Cohort Case Study Design

Printer-friendly version

A case-cohort study is similar to a nested case-control study in that the cases and non-cases are within a parent cohort; cases and non-cases are identified at time t1, after baseline. In a case-cohort study, the cohort members were assessed for risk factros at any time prior to t1. Non-cases are randomly selected from the parent cohort, forming a subcohort. No matching is performed.

Advantages of Case-Cohort Study:

Similar to nested case-control study design:

  • Efficient– not all members of parent cohort require diagnostic testing
  • Flexible– allows testing hypotheses not anticipated when the cohort was drawn (t0)
  • Reduces selection bias – cases and noncases sampled from same population
  • Reduced information bias – risk factor exposure can be assessed with investigator blind to case status

Other advantages, as compared to nested case-control study design:

  • The subcohort can be used to study multiple outcomes
  • Risk can be measured at any time up to t1 (e.g. elapsed time from a variable event, such as menopause, birth)
  • Subcohort can be used to calculate person-time risk

Disadvantages of Case-Cohort Study as compared to nested case-control study design:

  • Increased potential for information bias because
    • subcohort may have been established after t0
    • exposure information collected at different times (e.g. potential for sample deterioration)

Statistical Analysis for Case-Cohort Study:

Weighted Cox proportional hazards regression model (we will look at proportional hazards regression later in this course)

Cohort Study


A study design where one or more samples (called cohorts) are followed prospectively and subsequent status evaluations with respect to a disease or outcome are conducted to determine which initial participants exposure characteristics (risk factors) are associated with it. As the study is conducted, outcome from participants in each cohort is measured and relationships with specific characteristics determined


  • Subjects in cohorts can be matched, which limits the influence of confounding variables
  • Standardization of criteria/outcome is possible
  • Easier and cheaper than a randomized controlled trial (RCT)


  • Cohorts can be difficult to identify due to confounding variables
  • No randomization, which means that imbalances in patient characteristics could exist
  • Blinding/masking is difficult
  • Outcome of interest could take time to occur

Design pitfalls to look out for

The cohorts need to be chosen from separate, but similar, populations.

How many differences are there between the control cohort and the experiment cohort? Will those differences cloud the study outcomes?

Fictitious Example

A cohort study was designed to assess the impact of sun exposure on skin damage in beach volleyball players. During a weekend tournament, players from one team wore waterproof, SPF 35 sunscreen, while players from the other team did not wear any sunscreen. At the end of the volleyball tournament players' skin from both teams was analyzed for texture, sun damage, and burns. Comparisons of skin damage were then made based on the use of sunscreen. The analysis showed a significant difference between the cohorts in terms of the skin damage.

Real-life Example

Ramchand, R., Ialongo, N. S., & Chilcoat, H. D. (2007). The effect of working for pay on adolescent tobacco use. American Journal of Public Health, 97(11), 2056-2062.

This study uses data collected from high school students from Baltimore, Maryland, and studies the differences in initiation of tobacco use between a cohort of adolescents that started working for pay and a cohort of adolescents that did not work. The results suggest that adolescents who work for pay have a higher risk of initiating tobacco use.

Lindenauer, P. K., Rothberg, M. B., Pekow, P. S., Kenwood, C., Benjamin, E. M., & Auerbach, A. D. (2007). Outcomes of care by hospitalists, general internists, and family physicians. New England Journal of Medicine, 357(25), 2589-2600.

To study effects of hospitalists, general internists, and family physicians on patient care, patients that were hospitalized with certain conditions under the care of hospitalists, general internists, and family physicians were separated into three cohorts. The results showed that patients cared for by hospitalists had shorter hospital stays and lower costs than those cared for by general internists or family physicians.

Nichol, K. L., Nordin, J. D., Nelson, D. B., Mullooly, J. P., & Hak, E. (2007). Effectiveness of influenza vaccine in the community-dwelling elderly. New England Journal of Medicine, 357(14), 1373-1381.

To determine the long-term effectiveness of influenza vaccines in elderly people, cohorts of vaccinated elderly and unvaccinated community-dwelling elderly were studied. The results suggest that the elderly who are vaccinated have a reduced risk of hospitalization for pneumonia or influenza.

Related Formulas

Related Terms

  • Cohort

    A group that shares the same characteristics among its members (population).

  • Confounding Variables

    Variables that cause/prevent an outcome from occurring outside of or along with the variable being studied. These variables render it difficult or impossible to distinguish the relationship between the variable and outcome being studied).

  • Population Bias/Volunteer Bias

    A sample may be skewed by those who are selected or self-selected into a study. If only certain portions of a population are considered in the selection process, the results of a study may have poor validity.

  • Prospective Study

    A study that moves forward in time, or that the outcomes are being observed as they occur, as opposed to a retrospective study, which looks back on outcomes that have already taken place.

Now test yourself!


Leave a Reply

Your email address will not be published. Required fields are marked *