A set of training materials for professionals working in intervention epidemiology, public health microbiology and infection control and hospital hygiene.
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(a) Controls in different types of
case control studies: case cohort, traditional case control, density
Lets us come
back to the one of the characteristics of the control population, that
should be representative of exposures in
the source population. In selecting
controls for a case cohort study, a random sample of the source
should, if done correctly, be representative of the exposure
the population that gives rise to the cases. In a traditional case
study, where cases are excluded from the control selection, a bias has
introduced as the exposure distribution in potential controls is no
representative of the source population. If the attack rate is low, this
will also be low, but if attack rate is high, the potential for bias
be high (Chapter X). In a density case control study where cases occur
long time period, controls should be selected from the source population
free of disease at the time the case occurs. In this way they should be
representative of the person time experience of the source population
Does failure to
identify those with mild or asymptomatic infection as cases introduce
This situation is analogous to non- response among cases. If the
among symptomatic and asymptomatic cases are the same, then no bias is
introduced. There is only a reduction in power of the study. There is no
difference in control selection as controls should be representative of
In a hypothetical
case control study with 40 cases and 40 controls, and 50% exposure among
cases, Odds Ratio = 600/ 200 = 3.0
If we only detect
20 cases with the same number of controls , the Odds Ratio is unchanged
(300/100 = 3.0) as long as % exposure is the same in detected and
(c) Immune subjects
If some of the
population is immune at the start of the study, then they are not
be cases. They should then also be excluded as controls as they are not
the source population. In practice we do not usually know who is
immune. Again this may not matter if % exposed is the
same in immune and non-immune cases. However it may be that subjects are
immune because they have
already been cases in the past and that they have a similar level of
to the risk factor that caused the cases in the outbreak under study .
introduces bias that reduces the OR towards 1 and may result in a
detect a true association, especially if the proportion immune is high.
example, the inclusion of immune subjects in the control group is
explain the results of some case control studies that fail to show an
association between contaminated drinking water and cryptosporidiosis
(d) Power and sample size in
case control studies
A question often
arises about the number of controls given a limited number of cases.
Statistical programmes like Epi-Info can be used to estimate the sample
required to detect a specified odds ratio. It is unusual to select more
than 3 or 4 controls
per case as little statistical advantage is gained beyond this number
(Kirkwood and Sterne,
Figure). Alternatively we could show
that power increases and plateaus with an increasing number of controls
case. The graph would then have the same shape but inverted.
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