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Chapter 8

Case-Control Studies

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Chapter Outline

8.1 Introduction 8.2 Identification of cases and controls8.3 Obtaining information on exposure8.4 Data analysis8.5 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

Population

Cases

Sample non-cases

Exposure histories

Exposure histories

Odds Ratio

Note: case-control samples do not permit the calculatino Note: case-control samples do not permit the calculatino of incidence or prevalence!of incidence or prevalence!

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Case-Control 2-by-2 Table

Cases Controls

Exposed A1 B1

Nonexposed A0 B0

M1 M2

cross-tabulate exposure & disease status

1 0 1 0

1 0 1 0

/odds of exposure, casesOdds Ratio

odds of exposure, controls /

A A AB

B B B A

If done properly, the OR from the case control sample is If done properly, the OR from the case control sample is stochastically equivalent to the rate ratio in the underlying stochastically equivalent to the rate ratio in the underlying source populationsource population

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Illustrative Example 8.2

• Source populationSource population: A Seattle area HMO

• 175 histologically confirmed prostate confirmed prostate cancer casescancer cases

• 258 similarly aged men selected at random selected at random from source populationfrom source population (controlscontrols)

• ExposureExposure: prior vasectomy

D+ D-

E+ 61 93

E− 114 165

175 258

61 1650.95

93 114

about equal risk of prostate cancer in vasectomized and non-vasectomized men (“no association”)

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Interpretation of case-control ORsORs

• 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

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Identifying Cases• Types of cases

– Incident casesIncident cases onset of disease during study interval (preferred)(preferred)

– Prevalent casesPrevalent 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 objectiveobjective of the control series is to reflect the the

relative frequency of exposure in the source relative frequency of exposure in the source populationpopulation (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

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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

ExposureLevel

Cases Controls

0 A0 B0

1 A1 B1

i ⁞ ⁞

K Ak Bk

M1 M0

0

0

ii

i

ABOR

B A

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Multiple Levels of ExposureAlcohol gm/day

EsophCA+

EsophCA-

0-39 [0] 29 386

40-79 [1] 75 280

80-119 [2] 51 87

120+ [3] 45 22

200 775

0

0

ii

i

ABOR

B A

1

75 3863.57

280 29OR

0

29 3861 (referent)

386 29OR

2

51 3867.80

87 29OR

3

45 38627.23

22 29OR