DCEG investigators utilize a variety of research approaches in seeking to understand the causes of cancer. We have developed very brief definitions of some of the key epidemiologic terms to help the non-epidemiologist better understand how we study cancer in populations.
A cohort study compares a particular outcome (such as lung cancer) in groups of individuals who are alike in many ways but differ by a certain characteristic (for example, female nurses who smoke compared with those who do not smoke). DCEG investigators often pool together cohorts in order to search for information on rare exposures or cancers, or to strengthen the statistical power for a complicated analysis. Many of these so-called “pooling projects” are carried out under the auspices of the NCI Cohort Consortium. See examples of DCEG cohort studies.
A case-control study compares two groups of people: those with the disease or condition under study (cases) and a very similar group of people who do not have the disease or condition (controls). Researchers study the medical and lifestyle histories of the people in each group to learn what factors may be associated with the disease or condition. For example, one group may have been exposed to a particular substance that the other was not. Also called a retrospective study. See examples of case-control studies.
Descriptive epidemiology studies characterize trends in cancer incidence and mortality over time, age-specific rates, geographic distribution of cancer, race and ethnic differences in cancer rates, and birth cohort effects. See examples of descriptive epidemiology studies.
Evaluating exposure-response relationships is a crucial component in determining cancer causation. For that reason, quantitative exposure assessment plays an essential role in high-quality epidemiologic investigations. DCEG investigators have developed cutting-edge tools and techniques to evaluate the reliability and validity of exposure measurements used in cohort and case-control studies of occupational, lifestyle, and environmental exposures. In addition, our investigators continually work to improve upon these well-established methods. See examples of exposure assessment studies and methods.
Studies of cancer-prone families help to identify genetic and environmental factors that determine or modify cancer risk. Learn more about family studies.
DCEG investigates the biological basis of inherited and acquired genetic variants associated with cancer susceptibility, utilizing genome-wide association studies, exome sequencing, and candidate gene studies. DCEG investigators and their collaborators employ an array of advanced statistical methods to support these studies. Learn more about genomic studies.
Metabolomics is the study of small-molecule metabolites in cells, tissues, and organisms that are present in biofluids such as plasma and urine. An emerging field of study, metabolomics has the potential to improve exposure measures and delineate mechanistic links between exposures and cancer. Learn about early-stage DCEG research in metabolomics.
The human microbiota is the collection of all the microorganisms and bacteria that live in or on the human body, such as those present in the digestive system. In the emerging field of microbiomics, researchers study the extent and patterns of these microbes at various body sites and their influence on human health and disease. DCEG investigators are at the forefront of both methodologic and cancer association studies of the microbiome in human populations. Learn about early-stage DCEG research in microbiomics.
Molecular epidemiology is one approach we use to examine the relationship of genetic and environmental risk factors to cancer etiology. Using laboratory techniques, investigators look for biomarkers of disease and use them to understand the underlying mechanisms of disease in populations.
Risk modeling describes how researchers relate the risk of a given disease or health event to one or more risk factors. One purpose of risk modeling is to understand the etiologic importance of a given exposure while controlling for other factors that may affect risk. Another purpose is to use risk factors to predict the risk of disease in an individual or population. It is common to produce multivariate models of relative risk, which is the ratio of risk for a person with certain risk factors to the “reference” risk-level for all other people of the same age and race. The “reference” risk level is often the overall risk of disease given the lowest risk level for each factor in the model.
For clinical and public health applications, the absolute risk of disease is usually more useful than relative risk. The absolute risk is the chance that a person who is currently free of a given disease but has fixed risk factors will develop that disease over a defined time interval such as 5 years or 20 years. Absolute risk is reduced by competing mortality from other causes, especially over long time intervals. Methodologic research is used to define the best kinds of data for estimating absolute risk, to develop strategies for selecting and combining risk factors to project risk, to develop criteria to evaluate the performance of risk models in various applications, and to conduct validation studies using independent data to determine the performance of a risk model.
Learn about DCEG absolute risk models for breast cancer, colon cancer and melanoma, which were developed to aid clinicians and their patients.