Understanding the limits of large datasets.

Many health professionals use large datasets to answer behavioral, translational, or clinical questions. Understanding the impact of missing data in large databases, such as disease registries, can avoid erroneous interpretations of these data. Using the California Cancer Registry, the authors selected seven common cancers, seven sociodemographic and clinical variables, and the top three reporting sources, as examples of the type of data that would be deemed critical to most studies. The gender variable had no missing data, followed by age (<0.1 % missing), ethnicity (1.7 %), stage (9.8 %), differentiation (39.1 %), and birthplace (41.1 %). Reports from hospitals and clinics had the lowest percentages of missing data. Users of large datasets should anticipate the limitations of missing data to prevent methodological flaws and misinterpretations of research findings. Knowledge of what and how much data may be missing in large datasets can help prevent errors in research conclusions, while better guiding treatment modalities and public health policies and programs.

Health journalism internships: a social marketing strategy to address health disparities.

The USA seeks to eliminate health disparities by stimulating the rapid uptake of health-promoting behaviors within disadvantaged communities. A health journalism internship incorporates social marketing strategies to increase communities' access to cancer information, while helping the interns who are recruited from underrepresented communities gain admission to top graduate schools. Interns are taught basic health journalism skills that enable them to create immediate streams of cancer-related press releases for submission to community newspapers. Interns are charged with the social responsibility of continuing this dissemination process throughout their careers. Intermediate outcomes are measured as mediators of distal behavioral change goals.

Racial/ethnic and gender disparities in renal cell carcinoma incidence and survival.

PURPOSE: We used a population based cancer registry to examine trends in renal cell carcinoma incidence and survival among 4 racial/ethnic groups (white, black, Hispanic and Asian/Pacific Islander) and both genders. MATERIALS AND METHODS: Race/ethnicity, gender, age, staging, length of survival and cause of death data were analyzed using 39,434 cases of renal cell carcinoma from 1988 to 2004 from the California Cancer Registry. Annual age adjusted incidence rates and relative survival rates were calculated for the racial/ethnic and gender groups. These rates and the percent of localized cancer were plotted by year, and Microsoft Excel was used to calculate linear regression equations. Median age was also calculated. Z-tests and chi-square tests were performed to determine p values. RESULTS: An increase in renal cell carcinoma incidence was found with localized cancer accounting for most of the increase. Black patients had a significantly higher incidence rate (p <0.0001) and lower survival rate (p <0.0001) than all other races/ethnicities despite having more localized cancer (p <0.005). Black patients were also diagnosed at a younger age (p <0.0001) than their counterparts. On the other hand Asian/Pacific Islanders had a lower incidence rate (p <0.0001) and higher survival rate (p <0.05) than all other races/ethnicities. Males had approximately twice the incidence rate of females and a lower survival rate (p <0.005). CONCLUSIONS: Higher incidence rates and lower survival rates were identified among black and male patients compared to their counterparts, while Asian/Pacific Islanders showed the opposite trends. Such racial/ethnic and gender disparities in renal cell carcinoma incidence and survival may help elucidate biological, behavioral and environmental factors that can potentially be addressed.