Cancer Epidemiology Cohorts


Cohort studies are one of the fundamental designs for epidemiological research. Cancer epidemiology cohorts are large observational population studies in which groups of people with a set of characteristics or exposures are prospectively followed for the incidence of new cancers and cancer-related outcomes. Data from cohort studies have helped researchers to better understand the complex etiology of cancer, and have provided fundamental insights into key environmental, lifestyle, clinical, and genetic determinants of this disease and its outcomes.

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Joanne Watters Elena, Ph.D., M.P.H.
Program Director, Clinical and Translational Epidemiology Branch

Funded Projects

View a list of EGRP-supported cancer epidemiology cohorts, with links to their abstracts and publications.

Related Research Resources

This list provides links to resources that may be of interest to cancer epidemiologists interested in or conducting cohort-based studies, but is not exhaustive.

Descriptive Information from Existing Cohort Studies

  • Cancer Epidemiology Descriptive Cohort Database
    This searchable database contains descriptive information about existing cohorts, including study design, eligibility criteria, enrollment numbers, numbers of biospecimens, and numbers of cancer and other health outcomes.
  • Biospecimen Resources for Population Sciences
    This list provides links to biospecimen resources that may be of interest to cancer epidemiologists, but is not exhaustive.
  • NCI Cohort Consortium
    The NCI Cohort Consortium is an extramural-intramural partnership formed by NCI to address the need for large-scale collaborations to pool the large quantity of data and biospecimens necessary to conduct a wide range of cancer studies. It includes investigators responsible for more than 60 high-quality cohorts involving more than 7 million people. The cohorts are international in scope and cover large, rich, and diverse populations. Investigators team up to use common protocols and methods, and to conduct coordinated parallel and pooled analyses.

NIH-Sponsored Data Repositories

  • Database of Genotypes and Phenotypes (dbGAP)
    The database of Genotypes and Phenotypes (dbGaP) was developed to archive and distribute the data and results from studies that have investigated the interaction of genotype and phenotype in Humans.
  • BioLINCC
    The National Heart, Lung, and Blood Institute's (NHLBI) centralized, controlled-access database, where Investigators can deposit and access datasets related to heart, lung and blood diseases.
  • EpiShare
    EpiShare is a web-based platform for sharing biospecimens and/or datasets with the greater research community. EpiShare provides a central location for researchers to see summaries of National Institute of Environmental Health Sciences (NIEHS) Epidemiology Branch studies and specimen inventories, submit requests, and track all requestor correspondence.

Cohort-related Analytical Tools

  • Cohort MetaData Repository
    The Cohort Metadata Repository (CMR) is a tool that documents data harmonization across cohorts. Variables from each cohort can be searched and compared to determine if harmonization is possible. Once harmonization has occurred, the harmonized variables and the specifications used to create the variables are also documented in the CMR. The CMR contains only metadata (variable names, formats, codes, descriptions) and no individual-level data. For more information on the CMR and how to use it, watch our archived webinar, Introduction to the Cohort Metadata Repository (CMR): A Data Harmonization ToolExternal Web Site Policy.
  • Nested Cohort Software Package
    NCI's intramural Division of Cancer Epidemiology and Genetics (DCEG) has made available this software package for fitting Kaplan-Meier and Cox Models to estimate standardized survival and attributable risks for studies where covariates of interest are observed on only a sample of the cohort. Standard designs that can be handled by this software include the case-cohort and case-control studies conducted within defined cohorts. At this time, the software does not yet support nested case-control designs.

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