• Understanding Research: Case Control Studies

    by Cian O'Brien. Last modified: 09/05/14

    research

    • Study group is defined by the outcome (presence of a disease) not by exposure to a risk factor
    • The study starts with the identification of a group of cases (individuals with a particular health outcome) in a given population and a group of controls (individual without the health outcome)
    • Prevalence of exposure to a potential risk factor is compared between cases and control
    • If the prevalence of exposure is more common among cases than controls, the exposure may be a risk factor for the outcome
    • Useful for studying disease that are rare
    • Major characteristic is that data on potential risk factors are collected retrospectively – bias
    • A particular problem associated with case-controls – should be addressed in design and conduct of study

    Cases: People in a population with the disease

    Controls: People in a population without the disease

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    Issues in the design of case-control studies

    • Formulation of a clear hypothesis
    • Case definition
    • Sources of cases
    • Incident cases – cases newly diagnosed
    • Prevalent cases – individuals who have had the outcome under investigation for some time
    • Selection of controls  – should be selected to be a representative sample – to minimize bias

    Sources of Bias

    • Retrospective nature they are susceptible to the effects of bias which may be introduced as a result of a poor study design or during the collection of exposure and outcome data
    • Because the disease and exposure have already occurred at the outset of a case-control there may be differential reporting of exposure information between cases and controls based on their disease status
    • Cases and control may recall past exposures differently because knowledge of being a case may affect whether the individual remembers a certain exposure (recall bias)
    • The recording of exposure information may vary depending on the investigator’s knowledge of an individual’s disease status (observer bias)
    • Temporal bias may also occur when trying to establish a link between exposure and outcome. It must be clear that the exposure occurred well before the diagnosis of the disease
    • The design and conduct of the study must be carefully considered as there are limited options for the control of bias during analysis

    Confounding

    • A factor associated independently with both the exposure and outcome and can be a problem where cases and control differ with respect to a potential confounder.
    • It can be dealt with:
      • Design stage – when selecting controls (matching or restriction)
      • Analysis stage – statistical techniques (adjustment) and multivariate techniques

     Analysis of case-control studies

    • OR to estimate the strength of association between exposure and outcome
    • It is not possible to estimate the incidence of disease from a case-control study – unless the study is population based and all cases in a defined population are obtained

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    The odds ratio is a measure of the odds of exposure in the cases, compared to the odds of exposure in the control group.

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    Example

    Calculation of the OR from a hypothetical case-control study of smoking and cancer of the pancreas among 100 cases and 400 controls (Table 1)

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    The OR calculated from the hypothetical data in table 1 estimates that individuals with cancer of the pancreas (cases) are 4.5 times more likely to have smoked than those without the disease

    • The odds ratio of smoking and cancer of the pancreas has been performed without adjusting for potential confounders.
    • Further analysis of the data would involve stratifying by levels of potential confounders such as age.

    Strengths

    • Cost-effective relative
    • Case-control studies are retrospective, cases are identified at the beginning of the study –  no long follow up period (compared to cohort)
    • Efficient for the study of diseases with long latency periods
    • Efficient for the study of rare disease
    • Good for examining multiple exposures

    Weaknesses

    • Prone to bias – selection, recall & observer
    • Limited to examining one outcome
    • Unable to estimate incidence rates of disease
    • Poor choice for the study of rare exposures
    • The temporal sequence between exposure and disease may be difficult to determine

    Examples of case-control studies

    • Investigations of cases of childhood leukaemia near Sellafield

    Controlling for Confounding

    Design Stage:

    • Randomization – Reduces potential for confounding by generating groups that are fairly comparable with respect to known and unknown confounding variables (attempts to simulate a counterfactual contrast)
    • Restriction – Eliminates variation in the confounder (e.g. only recruiting males into the study will eliminate confounding by sex)
    • Matching – Involves selection of a comparison group that is forced to resemble the index group with respect to the distribution of one or more potential confounders

     Analysis:

    • Unlike selection and information bias, confounding is one type of bias that can be, to some extent, adjusted in the analysis
    • Stratification
    • Multivariate methods
    • To control for confounding in the analyses – must measure the confounders in the study!
    • Investigators usually do this by collecting data on all known, previously identified confounders
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    Cian O'Brien

    Cian O'Brien

    Cian is an Irish trained Emergency Medical Technician, Registered General Nurse and holds a Masters degree in Public Health from University College Cork, Ireland. His research interests include prehospital care and marathon medicine.

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