BackgroundThe 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.MethodsPopulation-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.ResultsOverall cancer incidence decreased for men by 1.8% annually from 2007 to 2011. 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. Overall mortality has been declining for both men and women since the early 1990’s and for children since the 1970’s. 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 100 000 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 100 000 non-Hispanic black women), which is reflected in high rates in southeastern states.ConclusionsProgress 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.

Many geographic studies use distance as a simple measure of accessibility, risk, or disparity. Straight-line (Euclidean) distance is most often used because of the ease of its calculation. Actual travel distance over a road network is a superior alternative, although historically an expensive and labor-intensive undertaking. This is no longer true, as travel distance and travel time can be calculated directly from commercial Web sites, without the need to own or purchase specialized geographic information system software or street files. Taking advantage of this feature, we compare straight-line and travel distance and travel time to community hospitals from a representative sample of more than 66,000 locations in the fifty states of the United States, the District of Columbia, and Puerto Rico. The measures are very highly correlated (r2 > 0.9), but important local exceptions can be found near shorelines and other physical barriers. We conclude that for nonemergency travel to hospitals, the added precision offered by the substitution of travel distance, travel time, or both for straight-line distance is largely inconsequential.

Previous studies found that uninsured and Medicaid insured cancer patients have poorer outcomes than cancer patients with private insurance. We examined the association between health insurance status and survival of New Jersey patients 18–64 diagnosed with seven common cancers during 1999–2004. Hazard ratios (HRs) with 95% confidence intervals for 5-year cause-specific survival were calculated from Cox proportional hazards regression models; health insurance status was the primary predictor with adjustment for other significant factors in univariate chi-square or Kaplan–Meier survival log-rank tests. Two diagnosis periods by health insurance status were compared using Kaplan–Meier survival log-rank tests. For breast, colorectal, lung, non-Hodgkin lymphoma (NHL), and prostate cancer, uninsured and Medicaid insured patients had significantly higher risks of death than privately insured patients. For bladder cancer, uninsured patients had a significantly higher risk of death than privately insured patients. Survival improved between the two diagnosis periods for privately insured patients with breast, colorectal, or lung cancer and NHL, for Medicaid insured patients with NHL, and not at all for uninsured patients. Survival from cancer appears to be related to a complex set of demographic and clinical factors of which insurance status is a part. While ensuring that everyone has adequate health insurance is an important step, additional measures must be taken to address cancer survival disparities.

Background & Aims Little is known about the effects of geographic factors, such as rural vs urban residence and travel time to colonoscopy providers, on risk-appropriate use of colorectal cancer (CRC) screening in the general population. We evaluated the effects of geographic factors on adherence to CRC screening and differences in screening use among familial risk groups. Methods We analyzed data from the 2010 Utah Behavior Risk Factor Surveillance System, which included state-added questions on familial CRC. Using multiple logistic regression models, we assessed the effects of rural vs urban residence, travel time to the nearest colonoscopy provider, and spatial accessibility of providers on adherence to risk-appropriate screening guidelines. Study participants (n=4260) were respondents 50–75 years old. Results Sixty-six percent of the sample adhered to risk-appropriate CRC screening guidelines, with significant differences between urban and rural residents (68% vs 57%, respectively; P<.001) across all familial risk groups. Rural residents were less likely than urban dwellers to be up-to-date with screening guidelines (multivariate odds ratio=0.65; 95% confidence interval [CI], 0.53–0.79). In the unadjusted analysis, rural vs urban residence (P<.001), travel time to the nearest colonoscopy provider (P=.003), and spatial accessibility of providers (P=.012) were significantly associated with adherence to screening guidelines. However, rural vs urban residence (P<.001) was the only geographic variable independently associated with screening adherence in the adjusted analyses. Conclusion There are marked disparities in use of risk-appropriate CRC screening between rural and urban residents in Utah. Differences in travel time to the nearest colonoscopy provider and spatial accessibility of providers did not account for the geographic variations observed in screening adherence.