The integration of epidemiology and molecular biology provides a new strategy to identify additional risk factors for breast cancer and to better understand the role played by traditionally recognized risk factors. The Carolina Breast Cancer Study (CBCS) is a population-based, case-control study designed to identify causes of breast cancer among Caucasian and African-American women who are residents of a 24-county area of central and eastern North Carolina. Information on established and potential breast cancer risk factors is obtained by personal interviews. Blood samples are collected from all consenting participants. Medical record documentation and paraffin-embedded tumor specimens are obtained for all breast cancer patients. DNA from tumor tissue is tested for a variety of molecular alterations characteristic of breast cancer. Germline DNA from blood lymphocytes is evaluated for presence of alleles increasing susceptibility to breast cancer. Statistical analyses evaluate gene-environment interaction by exploring the associations between environmental/behavioral factors and breast cancer in relation to specific molecular alterations (germline and tumor). Results will help identify high-risk women, clarify causal pathways, and hopefully contribute to the prevention of breast cancer.

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purpose: The goal of this study was to examine the effect of a rural community clinical oncology program‐based cancer‐care intervention program that was launched to increase the number of rural patients with cancer enrolled in clinical trials. description of study: Five rural counties in eastern North Carolina served as intervention communities, and five rural counties in South Carolina served as the comparison region. The intervention counties used a rapid tumor‐reporting system, a nurse facilitator who identified and prompted oncologists to enter patients into clinical trials, a quarterly newsletter to primary‐care physicians about cancer treatment and clinical trials, and a health educator who focused on community‐wide education regarding cancer prevention, treatment, and clinical trial information. Outcomes included changes in knowledge and attitudes about clinical trials among the primary‐care providers who were surveyed and enrollment in clinical treatment trials for breast and colorectal cancer, as analyzed by comparing practice pattern data from before and after the intervention. results: The results indicate that the intervention was not effective. The proportion of primary‐care physicians who were aware of clinical trials for their patients with cancer rose slightly in comparison counties (26% to 34%) but remained constant (41% to 43%) in intervention counties. Perceived patient and actual physician barriers toward clinical trial participation were reported by the physicians. A minority of potentially eligible patients with breast or colon cancer in both North Carolina and South Carolina were enrolled in clinical trials. clinical implications: These data suggest that different types of interventions may be needed to improve accrual to cancer treatment trials in rural communities. In addition, the role that primary‐care providers play in encouraging patients with cancer to participate in clinical treatment trials needs further exploration.

BackgroundStroke and myocardial infarction (MI) are serious public health burdens in the US. These burdens vary by geographic location with the highest mortality risks reported in the southeastern US. While these disparities have been investigated at state and county levels, little is known regarding disparities in risk at lower levels of geography, such as neighborhoods. Therefore, the objective of this study was to investigate spatial patterns of stroke and MI mortality risks in the East Tennessee Appalachian Region so as to identify neighborhoods with the highest risks.MethodsStroke and MI mortality data for the period 1999-2007, obtained free of charge upon request from the Tennessee Department of Health, were aggregated to the census tract (neighborhood) level. Mortality risks were age-standardized by the direct method. To adjust for spatial autocorrelation, population heterogeneity, and variance instability, standardized risks were smoothed using Spatial Empirical Bayesian technique. Spatial clusters of high risks were identified using spatial scan statistics, with a discrete Poisson model adjusted for age and using a 5% scanning window. Significance testing was performed using 999 Monte Carlo permutations. Logistic models were used to investigate neighborhood level socioeconomic and demographic predictors of the identified spatial clusters.ResultsThere were 3,824 stroke deaths and 5,018 MI deaths. Neighborhoods with significantly high mortality risks were identified. Annual stroke mortality risks ranged from 0 to 182 per 100,000 population (median: 55.6), while annual MI mortality risks ranged from 0 to 243 per 100,000 population (median: 65.5). Stroke and MI mortality risks exceeded the state risks of 67.5 and 85.5 in 28% and 32% of the neighborhoods, respectively. Six and ten significant (p < 0.001) spatial clusters of high risk of stroke and MI mortality were identified, respectively. Neighborhoods belonging to high risk clusters of stroke and MI mortality tended to have high proportions of the population with low education attainment.ConclusionsThese methods for identifying disparities in mortality risks across neighborhoods are useful for identifying high risk communities and for guiding population health programs aimed at addressing health disparities and improving population health.

The record files of the Dade County Medical Examiner Department were reviewed and 133 homicide-suicides were identified. Of these, ten (or 7.5%) were female perpetrated. The chart data of these 10 female homicide-suicide perpetrators, chart data of 50 female homicide-suicide victims, and 50 female individual suicides systematically selected as controls were tabulated using a standardized instrument. The results were analyzed for differences using simple statistical methods. The comparisons revealed that female homicide-suicide perpetrators were more likely than female homicide-suicide victims to live in mobile homes, kill their lover or ex-lover, have their crime accidentally discovered, leave a suicide note, kill on a weekend, and be depressed, but are less likely than female homicide-suicide victims to live with a spouse. Additionally, female homicide-suicide perpetrators were more likely than individual female suicides to live in mobile homes but less likely to live alone and to be depressed.