Variants of the case- control design

Katharina Alpers

EPIET introductory course, Menorca (Spain), 10 October, 2011

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Overview

Design of case-control studies

• Exclusive („traditional“)

• Inclusive („case-cohort“)

• Concurrent (density)

• Case-to-case

• Case-crossover

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Cohort study: incidence risk

Exposure Total Cases Risk (%) Risk ratio

Exposed 100 40 40% 4

Unexposed 100 10 10% Reference

Total 200 50 25%

Cumulative incidenceNumber of cases/population initially at risk

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Cohort study: incidence rate

Exposure Total

Time

Cases Rate

per 100 p.y.

Rate ratio

Exposed 1500 p.y 40 2.7/100 p.y. 2.7

Unexposed 1000 p.y. 10 1.0/100 p.y. Reference

Total 2500 p.y. 50 2.0/100 p.y.

Incidence densityNumber of cases/sum of times at risk

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Cohort study

Currently at risk

Cases exposed Ce

Start of study End of study

Currently at risk

Person years at riskof exposed (pyare)

Person years at risk of unexposed (pyaru)

Initiallyat

RiskNe

Initiallyat

RiskNu

Exposed population (E)

Unexposed population (U)Cases unexposed CU

Still at risk Ne - Ce

Still at risk Nu - Cu

TimeRodrigues L et al. Int J Epidemiol. 1990;19:205-13.

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Case-control studies

• Efficient for rare diseases

• Compare exposure in cases to sample of population– sampled from source population that gives rise to

cases– representative of exposure in source population

• Sampling independent of exposure status• Different control sampling schemes

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Cohort study Cases exposed

End of study

Exposed population (E)

Unexposed population (U)Cases unexposed

Still at risk

Still at risk

Cases

Sample of “non cases”

Traditional case-control design (exclusive)

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Traditional design

• Controls sampled from population still at risk at the end of the study period

• Disease odds ratio = exposure odds ratio• If disease is rare:

OR good estimate of risk ratio and rate ratio

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Cohort study Cases exposed

End of study

Exposed population (E)

Unexposed population (U)Cases unexposed

Still at risk

Still at risk

Cases

Sample of source population

Inclusive design: Case cohort study

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Case-cohort design

• Control group estimates the proportion of the total population that is exposed

• Controls selected from all individuals at risk at the start of the study– sampled regardless whether or not they will fall ill

• Case may also be selected as a control and vice versa -> kept in both groups

• OR estimates relative risk

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Cohort study Cases exposed

End of study

Exposed population (E)

Unexposed population (U)Cases unexposed

Still at risk

Still at risk

Cases

Sample of source populationStill at risk

Concurrent design: density case control

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Concurrent design: density case control

• Controls selected from those still at risk when a case occurs

• Control can later become a case • Not vice versa -> cases no longer at risk • Controls who later become cases kept in both groups• Controls represent person years at risk experience

among exposed and unexposed• Matched analysis on time of selection • OR estimates the rate ratio

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How to select controls to estimate the respective measure of association

Measure Design Formulation

Alternative

formulation

Controls to be sampled from

Risk ratio Inclusive Ce/Ne

Cu/Nu

Ce/Cu

Ne/Nu

Rate ratio Concurrent Ce/pyare

Cu/pyaru

Ce/Cu

pyare/pyaru

Odds ratio  Exclusive Ce/(Ne- Ce)

Cu/(Nu- Cu)

Ce/Cu

(Ne- Ce) /(Nu- Cu)

Rodrigues L et al. Int J Epidemiol. 1990;19:205-13.

Total study population

regardless of past or

future disease status

People currently at risk

People disease-free

throughout study period

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• Rare diseases: all give similar results

• Non-recurrent disease with high incidence-> Case cohort design (inclusive): OR relative Risk

• Recurrent common disease -> Density case control design (concurrent):

OR relative Rate

• Probability or effect of exposure changes along time -> Density case control design: OR relative Rate

• No need to quantify -> traditional design

What design and when?

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Relationship between OR and RR, according to the primary attack rate (AR)

Acknowledgements: Olivier le Polain, EPIET Cohort 15HPA London Epidemiology Unit, UK

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Cases detected by surveillance systems

• Non-random selection process:– Host factors (eg. asymptomatic infections)– Different health care seeking behaviour– Incomplete lab investigation– Incomplete reporting

• Differential recall – Between reported and not reported cases– Between cases and controls

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Case-to-case approach

• Same disease, different subtypes/clones:– Serotypes– Phage types– Antibiotic resistance patterns

• Controls = cases with non epidemic subtypes – from same source population – same susceptibility (underlying diseases)– included as cases if they had the outbreak strain– readily available

• Reduces selection AND recall bias• Food-exposure collected before status is known

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Two listeriosis outbreaks France, 1999-2000:two distinct PFGE patterns

0

1

2

3

4

5

6

7

8

9

10

Outbreak 2 (32 cases)

Outbreak 1 (10 cases)

October November December January February March 1999 2000

Cases

de Valk H et al. Am J Epidemiol 2001;154:944-50

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Listeriosis outbreak cases and sporadic cases distinguished by routine PFGE, France, 1999-2000

0

2

4

6

8

10

12

14Sporadic cases

Outbreak 2 (32 cases)

Outbreak 1 (10 cases)

October November December January February March 1999 2000

Cases

de Valk H et al. Am J Epidemiol 2001;154:944-50

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Case to case control study:controls selected among sporadic cases

listeriosis outbreak, France, 1999-2000

0

2

4

6

8

10

12

14 Other sporadic cases

Sporadic cases used as controls (N = 32)

Outbreak 2 (N = 32)

Outbreak 1 (N = 10)

October November December January February March 1999 2000

Cases

de Valk H et al. Am J Epidemiol 2001;154:944-50

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Outbreak of listeriosis, France, December 1999 - February 2000Results multivariable analysis

(29 cases, 32 controls)

Food consumed

Adjusted Odds ratio*

95% CI

p

Pork tongue in jelly 75.5 4.7 – 1216.0 0.002

Cooked ham 7.1 0.7 – 71.8 0.1

Pâté de campagne 8.9 1.7 – 46.1 0.009

*adjusted for underlying condition, pregnancy status and date of interview

de Valk H et al. Am J Epidemiol 2001;154:944-50

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Case-crossover design• Same person taken as its own control

-> No between-persons confounding

• Matched design: – Compare exposure in a risk period to one or more control periods

– Only pairs of discordant periods used in the analysis

• Acute diseases

• Exposure – must vary over time – short induction and transient effect

• sensitive to recall bias

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Reference period

“Wash out”

period

Currentperiod

Exposure

Study

Cases Matched pairs

1 Discordant 0, 1

2 Discordant 1, 0

3 Concordant 1, 1

4 Concordant 0,0

Case-crossover design

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Prolonged Salmonella Typhimurium outbreak, France Food exposures in the risk and control period

and matched OR for 17 nosocomial cases

Foods Riskperiod

Control period Matched

OR 95% C.I. Exposed (%) Exposed (%)

Veal 5 (29) 1 (6) 5 0,6 - 236,5 Pork 4 (23) 6 (35) 0,6 0,1 - 3,1 Hamburgers 13 (77) 5 (29) 5 1,1 - 46,9 Ham 6 (35) 5 (29) 1,5 0,2 - 17,9 Pâté 2 (12) 2 (12) 1 0,01 - 78,5 Chicken 2 (12) 3 (18) 1 0,01 - 78,5 Turkey 11 (65) 6 (35) 2,67 0,7 - 15,6 “Cordon bleu” 0 (0) 2 (12) undefined - Lamb sausages 2 (12) 0 (0) - Poultry sausages 2 (12) 0 (0) -

undefined

undefined

Haegebaert S et al. Epidemiol infect 2003;130,1-5

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Time trend in exposure: Between period confounding

Case-time control designORa/ORb = OR of exposure adjusted for time trend

Control period Risk period

onset

Cases:ORa for the exposure and the time trend

Case-time controls: ORb for the time trend

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Folic acid antagonists (FAA) in pregnancy and congenital cardiovascular defects (CCD)

• Case-crossover approach• Case: Woman who had a child with CCD (N=3870)• Exposure: FAA during 2nd & 3rd month of pregnancy• Control: Woman who had a child without CCD (N=8387)

OR=1.0 (0.5-2.0)

OR= 0.3 (0.2-0.6)

Case-time control OR = 1/0.3 = 2.9 (1.2-7.2)

-2 -1 1 2 3 4 5 6 7 8 9Cases:

-2 -1 1 2 3 4 5 6 7 8 9Controls:

Controlperiod

Riskperiod

Delivery

Hernandez-Diaz S. Am J Epidemiol 2003;158:385-391

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Conclusions

• If you do not need that OR estimates correctly the RR -> “traditional design”

• Otherwise, if you need OR RR-> identify the best design for each situation

• If it is difficult to find appropriate controls– Case to case– Case-crossover

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References • Rodrigues L et al. Int J Epidemiol 1990;19:205-13• Rothman KJ. Epidemiology: an introduction. Oxford University Press 2002, 73-93• Rothman KJ, Greenland S, Lash TL: Modern Epidemiology. 3. ed., Philadelphia:

Lippincott Williams & Wilkins, 2008. Chapter 8: Case-Control Studies, 111-127• McCarthy N, Giesecke J. 1 Int J Epidemiology 1999; 28, 764-8• de Valk H et al. Am J Epidemiol 2001;154:944-50• Haegebaert S et al. Epidemiol infect 2003;130,1-5• Hernandez-Diaz S et al. Am J Epidemiol 2003;158:385-391

Further Reading• Suissa S. The case-time-control design. Epidemiology 1995;6:248-253.• Greenland S. Epidemiology. 1996; 7231-239.• Mittleman, Maclure, Robins. Am J Epidemiol 1995;142;1:91-98. • Karagiannis I et.al. Epidemiol Infect 2010;138, 1726-1734