Transcript Unit 10: Case-Control, Case-Crossover, and Cross-Sectional Studies Unit 10 Learning Objectives: 1. Understand design features of case-control, case-crossover, and cross-sectional studies. 2.

Unit 10:
Case-Control, Case-Crossover,
and Cross-Sectional Studies
Unit 10 Learning Objectives:
1. Understand design features of case-control,
case-crossover, and cross-sectional studies.
2. Understand strengths and limitations of casecontrol, case-crossover, and cross-sectional
studies.
3. Recognize potential biases from case-control,
case-crossover, and cross-sectional studies.
4. Recognize the impact of using prevalent versus
incident cases in case-control studies.
5. Recognize the difficulty in selecting an appropriate
control group in case-control studies.
• Understand the nested case-control study design.
• Recognize the difference between fixed and timedependent variables, including confounding
variables.
Case-Control
Studies
Case Control Studies
PRIMARY STEPS:

Define and select the cases.

Assemble an appropriate comparison group
(controls).

Determine and compare the proportion of
cases who have experienced the exposure
of interest -- with the proportion of controls
who
experienced the exposure.
Case Control Studies

Typically, compare the proportions of
exposure by means of a ratio: ODDS RATIO
Odds for exposure among cases
OR =
Odds for exposure among controls
D+
D-
E+
a
b
E-
c
d
OR
=
(a / c)
------(b / d)
Defining Cases

Ensure cases are as homogenous as
possible. Establish strict diagnostic
criteria (e.g. certain histologic
characteristics).

Sub-definitions of cases such as
definite, probable or possible may be
needed.

Analysis can be conducted for each
sub-group.
Prevalent vs. Incident
(Newly Diagnosed) Cases
To the extent possible,
avoid including
prevalent cases!
WHY?
Prevalent vs. Incident
(Newly Diagnosed) Cases
Why?


Determinants of disease duration may
be related to the exposure such that the
magnitude of the exposure (e.g. low vs.
high) may be inaccurate.
Prevalent cases with long disease
duration may not accurately recall
antecedent events.
Prevalent vs. Incident
(Newly Diagnosed) Cases
Why?

With prevalent cases, it is more difficult
to ensure that reported events preceded
disease development rather than being
a consequence of the disease process.
Prevalent vs. Incident
(Newly Diagnosed) Cases
---However, case-control studies of
congenital malformations are
inevitably based on prevalent cases.
---Prevalent cases are commonly used in
studies of chronic conditions with illdefined onset times (e.g. multiple
sclerosis).
Selecting Cases

Sources of Cases:
– Hospitals, medical care facilities, etc.
– General population - locate and obtain
data from all or a random sample of
individuals from a defined population.
Selecting Cases

Note: DO NOT compromise validity in
the goal of generalization.

Select cases from a defined
population in whom complete and
reliable information can be obtained,
and where the exposure/disease
relationship is presumed to be
present.
Defining and Selecting Cases

Ascertainment of Disease Status:
– Case registries (i.e. cancer)
– Office records of physicians
– Hospital admission or discharge
records
– Pathology department log books
Selecting Controls

Axiom: Selection of an appropriate
comparison group is the most
difficult and critical issue in the
design of case-control studies.
Selecting Controls

Controls are subjects free of the
disease (or outcome of interest).
– Controls are seldom subjected to
medical exam to rule out the
disease of interest.
– Usually, they are assumed
disease free if they have not been
diagnosed.
Selecting Controls
1. The prevalence of exposure among
controls should reflect the
prevalence of exposure in the source
population.
2. Controls should come from the same
source population as cases (e.g.
would have been cases if diagnosed
with the disease).
Selecting Controls
3. The time during which a subject is
eligible to be a control should be the
time in which the individual is also
eligible to be a case.
If #1, #2, or #3 are not met = Selection
Bias
Selecting Controls
Sources of Controls:
-----------
General population
Random digit dialing
Neighborhood
Friends/relatives
Hospital or clinic-based
Selecting Controls
General Population Controls:
--- Population defined by geographic
boundaries (or specific
characteristics).
--- Cases may include all cases, or a
random sample of all cases.
--- Controls should be a random sample
of non-diseased individuals eligible
to be cases.
Selecting Controls
General Population Controls:
--- If entire population is sampled for cases
and controls, can calculate incidence
rates of disease in exposed and nonexposed.
--- Selection of controls may be costly, time
consuming, and exposure recall may not
be as accurate as “sick” controls.
--- Subjects in general population may be
less motivated to participate than
hospital-based controls.
Selecting Controls
Random Digit Dialing Controls:
--- May approximate random sampling
from the source population.
--- Controls are often matched to cases
on area code and prefix (i.e. SES
matching).
--- Probability of contacting each
eligible subject may differ due to
time of day, number in household,
answering machines, etc.
Selecting Controls
Neighborhood Controls:
--- May approximate random sampling
from the source population.
--- Controls are often matched to cases
from the same neighborhood.
--- If cases are from a particular
hospital, neighborhood controls may
include people who would not have
been treated at the same hospital
had they developed the disease (e.g.
VA hospital).
Selecting Controls
Friend/Relative Controls:
--- Tend to be more cooperative than
general population controls.
--- Often similar to cases on factors
such as SES, lifestyle, and ethnic
background.
--- However, being named as a friend by
the case may be related to exposure
status of the potential control.
Selecting Controls
Friend/Relative Controls:
--- The list of potential friend/relative
controls is often derived from the
case; this dependence may add a
potential source of bias.
--- Hence, friend/relative controls may
be too similar to cases regarding the
exposure of interest.
Selecting Controls
Hospital/Clinic-Based Controls:
--- Source population refers to people
who “feed” the hospital or clinic.
--- Usually easier and less expensive
than general population controls.
--- May be more aware of exposures
and likely to cooperate than general
population controls (healthier).
Selecting Controls
Hospital/Clinic-based Controls:
--- Controls are ill; distribution of the
exposure may not reflect the
distribution of exposure in the source
population for cases.
--- Controls should be limited to
diagnoses for which there is no prior
indication of a relation with exposure.
--- Subjects may have changed their
exposure status as a result of being
sick.
Selecting Controls
General Remarks:
--- Often, there is no perfect control
group; several groups can be selected,
if feasible.
--- If study results are consistent across
control groups, may indicate a valid
result, but also possibly similar net
bias.
--- If different effects are observed, may
provide useful information as to nature
of the association or potential biases.
Selecting Controls
For each control group, how many
controls per case?
-- the optimal case-control ratio is 1:1
-- when the number of cases is small,
the sample size for the study can be
increased by using more than one
control
e.g.
1:2
1:3
1:4
Selecting Controls
AXIOM:
The benefit of increased
sample size is not as relevant
past the 1:4 ratio (e.g
increase in statistical power).
Ascertaining Exposure

Sources of exposure data (cases and
controls):
---Study subjects (self-report). Particularly
vulnerable to recall bias as cases may
recall their exposure history more
thoroughly than controls.
---Records (preferably completed before
the occurrence of outcome events).
---Interviews with surrogates (spouses,
siblings, etc.).
Ascertaining Exposure

How far back should exposure be
assessed?
---Define a part of the person’s exposure
history considered relevant to the
etiology of disease (e.g. the
“empirical induction” period).
---Code the exposure data in an
etiologically-relevant manner
(e.g. magnitude of exposure, years of
exposure, ever exposed, etc.).
Nested Case-Control Study
Definition: Hybrid design in which a casecontrol study is nested in a cohort study.
Cohort Study Population
Subjects
Develop
Disease
CASES
Do Not
Develop
Disease
CONTROLS
Exposure Status
Ascertained
Nested Case-Control Study
Advantages:
---Exposure data are collected before disease
development; eliminates recall bias.
---Can be economical if complete exposure
ascertainment is limited to only cases and
controls nested in the total cohort.
Often used in occupational epidemiology
where the occupational cohort is the
source population.
Summary – Case Control Studies
---Selection of an appropriate comparison
group is the most challenging and
important aspect of the study design.
---In population-based studies, incidence
can be calculated when entire population
is sampled.
---Hospital-based studies are often easiest
and cheapest to conduct, but may be
prone to biased exposure
ascertainment.
Summary – Case Control Studies
Advantages:
---Relatively quick and inexpensive.
---Well suited to evaluation of diseases
with long induction periods.
---Optimal for evaluation of rare diseases.
---Can examine multiple etiologic factors
for a single disease.
Summary – Case Control Studies
Disadvantages:
---Inefficient for evaluation of rare
exposures unless the disease is common
among the exposed.
---If not population based, cannot compute
incidence among the exposed and nonexposed.
Summary – Case Control Studies
Disadvantages (cont.):
---May be difficult to establish the temporal
relationship between exposure and
disease.
---Prone to bias compared to other analytic
designs, in particular, selection and recall
bias.
Review of Recommended Reading
PPA and Risk of Hemorrhagic Stroke
--- Case control study investigating exposure to products
containing phenylpropanolamine (PPA) and risk of
hemorrhagic stroke in persons 18-49 years of age.
--- 702 cases and 1,376 matched control subjects (randomdigit dialing) from 43 hospitals in 4 states (1994 to 1999)
--- Multiple definitions of exposure to PPA, including any
use, first use, specific type of product (i.e. appetite
suppressant).
--- Primary focal time to assess prior exposure history was
day/time that symptoms led subject to seek medical
attention.
--- Trained interviewers used structured instrument to
document prior exposure history.
--- Analyses conducted separately for men and women.
Discussion Question 1
The investigators excluded stroke victims who
died or did not have the ability to communicate
because they felt that proxy data (i.e. spouse) on
exposure status would be unreliable.
How might this exclusion of potential case
subjects bias (if at all) the study results?
Source: NEJM 2000; 343:1826-1832.
Discussion Question 2
The primary time in which exposure to PPA
was assessed occurred immediately preceding
the time in which medical attention was sought.
What type of bias (if any) could this strategy
have introduced?
Source: NEJM 2000; 343:1826-1832.
Discussion Question 3
On average, cases were required to recall PPA
exposure status over a more remote period
than control subjects. Do you think this
strategy offset the potential greater motivation
for cases to recall exposures to over-thecounter medications than control subjects?
Source: NEJM 2000; 343:1826-1832.
Discussion Question 4
Not stated in the article, the participation
rate for eligible subjects was 75% for cases
compared to 36% for controls.
How might this differential rate of participation
bias (if at all) the study results?
Source: NEJM 2000; 343:1826-1832.
Discussion Question 5
Interpret the results in table 4.
Are the findings similar among men
and women?
Source: NEJM 2000; 343:1826-1832.