theoretical
  • Proportional Hazards Models
  • Stochastic Processes
  • Treatment Outcome