Variations in percent mammographic density (PMD) reflect variations in the amounts of collagen and number of epithelial and non-epithelial cells in the breast. Extensive PMD is associated with a markedly increased risk of invasive breast cancer. The PMD phenotype is important in the context of breast cancer prevention because extensive PMD is common in the population, is strongly associated with risk of the disease, and, unlike most breast cancer risk factors, can be changed. Work now in progress makes it likely that measurement of PMD will be improved in the near future and that understanding of the genetics and biological basis of the association of PMD with breast cancer risk will also improve. Future prospects for the application of PMD include mammographic screening, risk prediction in individuals, breast cancer prevention research, and clinical decision making.

To assess a schema for estimating the risk of radiation-induced breast cancer following exposure of the breast to ionizing radiation as would occur with mammography and to provide data that can be used to estimate the potential number of breast cancers, cancer deaths, and woman-years of life lost attributable to radiation exposure delivered according to a variety of screening scenarios. An excess absolute risk model was used to predict the number of radiation-induced breast cancers attributable to the radiation dose received for a single typical digital mammography examination. The algorithm was then extended to consider the consequences of various scenarios for routine screening beginning and ending at different ages, with examinations taking place at 1- or 2-year intervals. A life-table correction was applied to consider reductions of the cohort size over time owing to nonradiation-related causes of death. Finally, the numbers of breast cancer deaths and woman-years of life lost that might be attributable to the radiation exposure were calculated. Cancer incidence and cancer deaths were estimated for individual attained ages following the onset of screening, and lifetime risks were also calculated. For a cohort of 100 000 women each receiving a dose of 3.7 mGy to both breasts and who were screened annually from age 40 to 55 years and biennially thereafter to age 74 years, it is predicted that there will be 86 cancers induced and 11 deaths due to radiation-induced breast cancer. For the mammographic screening regimens considered that begin at age 40 years, this risk is small compared with the expected mortality reduction achievable through screening. The risk of radiation-induced breast cancer should not be a deterrent from mammographic screening of women over the age of 40 years.

Mammographic density has been strongly associated with increased risk of breast cancer. Furthermore, density is inversely correlated with the accuracy of mammography and, therefore, a measurement of density conveys information about the difficulty of detecting cancer in a mammogram. Initial methods for assessing mammographic density were entirely subjective and qualitative; however, in the past few years methods have been developed to provide more objective and quantitative density measurements. Research is now underway to create and validate techniques for volumetric measurement of density. It is also possible to measure breast density with other imaging modalities, such as ultrasound and MRI, which do not require the use of ionizing radiation and may, therefore, be more suitable for use in young women or where it is desirable to perform measurements more frequently. In this article, the techniques for measurement of density are reviewed and some consideration is given to their strengths and limitations.

Background: Population-based cancer screening can reduce cancer burden but was interrupted temporarily due to the COVID-19 pandemic. We estimated the long-term clinical impact of breast and colorectal cancer screening interruptions in Canada using a validated mathematical model. Methods: We used the OncoSim breast and colorectal cancers microsimulation models to explore scenarios of primary screening stops for 3, 6, and 12 months followed by 6–24-month transition periods of reduced screening volumes. For breast cancer, we estimated changes in cancer incidence over time, additional advanced-stage cases diagnosed, and excess cancer deaths in 2020–2029. For colorectal cancer, we estimated changes in cancer incidence over time, undiagnosed advanced adenomas and colorectal cancers in 2020, and lifetime excess cancer incidence and deaths. Results: Our simulations projected a surge of cancer cases when screening resumes. For breast cancer screening, a three-month interruption could increase cases diagnosed at advanced stages (310 more) and cancer deaths (110 more) in 2020–2029. A six-month interruption could lead to 670 extra advanced cancers and 250 additional cancer deaths. For colorectal cancers, a six-month suspension of primary screening could increase cancer incidence by 2200 cases with 960 more cancer deaths over the lifetime. Longer interruptions, and reduced volumes when screening resumes, would further increase excess cancer deaths. Conclusions: Interruptions in cancer screening will lead to additional cancer deaths, additional advanced cancers diagnosed, and a surge in demand for downstream resources when screening resumes. An effective strategy is needed to minimize potential harm to people who missed their screening.