Case-Control study Selection of Cases

1. Case-Control studySelection of Cases • Diagnostic criteria: specific to each investigation; homogeneous group of cases • The source of cases: primary study base secondary or case-defined study base • Incident or prevalent case

2. Case-Control studyPrinciples, control selection • Should be selected from the samepopulation that gave rise to the cases • Controls should be selected independently of their exposure status; If sampling rate, the same for exposed and unexposed, is known, incidence rate can be calculated

3. Case-Control studySelection of Controls • Sources 1: a population explicitly defined • Methods: 1. No sampling: total population 2. Random and systematic sampling 3. Paired sampling

4. CasCase-Control study • When a list of all potential controls is not available • Random digit dialing (RDD) Sampling of households based on random selection of telephone numbers; matched to cases on area code and prefix 2. Paired Sampling Primary or *Secondary study base Alternative to RDD or RDD not realistic Implicit, indirect matching

5. Case-Control studyPaired sampling Objective • to provide a sampling scheme for control selection that minimizes subjectivity and arbitrariness during the process Individuals are selected by virtue of some defined temporal or geographic relationship to the case Example: • Next patient admitted after the case, the person living in the nearest residence to that of case, the student next to the case in an alphabetical class listing

6. Case-Control studyMatching; pre-specified distribution • Explicitly identified matching variables and values • Paired sampling: the next person admitted who satisfied the defined criteria • To select controls identical to the cases with respect to one or more potentially confounding factors, with certain homogeneous levels

7. Confounding • Rates: Counterfactual Substitution/Reference group • If both rates are not equal, before-after rate difference is confounded for the causal rate difference or ratio

8. Confoundingdefinition • A distortion of an exposure-outcome association brought about by the association of another factor with both outcome and exposure. • The definition of confounding involves a definition of the study hypothesis • Two associations, One condition

10. Criteria for a confounding facCriteria for a confounding factor • A confounding factor must be a risk factor for the disease: must be predictive of disease occurrence apart from its association from exposure • i.e. predictive among unexposed or reference group

11. Criteria for a confounding facCriteria for a confounding factor 2. A confounding factor must be associated with the exposure under study in the source population (the population at risk from which the cases derived) 3. A confounding factor must not be affected by the exposure or the disease Cannot be an intermediate step in the causal pathway Should be an extraneous risk factor

12. Standardization1 *Standard The set of weight that is used to taking weight average **Standardized Adjustment has been made for the effects of one or more potential confounding factors by calculating a weighted average of category- specific rates

13. Standardization • Direct a standard population with a known age distribution is selected comparable, a directly standardized rate can be compared with any other rate standardized to the same population • Indirect a set of age-specific standard rates is selected

16. StandardizaStandardizationStandardized Mortality Ratio; SMR • Indirect, Rates from: 1. non-exposed group from within the same occupational setting 2. A general population, e.g., TW male aged 20-59 years • Standardized mortality ratio = O/E

17. SMR • O: the number of cases observed in the study group • E = T1I1*+T2I2* +------ • It is generally not equal to the number of cases one should expect in the study group if it had experienced the rates of the reference population; Alteration of the person-time rate usually alters the distribution of person-time in the study group *Assumption:

19. SMR • Excess risk among those exposed • Using general population as standard, the magnitude is less than what has been estimated by relative risk; underestimate the increased or decreased risk • Should not be directly compared to evaluate the relative effect of different levels of exposure • The only valid comparison of an indirectly standardized rate is with the population from which the standardized rates derived

21. Causal relationship • Study design, selection of study subjects: external validity to be reasonable • Do the results support a causal relationship? • Observation bias confounding chance causal relationship Fall 2006 NCKU

22. Observation bias • Relevant to the measurement of the dependent variable in the study • In a cohort study: outcome • In a case-control study: exposure • The key issue is the relationship between the true value of the factor being assessed and the value of the variable chosen to represent the factor in the study

23. Non-differential error/bias • All methods of measurement will have a degree of error which is a function of the measurement used • However, the inaccuracy is similar in the different groups of subjects being compared

24. The effect of non-differential error • Make the observed association, e.g., the relative risk estimate, closer to the null value that is the true situation • The exposure variable measured, a very inaccurate estimate of the true biological factor concerned, because it is an extremely indirect measurement • The closer we come to the biological causal factor, the higher the relative risk will become • e.g., smoking: Yes/No, package-yr, DNA adduct

25. Bias, differential • Inaccuracy which is different in size or direction in one of the groups under study than in others • The effect: bias can influence the results of a study in any direction • The most important sources of bias are variation in the subject’s response to the method of assessment, and variation in the observer’s response

27. Bias in case-control study1Selection • Selection bias can occur whenever the inclusion of cases or controls into the study depends in some way on the exposure of interest, since exposure and disease have both occurred • e.g., Milk drinking and Salmonella infection