1. Instructor Resource Chapter 11 Copyright © Scott B. Patten, 2015. Permission granted for classroom use with Epidemiology for Canadian Students: Principles, Methods & Critical Appraisal (Edmonton: Brush Education Inc. www.brusheducation.ca).

2. Chapter 11. Case-control studies

3. Objectives Define case-control studies. Explain how to interpret measures of association calculated from case-control data. Describe recall bias. Describe the rare disease assumption. Distinguish between induction and latency periods for disease, and describe the dynamic of component causes of disease. Define primary, secondary, and tertiary prevention. List strengths and weaknesses of case-control studies.

4. What is a case-control study? It is a type of analytic study: it usually has analytic goals. Participants are selected based on their disease status. Participants include: cases (who have the disease under investigation) controls (who do not) Exposure is assessed retrospectively.

5. 2 x 2 table for case-control studies CasesControls Exposedab Nonexposedcd Totaln cases n controls

6. 2 x 2 table for case-control studies (continued)

7. A measure of association for case-control studies

8. Odds ratios Recall that a prevalence odds ratio could be calculated from cross-sectional data. The formula was the same. However, as the case-control design usually has analytical goals, incidence is of more interest. Case-control studies rarely use prevalent cases. When the cases are incident cases, the estimated odds ratio is an incidence odds ratio.

9. Advantages of case-control studies The main advantage of the case-control design is its efficiency. The design is efficient because selection of cases can be accomplished flexibly and the control group is usually only a small subset of the analogous group in the general population. Therefore, a relatively small investment of research resources can produce a precise estimate.

10. Case-control studies Links to examples: http://www.ncbi.nlm.nih.gov/pubmed/8059766 http://www.ncbi.nlm.nih.gov/pubmed/15364185 http://www.ncbi.nlm.nih.gov/pubmed/23164221 http://www.ncbi.nlm.nih.gov/pubmed/25208536 http://www.ncbi.nlm.nih.gov/pubmed/21033532

11. Selection bias in case-control studies Selection bias is a major methodological concern for case-control studies. Selection bias results if selection of cases and controls depends on exposure in some way that is not equivalent between the 2 groups. It is easiest to be confident that selection bias has not occurred if the selection of cases and controls does not depend in any way on exposure.

12. Berkson’s bias This is bias that arises when selection of cases and controls occurs in a hospital setting. The probability of hospitalization is often related to exposure in a way that differs in cases and controls.

13. Misclassification bias in case- control studies Since the target of estimation is a more complex parameter (an odds ratio rather than simply odds, a frequency, or a rate), this is a more difficult issue than it was in prevalence or incidence studies. The problem becomes easier if you consider the numerator (odds of exposure in cases) and the denominator (odds of exposure in controls) separately. If the numerator is inflated, the estimate of the odds ratio will be too high. If the denominator is inflated, the estimate of the odds ratio will be too low.

14. Nondifferential misclassification of exposure Exposure assessment is prone to error in case- control studies because it is retrospective. The measure of exposure can have low sensitivity and/or low specificity. Low sensitivity produces false negatives. Low specificity produces false positives. If the error rates are the same in cases and controls, the misclassification is nondifferential.

15. Differential misclassification of exposure If the error rates in classification of exposure are different in the cases and controls, the misclassification is differential. A classical type of differential misclassification bias in case-control studies is recall bias.

16. Recall bias Imagine a study of drug exposures during pregnancy (exposure) as a risk factor for birth defects (outcome). Since mothers of babies with birth defects are likely to reflect more deeply about their pregnancy, they may have more accurate recall of past drug exposures. What effect would this have on the odds ratio (OR)?

17. Recall bias (continued) The sensitivity for exposure in the controls is lower than in the cases. Therefore, the odds of exposure in the controls (denominator of the OR) will be too small. This will lead to an overestimation of the OR.

18. Nondifferential misclassification bias What if the sensitivity for assessment of exposure was the same (nondifferential) in cases and controls. The direction of bias is towards the null value for the OR (which is 1).

19. The rare disease assumption Imagine the classic 2 x 2 table. Note that when a disease is rare, a and b are small and the ratio of the 2 odds approximates the ratio of the analogous 2 proportions. DiseaseNo Disease Exposedab Nonexposedcd

20. The rare disease assumption (continued) When the disease is rare…. DiseaseNo Disease Exposedab Nonexposedcd

21. The rare disease assumption (continued) (and) When the disease is rare…. DiseaseNo Disease Exposedab Nonexposedcd

22. Induction period This is the period of time between exposure to a risk factor and the initiation of a disease mechanism. An advantage of the case-control design is that it can assess associations characterized by long induction periods.

23. Latency period Latent means “hidden.” A latency period is the time between the initiation of a disease and its emergence as a clinically evident entity.

24. Primary, secondary, and tertiary prevention Primary prevention: preventing the occurrence of disease by eliminating a risk factor or its effects (occurs in the induction phase). Secondary prevention: improving outcomes through earlier detection (in the latency phase). Tertiary prevention: diminishing the impact of a disease (after the disease has become a clinical entity).

25. Strengths of the case-control study design efficiency fit with rare diseases fit with long induction and latency periods ability to examine multiple exposures

26. Weaknesses of the case- control study design vulnerable to selection and misclassification bias not a good fit for rare exposures limited to estimating odds ratios (cannot, for example, estimate incidence. temporality issues: in studies of prevalent cases, the timing of exposure and disease may be unclear

27. End