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Study designs. Alain Moren, Epiconcept, June 2006 Source: EPIET. Cohort study measuring risk. Denominator = those present at beginning Usually short duration = outbreak (attack rate). Cohort study measuring rate. Individuals contribute to different length of time
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Study designs Alain Moren, Epiconcept, June 2006 Source: EPIET
Cohort study measuring risk Denominator = those present at beginning Usually short duration = outbreak (attack rate)
Cohort study measuring rate Individuals contribute to different length of time Denominator = sum of times
Exposed population (E) Cases exposed CE Initially at Risk NE Person years at risk of exposed (pyarE) Currently at risk Still at risk NE - CE Unexposed population (U) Cases unexposed CU Initially at Risk Nu Person years at risk of unexposed (pyarU) Currently at risk Still at risk Nu - Cu End of study Start of study Cohort study Can we use a sample of the denominator instead of the entire denominator? Time Rodrigues L et al. Int J Epidemiol. 1990;19:205-13.
Source population IR RR Cases Pop. 30/100 10/100 E .3 3 30 100 = 3 Ref. .1 10 100 E Cases Sample E 30 10 30/10 10/10 = 3 10 10 E
Case control study design Source population Cases Controls Cases Pop. E E a P1 a b I1 = a / P1 c P0 c d E I0 = c /P0 E Cases Sample E a / (P1 / y) a P1 / y a / P1a / (P1 /y) ---------- = --------------- c / P0 c / (P0 /y) c / (P0 / y) c P0 / y E
Controls selection • Controls sampled to mirror the exposure experience in the source population • sampled from source population that gives rise to cases • representative of exposure in source population • Sampling independently of exposure status
Exposed population (E) Cases exposed CE Initially at Risk NE Person years at risk of exposed (pyarE) Currently at risk Still at risk NE - CE Unexposed population (U) Cases unexposed CU Initially at Risk Nu Person years at risk of unexposed (pyarU) Currently at risk Still at risk Nu - Cu Occurrence of New case End of study Start of study Cohort study Time Rodrigues L et al. Int J Epidemiol. 1990;19:205-13.
Exposed population (E) Cases exposed CE Initially at Risk NE Person years at risk of exposed (pyarE) Currently at risk Still at risk NE - CE Unexposed population (U) Cases unexposed CU Initially at Risk Nu Person years at risk of unexposed (pyarU) Currently at risk Still at risk Nu - Cu Occurrence of New case End of study Start of study Traditional case control study Cases and Sample of “non cases” Cases Controls E CE (NE-CE ) * f Non E CU (NU-CU ) * f Cohort study Time Rodrigues L et al. Int J Epidemiol. 1990;19:205-13.
Traditional (exclusive) designMeasure of effect = Odds ratio • Controls sampled from population still at risk at the end of the study period • OR good estimate of risk ratio and rate ratio if disease is rare
Exposed population (E) Cases exposed CE Initially at Risk NE Person years at risk of exposed (pyarE) Currently at risk Still at risk NE - CE Unexposed population (U) Cases unexposed CU Initially at Risk Nu Person years at risk of unexposed (pyarU) Currently at risk Still at risk Nu - Cu Occurrence of New case End of study Start of study Case cohort study Cases and Sample of source population Cases Controls E CE (NE) * f Non E CU (NU) * f Cohort study Time Rodrigues L et al. Int J Epidemiol. 1990;19:205-13.
Case-cohort design Measure of Risk ratio (relative risk) • Control group to estimate the proportion of the total population that is exposed: may include cases • In a fixed population controls selected from all individuals at risk at the start of the study • Controls sampled regardless whether or not they will have developed the disease • A person selected as a case may also be selected as a control and vice versa • They are kept in both groups • No need to document disease status among controls • Example: outbreak of gastro-enteritis with 30% attack rate
Density case control study Cases and Sample of source population still at risk Cases Controls E CE (NpyE) * f Non E CU (NpyU) * f Exposed population (E) Cases exposed CE Initially at Risk NE Person years at risk of exposed (pyarE) Currently at risk Still at risk NE - CE Unexposed population (U) Cases unexposed CU Initially at Risk Nu Person years at risk of unexposed (pyarU) Currently at risk Still at risk Nu - Cu Occurrence of New case End of study Start of study Cohort study Time Rodrigues L et al. Int J Epidemiol. 1990;19:205-13.
Density case control (concurrent) design OR estimates the rate ratio • Controls are selected concurrently from those still at risk when a case occur • A person selected as a control can later become a case • The opposite not possible: a case no longer at risk • A control who later becomes a case is kept in both groups • Controls represent person years at risk experience among exposed and unexposed • Match analysis on time of selection is necessary to give unbiased estimate of rate ratio
Exposed population (E) Cases exposed CE Initially at Risk NE Person years at risk of exposed (pyarE) Currently at risk Still at risk NE - CE Unexposed population (U) Cases unexposed CU Initially at Risk Nu Person years at risk of unexposed (pyarU) Currently at risk Still at risk Nu - Cu Occurrence of New case End of study Start of study Cohort study Time Rodrigues L et al. Int J Epidemiol. 1990;19:205-13.
Exposed population (E) Cases exposed CE Initially at Risk NE Person years at risk of exposed (pyarE) Currently at risk Still at risk NE - CE Unexposed population (U) Cases unexposed CU Initially at Risk Nu Person years at risk of unexposed (pyarU) Currently at risk Still at risk Nu - Cu Occurrence of New case Start of study End of study Cohort populations & measures of association Cohort design 3 measures of association
Exposed population (E) Cases exposed CE Initially at Risk NE Person years at risk of exposed (pyarE) Currently at risk Still at risk NE - CE Unexposed population (U) Cases unexposed CU Initially at Risk Nu Person years at risk of unexposed (pyarU) Currently at risk Still at risk Nu - Cu Occurrence of New case Start of study End of study Cohort populations & measures of association Measures of association
Exposed population (E) Cases exposed CE Initially at Risk NE Person years at risk of exposed (pyarE) Currently at risk Still at risk NE - CE Unexposed population (U) Cases unexposed CU Initially at Risk Nu Person years at risk of unexposed (pyarU) Currently at risk Still at risk Nu - Cu Numerator = ratio of exposed to non-exposed cases Denominator = ratio of exposed to unexposed: persons at risk at start of the study person years at risk for the duration of the study persons still disease free at the end of study Occurrence of New case Start of study End of study Cohort populations and estimate each measure of association
Exposed population (E) Cases exposed CE Initially at Risk NE Person years at risk Of exposed (pyarE) Currently at risk Still at risk NE - CE Unexposed population (U) Cases unexposed CU Initially at Risk Nu Person years at risk of unexposed (pyarU) Currently at risk Still at risk Nu - Cu Occurrence of New case Start of study End of study Cohort populations and controls selection for the OR to estimate each measure of association Numerator = ratio of exposed to non-exposed cases Denominators = ratio of exposed to non-exposed persons at risk at start of the study person years at risk for the duration of the study persons still disease free at the end of study
How to select controls to estimate the respective measure of association
Exposed population (E) Cases exposed CE Initially at Risk NE Person years at risk Of exposed (pyarE) Currently at risk Still at risk NE - CE Unexposed population (U) Cases unexposed CU Initially at Risk Nu Person years at risk of unexposed (pyarU) Currently at risk Still at risk Nu - Cu Case-cohort design Occurrence of New case Start of study End of study Density case control design Traditional case control design Cohort populations, control selection to estimate each measure of association & corresponding designs
What design and when? • Traditional case control - rare disease • Case cohort - frequent disease - same denominator over time - non recurrent outcome • Density case control - rare or frequent disease - exposure changes over time - non or recurrent outcome
OR in case-control studies: the rare disease assumption • Case control study very efficient for rare diseases • Initially used for testing significant differences in exposure without attempting to quantify the risk associated with exposure :« Statistically do more lung cancer patients have a history of smoking than controls ?» rather than « by how many times does smoking increase the risk of lung cancer ? » • Cornfield (1961): if disease is rare : OR ~ RR • Used more and more for common diseases • Miettinen (1976), Greenland (1981), Smith (1984) : if controls chosen appropriately, no rare disease assumption is needed for the OR to estimate the relative risk or rate !
Incidence of breast cancer after radiation Total Cases Non C. Rate RR E 28010 41 27969 14.6 1.9 E 19017 15 19002 7.9 Ref.
Incidence of breast cancer after radiation Random Total Cases Non C. Rate RR Contr. OR 28010 41 27969 14.6 1.9 280 1.9 19017 15 19002 7.9 Ref. 190 Ref.
Incidence of breast cancer after radiation Non Random Cases. Total Cases Non C. Rate RR Contr. OR Contr. OR 28010 41 27969 14.6 1.9 280 1.9 279 1.9 19017 15 19002 7.9 Ref. 190 Ref.190Ref.
Outbreak of food borne disease in a nursing home 100 residents, 40 cases Cohort Source Population Non cases Cases E 24 60 36 4 36 40 E RR = 6
Outbreak of food borne disease in a nursing home 100 residents, 40 cases Cohort Potential control groups Source Population Non cases Non cases Cases E 24 60 36 12 18 4 36 40 E RR = 6 OR = 13.5
Outbreak of food borne disease in a nursing home 100 residents, 40 cases Cohort Potential control groups Source Population Source Population Non cases Non cases Cases E 24 60 30 36 12 18 4 36 40 20 E RR = 6 OR = 13.5 OR =6
Rare disease assumption = wrong issue Issue = selection of controls
Alternative designs • « Case-to-case » • « Case-crossover »
« Case-to-caseapproach » Source: Jean Claude Desenclos, Jet De Valk
Two listeriosis outbreaks of 2 distinct PFGE patterns, France, 1999-2000 Cases October November December January February March 1999 2000 de Valk H et al. Am J Epidemiol 2001;154:944-50
Listeriosis outbreak cases and sporadic cases distinguished by routine PFGE, France, 1999-2000 Cases October November December January February March 1999 2000 de Valk H et al. Am J Epidemiol 2001;154:944-50
Controls selected among sporadic cases for the case to case control study, listeriosis outbreak 2, France, 1999-2000 (Source: InVS-CNR) Cases October November December January February March 1999 2000 de Valk H et al. Am J Epidemiol 2001;154:944-50
Food consumption of case-patients and control-subjects, multivariate analysis on 29 case-patients and 32 control-subjects. Outbreak of listeriosis, France, December 1999 - February 2000. *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 » control study • Possible if disease can be classified in subgroups that have specific risk factors • May be the case for infectious agents subtypes? • 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 the information (recall) bias • Food-exposure collected before status is known
The case-crossover design • Same person taken as its own control (matched design) • Compare exposure in a « risk period » to a prior « control period » of the same duration • No control group needed • Only pairs of period discordant for the exposure of interest used in the analysis • Acute diseases & exposures that change overtime • Transient exposures (drug adverse events…) • Key issue : the definition of the risk period
Exposure Onset “Wash out” Reference period Current period period Cases Matched pairs 1 Discordant 0, 1 2 Discordant 1, 0 3 Concordant 1, 1 4 Concordant 0,0
Exposure Onset Discordant pair ( 0,1 ) Discordant pair ( 1,0) Concordant pair ( 1,1 ) Concordant pair ( 0,0 ) “Wash out” Control period period Risk period 72 hours 72 hours 48 hours « Case crossover » design applied to a prolonged Salmonella Typhimurium outbreak Haegebaert S et al. Epidemiol infect 2003;130,1-5
Food exposures from menu information in the risk and control period and matched OR for 17 nosocomial cases Risk Control Matched Foods period period 95% C.I. OR 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 undefined Lamb sausages 2 (12) 0 (0) - undefined Poultry sausages 2 (12) 0 (0) - Haegebaert S et al. Epidemiol infect 2003;130,1-5
Case-crossover design • No need of a control group • One to several control-periods per risk period • Controls for « between-persons » confounding • Need of data collected prior to onset (administrative source), • If exposure collected by interview then very sensitive to recall bias • May be biased by time trend in exposure: between-period confounding • « Case-time-control design »
References • Rodrigues L et al. Int J Epidemiol 1990;19:205-13 • 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 • Rothman KJ; Epidemiology: an introduction. Oxford University Press 2002, 73-93 • Suisa S. The case-time-control design. Epidemioogy. 1995;6:248-253. • Greenland S. Confounding and exposure trends in Case-cross-over and case-time-control designs. Epidemiology. 1996; 7231-239. • Mittleman, Maclure, Robins. Control sampling strategies for case cross-over studies: An assessment or relative effectiveness. A J Epidemiol. 142;1:91-98.
Exposed population (E) Cases exposed CE Initially at Risk NE Person years at risk of exposed (pyarE) Currently at risk Still at risk NE - CE Unexposed population (U) Cases unexposed CU Initially at Risk Nu Person years at risk of unexposed (pyarU) Currently at risk Still at risk Nu - Cu Occurrence of New case End of study Start of study Cohort study Time Rodrigues L et al. Int J Epidemiol. 1990;19:205-13.
Investigation Mandatory notification InVS Clinicians DDASS Routine extended food questionnaire Cluster detection >3 isolates with same PFGE pattern in 10 weeks Lm human isolates NRC Laboratories Routine ongoing PFGE typing Surveillance of human listeriosis, France • Timely detection of clusters • Food history readily available when cluster recognised • “Case to case” case-control studies