Ideally, crude, age-adjusted, and age-specific rates are used to plan for population-based cancer prevention and control interventions.
Confidence intervals reflect the range of variation in estimating cancer rates. The width of a confidence interval depends on the amount of variability in the data.
Stage measures how far a cancer has spread from its origin. The staging system used by CDC’s National Program of Cancer Registries (NPCR) and the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) programs is called Summary Stage. Information on stage provided in the U.S. Cancer Statistics Data Visualizations tool is classified using a Merged Summary Stage variable that combines three different summary stage variables used during different time periods.
Surveillance of cancer incidence and survival are essential in monitoring and understanding CDC’s efforts to support the needs of cancer survivors.
Prevalence helps identify the level of disease burden on the population and health care system. It is a function of both incidence and survival.
Healthy behaviors such as being physically active, avoiding tobacco, limiting the amount of alcohol you drink, and getting cancer screening tests and human papillomavirus vaccine as recommended may prevent or help successfully manage cancer.
Although cancer represents many heterogeneous diseases, some cancer types share common risk factors. Because risk factor information is not routinely collected by cancer registries, estimates for risk factor-associated cancers often are based only on cancer type. Using these standard definitions for risk factor-associated cancers can help facilitate comparisons of cancer burden across states and communities.
Cancer death rates and counts for 2011–2015 were estimated for the 436 federal congressional districts according to the boundaries for the 115th Congress of the United States. Cancer incidence rates and counts were estimated for 424 federal congressional districts.
When the numbers of cases or deaths used to compute rates are small, those rates tend to have poor reliability. Another important reason for using a threshold value for suppressing cells is to protect the confidentiality of patients whose data are included in a report by reducing or eliminating the risk of disclosing their identity.