Transcript chap8-eks-3ed.ppt

Chapter 8
Case-Control Studies
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Chapter Outline
8.1 Introduction
8.2 Identification of cases and controls
8.3 Obtaining information on exposure
8.4 Data analysis
8.5 Statistical justifications …
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Case-Control Studies
• Identify cases in a source population
• Select at random non-cases from the same
source population
• Compare exposure histories in cases & controls
Cases
Exposure histories
Population
Odds Ratio
Sample
non-cases
Exposure histories
Note: case-control samples do not permit the calculatino
of incidence or prevalence!
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Case-Control 2-by-2 Table
cross-tabulate exposure & disease status
Exposed
Nonexposed
Odds Ratio 
Cases
A1
Controls
B1
A0
B0
M1
M2
A /A
AB
odds of exposure, cases
 1 0  1 0
odds of exposure, controls B1 / B0 B1 A0
If done properly, the OR from the case control sample is
stochastically equivalent to the rate ratio in the underlying
source population
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Illustrative Example 8.2
D+
D-
• Source population: A
Seattle area HMO
E+
61
93
• 175 histologically
E− 114
165
confirmed prostate
cancer cases
175
258
• 258 similarly aged men
selected at random
A1 × B0
61 165
 0.95
from source population OR = B × A 
93 114
1
0
(controls)
 about equal risk of prostate
• Exposure: prior
cancer in vasectomized and
vasectomy
non-vasectomized men (“no
association”)
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Interpretation of case-control ORs
• Case-control OR is
stochastically
equivalent to an RR
• Multiple justifications
are provided in §8.5
• One such justification
is shown on the next
slide
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Case-Control Odds Ratio = Rate Ratio in
Underlying Cohort (Incidence Density Sampling)
• The 2-by-2 table should be
viewed as a sample from a
conceptual prospective
cohort
• Consider following a cohort:
as a case occurs, select at
random one or more controls
Rate Ratio =
rate1 A1 / T1 A1 / A0
=
=
rate0 A0 / T0 T1 / T0
where A1 represents number of exposed
cases, T0 represents number of non-exposed
person-time, and so on
A1 / A0 comes directly from case series
T1 / T0 in the underlying cohort estimated
by B1 /B0 from the control series
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Identifying Cases
• Types of cases
– Incident cases  onset of disease during study
interval (preferred)
– Prevalent cases  onset of disease before or during
study interval
• Sources of cases
– Population surveillance
– Hospitals and clinics
– Death certificates
– Administrative health records
– Pharmacy records
• Accurate ascertainment of
cases = essential!
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Selection of Controls
• The objective of the control series is to reflect
the relative frequency of exposure in the
source population (B1/B0 ≈ T1/T0)
•  controls represent a random sample of the source
population
• If using hospital-based cases → random sample of
hospital’s catchment area
• Sources of controls in practice
–
–
–
–
Population-based sample
Hospitals / clinics
“Friend controls”
Nested in a cohort
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Number of Controls per Case
• Maximum efficiency
with 1 control per
case (1:1)
• To increase statistical
power when the
number of cases is
limited, select up to 4
controls per case
(4:1)
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Sources of Exposure Information
•
•
•
•
•
•
Interview
Medical records
Birth & death certificates
Employment records
Environmental records
Biological specimens
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Good Information
• The quality of the study
depends on the quality of its
information (
)
• Gather information for cases
and controls in identical
manners (
is
best)
• Well designed
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Data Analysis
• Covered
– Dichotomous
exposure
– Multiple levels of
exposure
• Not covered
– Matched pairs
– Matched tuples
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Multiple Levels of Exposure
Exposure
Level
0
Cases
Controls
A0
B0
1
A1
B1
i
⁞
⁞
K
Ak
Bk
M1
M0
Ai B0
OR i 
Bi A0
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Multiple Levels of Exposure
Alcohol
gm/day
0-39 [0]
40-79 [1]
80-119 [2]
120+ [3]
Esoph
CA+
Esoph
CA-
29
386
75
280
51
87
45
22
200
775
Ai B0
OR i 
Bi A0
29  386
OR 0 
 1 (referent)
386  29
75  386
OR1 
 3.57
280  29
51 386
OR 2 
 7.80
87  29
45  386
OR 3 
 27.23
22  29
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