Background: The American Cancer Society (ACS), Centers for Disease Control and Prevention (CDC), National Cancer Institute (NCI), and North American Association of Central Cancer Registries (NAACCR) collaborate annually to produce updated, national cancer statistics. This Annual Report includes a focus on breast cancer incidence by subtype using new, national-level data.
Methods: Population-based cancer trends and breast cancer incidence by molecular subtype were calculated. Breast cancer subtypes were classified using tumor biomarkers for hormone receptor (HR) and human growth factor-neu receptor (HER2) expression.
Results: Overall cancer incidence decreased for men by 1.8% annually from 2007 to 2011 [corrected]. Rates for women were stable from 1998 to 2011. Within these trends there was racial/ethnic variation, and some sites have increasing rates. Among children, incidence rates continued to increase by 0.8% per year over the past decade while, like adults, mortality declined. HR+/HER2- breast cancers, the subtype with the best prognosis, were the most common for all races/ethnicities with highest rates among non-Hispanic white women, local stage cases, and low poverty areas (92.7, 63.51, and 98.69 per 100000 non-Hispanic white women, respectively). HR+/HER2- breast cancer incidence rates were strongly, positively correlated with mammography use, particularly for non-Hispanic white women (Pearson 0.57, two-sided P < .001). Triple-negative breast cancers, the subtype with the worst prognosis, were highest among non-Hispanic black women (27.2 per 100000 non-Hispanic black women), which is reflected in high rates in southeastern states.
Conclusions: Progress continues in reducing the burden of cancer in the United States. There are unique racial/ethnic-specific incidence patterns for breast cancer subtypes; likely because of both biologic and social risk factors, including variation in mammography use. Breast cancer subtype analysis confirms the capacity of cancer registries to adjust national collection standards to produce clinically relevant data based on evolving medical knowledge.
© The Author 2015. Published by Oxford University Press.