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Case-control designs in the study of common diseases & alternative designs JC Desenclos, F Simón, A Moren EPIET, Menorca, Spain, October 9, 2006.

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Presentation on theme: "Case-control designs in the study of common diseases & alternative designs JC Desenclos, F Simón, A Moren EPIET, Menorca, Spain, October 9, 2006."— Presentation transcript:

1 Case-control designs in the study of common diseases & alternative designs JC Desenclos, F Simón, A Moren EPIET, Menorca, Spain, October 9, 2006

2 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

3 Cohort populations origin of cases and controls Currently at risk Cases exposed C E Start of study End of study Currently at risk Person years at risk (pyrs E ) Occurrence of New case Person years at risk (pyrs U ) Initially at Risk N E Initially at Risk N u Exposed population (E) Unexposed population (U) Cases unexposed C U Still at risk N E - C E Still at risk N u - C u Rodrigues L et al. Int J Epidemiol. 1990;19:

4 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 C UUU EEE CNC CNC EU UE NC N C EU UE pyrsC C )CN(C )CN(C EEU UUE

5 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)

6 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

7 Traditional design (exclusive) Controls sampled from population still at risk at the end of the study period OR E of cases to controls = OR D of exposed to non exposed OR good estimate of relative risk and relative rate if disease is rare

8 Example: waterborne OB of gastro-enteritis Water consumption IllNot illTotal Yes No Total Attack rate = 0,29 RR = 3,04 Case (n = 50) Control (n = 50) Yes3719 No1331 OR = 4,64 (CI 95%: 1.8 – 11.9) Case (n = 50) Control (n = 50) Yes3724 No1326 OR = 3,08 (CI 95%: 1.2 – 7.8) Exclusive designCase cohort design (inclusive)

9 Which design is best? Rear diseases: similar results Common diseases: Non-recurrent disease with high incidence –Inclusive design (case-cohort): OR RR 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: OR RRate

10

11 Alternative designs « Case to Case » « Case - Crossover » « Case-time-control»

12 « Case to case design »

13 Two listeriosis outbreaks of 2 distinct PFGE patterns, France, October November December January February March Cases de Valk H et al. Am J Epidemiol 2001;154:944-50

14 Listeriosis outbreak and sporadic cases by routine PFGE pattern, France, October November December January February March Cases de Valk H et al. Am J Epidemiol 2001;154:944-50

15 Controls selected among sporadic cases for the study of outbreak 2, France, (Source: InVS-CNR) October November December January February March Cases de Valk H et al. Am J Epidemiol 2001;154:944-50

16 Food consumption multivariate analysis on 29 case-patients and 32 control-patients. Outbreak of listeriosis France, December February *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

17 « 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

18 « Case-Crossover design »

19 September October November December January Haegebaert S et al. Epidemiol infect 2003;130,1-5 Hospital and community OB of S. Typhimurium

20 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

21 « Case crossover » design applied to a prolonged S. Typhimurium outbreak Haegebaert S et al. Epidemiol infect 2003;130,1-5

22 Food exposures from menu information in the risk and control periods and matched OR for 17 nosocomial cases Foods Risk period Control period Matched OR 95% C.I. Exposed (%) Veal5 (29)1 (6) 5 0, ,5 Pork4 (23)6 (35) 0,6 0,1 - 3,1 Hamburgers13 (77)5 (29) 5 1,1 - 46,9 Ham6 (35)5 (29) 1,5 0,2 - 17,9 Pâté2 (12) 1 0, ,5 Chicken2 (12)3 (18) 1 0, ,5 Turkey11 (65)6 (35) 2,67 0,7 - 15,6 Cordon bleu0 (0)2 (12) undefined - Lamb sausages2 (12)0 (0) - Poultry sausages2 (12)0 (0) - undefined Haegebaert S et al. Epidemiol infect 2003;130,1-5

23 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»

24 «Case-time control design»

25 Between period confounding OR a /OR b = OR of exposure adjusted for time trend Cyclical variation of exposure Control periodRisk period onset Cases : OR a for the exposure and the time trend Controls: OR b for the time trend

26 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 2 nd & 3 rd month of pregnancy Case-crossover study for cases and controls independently OR=1.0 ( ) OR= 0.3 ( ) Case-time control OR = 1/0.3 = 2.9 ( ) Cases: Controls: OR crude =2.3 ( ) Control period Risk period Delivery Hernandez-Diaz S. Am J Epidemiol 2003;158:

27 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

28 Find the foot fitting the glass slipper

29 References 1.Rodrigues L et al. Int J Epidemiol 1990;19: de Valk H et al. Am J Epidemiol 2001;154: Haegebaert S et al. Epidemiol infect 2003;131, Hernandez-Diaz S et al. Am J Epidemiol 2003;158: Rothman KJ; Epidemiology: an introduction. Oxford University Press 2002, 73-93


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