cases
case-control studies
have disease of interest
controls
case-control studies
don’t have disease of interest but COULD develop it
pros
case-control studies
cons
case-control studies
when do we use case-control studies
to examine a possible relationship btwn exposure and disease
start with
case-control studies
cases and controls, then measure exposure
odds ratio =
case-control studies
ad/bc
OR = 1.2
the odds of using artifical sweeteners is 1.02 times greater in bladder cancer cases than in controls
if exposure is associated with disease, we expect
more exposed in cases than controls
OR < 1
case-control studies
protective factor
OR = 1
case-control studies
no association
OR = 2
case-control studies
cases twice as likely as controls
95% confidence interbal
case-control studies
if 1 is included, OR is not significant
if 1 is NOT included, OR is significant
OR provides good estimate of risk when
case-control studies
design: finding cases
case-control studies
sources of controls
case-control studies
non hospitalized controls:
* community: can be probability sample
* neighborhood controls
* random digit dialing to match neighborhood
* friend control
hospitalized controls:
* all other patients
* defined diagnosis
exposure
case-control studies
wording of questions
recall of exposure limitations
case-control studies
limitations in recal
case-control studies
ppl might not know specific info or remember
recall bias
case-control studies
cases may recall info to ggreater extent than controls
differential recall may lead to artifactual relationship
use of multiple controls
case-control studies
2 or 3 same controls per case increases power of study
controls of diff types may help (if looking at risk for brain tumors have a normal control and other cancer control)
nested case control study
case-control studies
case control nested in cohort study
population in defined cohort with baseline surveys and samples followed over time
cases: those who develop disease over time
advantages of nested case control
data collected before disease develops (no recall bias)
cheaper than analyzing all samples for all cohort members