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Case Control Study

Lead Author(s): Jeff Martin, MD

Case Control Design

The main advantage of case-control designs is that it allows you to sample the experience of the study base most efficiently.

  • Stated in other words, case-control designs allow you to make measurements on far fewer subjects than cohort studies but still get the same answer.
The reason to do this is to conserve resources, something that is becoming more and more important these days as funding is drying up. A typical example is when expensive testing on stored biological samples are required for an analysis. It is often prohibitively costly to test everyone in the cohort.

Sampling Cases Within a Cohort

Given that all the cases are diagnosed, how would you sample controls from this cohort for a case-control study?

Think of the selection of cases and controls as occurring from a cohort as in the diagram below.

0528_1_casecontrol.JPG

Three Ways to Sample Controls Within a Cohort

  • A case-control study conducted from within a cohort is called a nested case-control study.

Summary of Case-Control Sampling

Design Sampling Measure of Association
Case-cohort Entire cohort at baseline risk ratio
Incidence-density Non-cases at time of diagnosis rate ratio
Prevalent Case Control Non-cases at single point in time odds ratio

Case-control design obtains a sample of the denominator rather than entire denominator

  • Introduces some sampling error
  • Reduces precision of the risk ratio or rate ratio or odds ratio estimate because sample N is smaller than full study base N
  • Loss of precision offset by large gain in cost and time of study

Important Features of a Case Control Study

(1) Primary versus Secondary Study Base: (2) Incident versus Prevalent Sampling:

Prevalent Sampling in a Case-Control Study

(1) UCSF Study of glioma patients is an example of prevalent sampling.

The patients are under treatment at UCSF during study period

  • Poor survival so patients in treatment will over-represent those who live longest
  • Nature of bias variable and not predictable
(2) Kaiser Permanente Study of Sigmoidoscopy is another example of prevalent sampling.

  • Cases = colon cancer deaths detectable by sigmoidoscopy: 261

  • Controls = alive and in Kaiser at time of matched CA death (incidence-density)
    • 4 controls per case

  • Many important findings have come from well designed case-control studies. This Kaiser study was the first to show strong evidence that screening sigmoidoscopy prevented colon cancer deaths. It had a substantial influence on clinical practice, yet it wasn’t a randomized trial, a study that would have required huge numbers and many years of follow-up. The study was feasible because Kaiser has a large membership, has been in existence for a long time, and has an excellent record keeping system.

Critical Features of Good Case-Control Design

Clearly identifiable study base (preferably a primary study base)

Cases: all, or random sample, of incident diagnoses in the study base

Controls: an unbiased sample of study base to estimate exposure prevalence in non-cases

Measurements preferably based on records or stored biological samples rather than recall

Case-control studies with all of these design features are a strong and valid study design that can produce results as convincing as any other type of observational study.

Measures of Association in a Case Control Study

The odds ratio is the only measure of association available in case-control design.

The odds ratio of disease in the exposed and unexposed

  • EQUALS the odds ratio of exposure in the diseased and the not diseased
The odds ratio of exposure in the diseased and not diseased that is actually measured in a case-control study,
  • but it is the odds ratio of disease in the exposed and unexposed that we are interested in.
  • Fortunately, they are mathematically identical. (See proof of mathematical equivalence.)
Fortunately, the odds ratio approximates the risk ratio and approximates the rate ratio in a case control study.

Common Misunderstandings about Case Control Studies

  • They can only study one disease outcome

  • Inference is not as valid as from a cohort

  • Rare disease assumption is required for OR from case-control to estimate risk ratio.
    • The rare disease assumption only looks at the effect of removing potential controls who are diagnosed with the outcome disease.
    • Some will have left the study base or died, and these changes in the group of non-cases who are sampled can bias the estimate of exposure in the controls.

  • Retrospective measurement is necessary in case-control studies

Reasons for Choosing Case Control Study Design

  • There are typically more opportunities for bias and misclassification in case-control studies than in cohort studies

  • Relative ease with which they can be done has encouraged a lot of badly designed studies

  • Low cost and shorter time should be an incentive to better, not worse, design

Case Control Study Design Recommendations

Historically the two chief weaknesses of case-control studies have been inappropriate selection of a control group and poor measurement of exposure.
  • The former has usually occurred in the setting of hospital-based studies with secondary study bases where it is very difficult to determine the study base that gave rise to the cases.


  • Use measurements recorded prior to the diagnosis when possible (medical records, etc.) or perform biological measurements on stored specimens. (See the example of the study in the Netherlands on vitamins and bladder cancer)
Poor measurement often occurs from using questionnaire recall of exposures.

If those weaknesses can be avoided, case-control can be a solid valid study design.


Topic revision: r41 - 03 Apr 2012 - 13:31:46 - MaryBanach
BERDpedia.CaseControlStudy moved from Main.CaseControlStudy on 08 Feb 2008 - 06:13 by MichaelGold?
 

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