Case-control designs in the study of common diseases & alternative designs JC Desenclos, F Simón, A...
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Transcript of Case-control designs in the study of common diseases & alternative designs JC Desenclos, F Simón, A...
Case-control designs in the study of common diseases
& alternative designs
JC Desenclos, F Simón, A Moren
EPIET, Menorca, Spain, October 9, 2006
Case-control studies
• Objective: compare exposure in cases and in population origin of cases– Sample of that population as controls– Representative as for the exposure of interest
• Random sampling, regardless exposure or disease status
• Meaning of OR differs according to different control sampling schemes
Cohort populations origin of cases and controls
Currently at risk
Cases exposed CE
Start of study End of study
Currently at risk
Person years at risk(pyrsE)
Occurrence of New case
Person years at risk (pyrsU)
Initiallyat
RiskNE
Initiallyat
RiskNu
Exposed population (E)
Unexposed population (U)Cases unexposed CU
Still at risk NE - CE
Still at risk Nu - Cu
Rodrigues L et al. Int J Epidemiol. 1990;19:205-13.
Origin of controls and measures of association
Inclusive (case-cohort)
Concurrent (density)
ExcIusive (traditional)No cases at the end
of the study period
People at risk when
the case appears
Total Study Cohort
origin of cases
Origin of Sampled Controls
Alternative Formulation
Formulation
Odds Ratio
Relative Rate
Density Incidence Ratio
Relative Risk
Cumulative
Incidence Ratio
Estimated
Measure of Association
U U
EE
NC
NC
UU
EE
pyrsC
pyrsC
UUU
EEE
CNC
CNC
EU
UE
NC
NC
EU
UE
pyrsC
pyrsC
)CN(C
)CN(C
EEU
UUE
Inclusive design (case-cohort): OR estimates RR
• Controls representative proportion of total population at risk at the beginning of the study period
including cases
• Sampling independent of the exposure and outcome
• A case may also be a control
• No need to asses disease status among controls
• Reasonable if source population is followed up for the same time period (ex: OB of gastro-enteritis)
Concurrent design: OR estimates Relative Rates
• Controls representative proportion of population at risk when the case appears (concurrent selection)
• Represent person-time at risk in exposed and unexposed
• A control can be a case later
• A person can be a control for several cases
• Matched analysis because of time matching
• Example: Prolonged OB of hepatitis C in a dialysis unit selecting 3 controls per case among those at risk of infection at the same time as the case occurs
Traditional design (exclusive)
• Controls sampled from population still at risk at the end of the study period
• ORE of cases to controls = ORD of exposed to non exposed
• OR good estimate of relative risk and relative rate if disease is rare
Example: waterborne OB of gastro-enteritis
Water consumption
Ill Not ill Total
Yes 148 188 336
No 54 319 373
Total 202 507 709
Attack rate = 0,29RR = 3,04
Case
(n = 50)
Control (n = 50)
Yes 37 19
No 13 31
OR = 4,64 (CI 95%: 1.8 – 11.9)
Case
(n = 50)
Control (n = 50)
Yes 37 24
No 13 26
OR = 3,08 (CI 95%: 1.2 – 7.8)
Exclusive design Case cohort design (inclusive)
Which design is best?
• Rear diseases: similar results
• Common diseases:
• Non-recurrent disease with high incidence– Inclusive design (case-cohort): ORRR
• Highly incident and recurrent disease or when probability of exposure changes along time or when the effect of exposure may change along time – Concurrent design: ORRRate
Alternative designs
• « Case to Case »
• « Case - Crossover »
• « Case-time-control»
« Case to case design »
Two listeriosis outbreaks of 2 distinct PFGE patterns, France, 1999-2000
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
Listeriosis outbreak and sporadic cases by routine PFGE pattern, 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
Controls selected among sporadic cases for the study of outbreak 2, France, 1999-2000
(Source: InVS-CNR)
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
Food consumption multivariate analysis on 29 case-patients and 32 control-patients. Outbreak of listeriosis
France, December 1999 - February 2000.
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 by logistic regression
de Valk H et al. Am J Epidemiol 2001;154:944-50
« Case-to-case » study design
• Controls = patient with non epidemic subtypes
– from same source population
– same susceptibility (underlying diseases)
– included as cases if they had the OB strain
– Information readily available
• Reduces the information (recall) bias
• Food-exposure collected before status is known
« Case-Crossover design »
September October November December January
Community cases
Hospital 1
Cases Hospital 2
8 Hospital 3
7 Hospital 4
6 Hospital 5
5 Nursing home4
3
2
1
37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 01 Week
Alert
Haegebaert S et al. Epidemiol infect 2003;130,1-5
Hospital and community OB of S. Typhimurium
Case-Crossover design
• Same person taken as control (matched design)• Compare exposure in a «risk period» to a prior «control
period» of the same duration • Matched analysis (discordant periods)• Evaluates exposures that
– vary from time to time within a person– triggering a short term effect, with abrupt onset
• Key issue : the definition of the risk period
« Case crossover » design applied to a prolonged S. Typhimurium outbreak
Control period
72 hours
“Wash out”period
48 hoursRisk period 72 hours
Discordant pair ( 1,0 )
Concordant pair ( 1,1 )
Discordant pair ( 0,1 )
Concordant pair ( 0,0 )
Exposure
Onset
Haegebaert S et al. Epidemiol infect 2003;130,1-5
Food exposures from menu information in the risk and control periods 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
Case-Crossover design
• For extended source outbreaks• No need of a control group• One to several control-periods per risk period• Controls for «between-persons» confounding• Very sensitive to recall bias unless data have been
collected prior to onset (administrative databases) • May be biased by time trend in exposure: between-
period confounding– «Case-time-control»
«Case-time control design»
Between period confounding
ORa/ORb = OR of exposure adjusted for time trend
Cyclical variation of exposure
Control period Risk period
onset
Cases : ORa for the exposure and the time trend
Controls: ORb for the time trend
Folic acid antagonists (FAA) in pregnancy and congenital cardiovascular defects (CCD)
• Case: Woman who had a child with CCD (N=3870)• Control: Woman who had a child without CCD (N=8387)
• Exposure: FAA during 2nd & 3rd month of pregnancy
• Case-crossover study for cases and controls independently
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:
ORcrude=2.3 (1.4-3.9)
Controlperiod
Riskperiod
Delivery
Hernandez-Diaz S. Am J Epidemiol 2003;158:385-391
Conclusions
• If you do not need that OR estimates correctly the RR then: “traditional design”
• Otherwise, if you need OR RR, identify the best design for each situation
• If you can not find or want to avoid controls– Case to case– Case-crossover
Find the foot fitting the glass slipper
References
1. Rodrigues L et al. Int J Epidemiol 1990;19:205-13
2. de Valk H et al. Am J Epidemiol 2001;154:944-50
3. Haegebaert S et al. Epidemiol infect 2003;131,809-813
4. Hernandez-Diaz S et al. Am J Epidemiol 2003;158:385-391
5. Rothman KJ; Epidemiology: an introduction. Oxford University Press 2002, 73-93