1. Chapter 6 Analytic Epidemiology: Types of Study Designs

2. Learning Objectives State three ways in which study designs differ from one another Describe case-control, ecologic, and cohort studies Calculate an odds ratio, relative risk, and attributable risk State appropriate uses of randomized controlled trials and quasi-experimental designs

3. Introduction Major categories of analytic designs: – Case-control – Cohort – Ecologic – Intervention studies

4. Importance of Analytic Studies Lead to the prevention of disease Assist in creation of quantitative evaluations of intervention programs Aid in determining safety and efficacy of new drugs and other procedures

5. Two Categories of Analytic Studies Observational design: investigator – Does not have control over the exposure factor – Usually is unable to assign subjects randomly to study conditions Experimental design: investigator – Controls who is exposed to a factor of interest – Assigns subjects randomly to study groups

6. Characteristics of Study Designs Who manipulates the exposure factor? How many observations are made? What is the directionality of exposure? What are the methods of data collection? What is the timing of data collection? What is the unit of observation? How available are the study subjects?

7. Observational Analytic Studies Ecologic Case-control Cohort

8. Ecologic Studies “…a study in which the units of analysis are populations or groups of people rather than individuals.” Examples of groups are nations, states, census tracts, counties. May be used when individual measurements are not available, but group-level data can be obtained.

9. Ecologic Studies (cont.) Ecologic comparison study: involves an assessment of the association between exposure rates and disease rates during the same time period. Ecologic correlation: an association between two variables (exposure and outcome) measured at the group level.

10. Ecologic (Ecological) Fallacy “An erroneous inference that may occur because an association observed between variables on an aggregate level does not necessarily represent or reflect the association that exists at an individual level;…”

11. Example of Ecologic Fallacy Worldwide, richer cities have higher rates of coronary heart disease (CHD) than poorer cities. It would be incorrect to infer that richer individuals have higher rates of CHD than poorer individuals. In fact, in industrialized cities poorer people have higher CHD rates than richer ones.

12. Ecologic Studies (cont.) Advantages May provide information about the context of health. Can be performed when individual-level measurements are not available. Can be conducted rapidly and with minimal resources. Disadvantages Ecologic fallacy Imprecise measurement of exposure

13. Case-Control Studies Subjects are defined on the basis of the presence or absence of an outcome of interest. Cases are those individuals who have the outcome or disease of interest, whereas the controls do not.

14. Diagram of a case-control study. Modified from Cahn MA, Auston I, Selden CR, Pomerantz KL. Introduction to HSR, May 23, 1998. National Information Center on Health Services Research and Health Care Technology (NICHSR), National Library of Medicine. 1998. Available at: http://www.nlm.nih.gov/nichsr/pres/mla98/cahn/sld036.htm. Accessed July 30, 2008.

15. Case-Control Studies (cont.) Matched case-control study is one in which the cases and controls have been matched according to one or more criteria such as sex, age, race, or other variables. – Matching aids in controlling confounding.

16. Odds Ratio The odds ratio (OR) is a measure of the association between frequency of exposure and frequency of outcome used in case-control studies. See next slide for method of labeling cells in a case-control study. Refer to next slide and note that the formula for OR is: OR = (AD)/(BC)

17. Fourfold Table: Case-Control Study

18. Odds Ratio (cont.) As shown in the fourfold table: – The odds in favor of exposure among the disease group (the cases) = A/C. – The odds in favor of exposure among the no- disease group (the controls) = B/D. – The OR is defined as (A/C) ÷ (B/D). – The OR can be expressed as AD/BC.

19. Sample Calculation

20. Interpretation of an Odds Ratio (OR) If the observed OR is not due to chance (is statistically significant), then: – An OR ˃ 1 suggests a positive association between exposure and disease. – An OR of 2.1 (about 2) suggests that the odds of disease are about two times higher among the exposed than among the nonexposed. – An OR <1 indicates that the exposure might be a protective factor. An OR = 1.0 indicates no association between exposure and outcome (not statistically significant).

21. Case-Control Studies (cont.) Advantages Can be used to study low- prevalence conditions – Having a disease is a criterion for being selected as a case. Relatively quick and easy to complete Usually inexpensive Involve smaller number of subjects Disadvantages Measurement of exposure may be inaccurate Representativeness of cases and controls may be unknown Provide indirect estimates of risk The temporal relationship between exposure factor and outcome cannot always be ascertained.

22. Cohort Studies A cohort is defined as a population group, or subset thereof (distinguished by a common characteristic), that is followed over a period of time. Examples: – Birth or age cohort – Work cohort – School/educational cohort

23. Types of Cohort Studies Prospective cohort study Retrospective cohort study Historical prospective cohort study

24. Prospective Cohort Study Subjects are classified according to their exposure to a factor of interest and then are observed over time to document the occurrence of new cases (incidence) of disease or other health events.

25. Diagram of a prospective cohort study Source: Modified from Cahn MA, Auston I, Selden CR, Pomerantz KL. Introduction to HSR, May 23, 1998. National Information Center on Health Services Research and Health Care Technology (NICHSR), National Library of Medicine. 1998. Available at: http://www.nlm.nih.gov/nichsr/pres/mla98/cahn/sld034.htm. Accessed July 30, 2008.

26. Retrospective Cohort Study Makes use of historical data to determine exposure level at some baseline in the past Follow-up for subsequent occurrences of disease between baseline and present is performed. Example: a study of mortality among an occupational cohort of shipyard workers employed at a specific naval yard during a defined time interval in the past.

27. Historical Prospective Cohort Study Combines retrospective and prospective approaches

28. Measure of Association Used in Cohort Studies Relative risk (RR): the ratio of the incidence rate of a disease or health outcome in an exposed group to the incidence rate of the disease or condition in a nonexposed group.

29. Relative Risk (RR) Relative risk = Incidence rate in the exposed Incidence rate in the nonexposed

30. Fourfold Table Used to Calculate a Relative Risk Disease Status Yes No Total Exposure Yes A B A+B Status No C D C+D

31. Relative Risk (RR) (cont.) From the fourfold table: – Total number of subjects in the exposure group (exposure status is Yes) = A + B – Total number of subjects in the nonexposed group (exposure status is No) = C + D – Incidence of disease in the exposed group = A/(A + B) – Incidence of disease in the nonexposed group = C/(C + D) – The relative risk (RR) = [A/(A + B)] ÷ [C/(C + D)]

32. Sample Calculation Exposed to solvents Liver Cancer No Liver Cancer Total YesA = 3B = 104A + B = 107 NoC = 2D = 601C + D = 603 Relative Risk = (3/107) ÷(2/603) =8.43

33. Difference in Rates (Risks) Attributable risk, in a cohort study, refers to the difference between the incidence rate of a disease in the exposed group and the incidence rate in the nonexposed group. From the previous example, the attributable risk per thousand is: – [(3/107) X 1,000] – [(2/603) X 1,000] = 28.03 – 3.32 = 24.71 per 1,000

34. Population Risk Difference Incidence in the total population − incidence in the nonexposed segment. Calculation example. Suppose that: – Annual lung cancer incidence among men in the population is 79.4 per 100,000. – Annual lung cancer incidence among nonsmoking men is 28.0 per 100,000. – The population risk difference is (79.4 − 28.0), or 51.4 per 100,000 men.

35. Cohort Studies (cont.) Advantages Permit direct observation of risk Exposure factor is well defined Can study exposures that are uncommon in the population The temporal relationship between factor and outcome is known Disadvantages Expensive and time consuming Complicated and difficult to carry out Subjects may be lost to follow-up during the course of the study Exposures can be misclassified

36. Experimental Studies In epidemiology, experimental studies are implemented as intervention studies. An intervention study is “An investigation involving intentional change in some aspect of the status of the subjects,…” – Randomized control trial (RCT) – Quasi-experimental design

37. Randomized Controlled Trial Randomized controlled trial (RCT): “…subjects in a population are randomly allocated into groups, usually called study and control groups, to receive or not to receive an experimental preventive or therapeutic procedure, maneuver, or intervention….”

38. Randomized Controlled Trial (cont.) A prophylactic trial is designed to test preventive measures. Therapeutic trials evaluate new treatment methods. Clinical trial refers to “A research activity that involves the administration of a test regimen to humans to evaluate its efficacy and safety….” In a crossover design, participants may be switched between treatment groups.

39. Diagram of a randomized controlled trial Source: Modified from Cahn MA, Auston I, Selden CR, Pomerantz KL. Introduction to HSR, May 23, 1998. National Information Center on Health Services Research and Health Care Technology (NICHSR), National Library of Medicine. 1998. Available at: http://www.nlm.nih.gov/nichsr/pres/mla98/cahn/sld038.htm and http://www.nlm.nih.gov/nichsr/pres/mla98/cahn/sld039.htm. Accessed July 30, 2008.

40. Community Intervention A community intervention (community trial) is an intervention designed for the purpose of educational and behavioral changes at the population level. – Most community interventions use quasi- experimental designs.

41. Quasi-experimental Study A quasi-experimental study is a type of research in which the investigator manipulates the study factor but does not assign individual subjects randomly to the exposed and nonexposed groups.

42. Program Evaluation Program evaluation is used to determine whether the program meets stated goals and is justified economically.

43. Challenges to the Validity of Study Designs External validity Sampling error Internal validity Bias

44. External Validity Refers to one’s ability to generalize from the results of the study to an external population – A convenience sample (grab bag sample) may not demonstrate external validity. – Random samples are more likely to demonstrate external validity than convenience samples.

45. Sampling Error A type of error that arises when values (statistics) obtained for a sample differ from the values (parameters) of the parent population

46. Internal Validity Refers to the degree to which the study has used methodologically sound procedures

47. Bias in Epidemiologic Studies Epidemiologic studies may be impacted by bias, which is “Systematic deviation of results or inferences from truth….” Types of bias include the following: – Hawthorne effect – Recall bias – Selection bias – Healthy worker effect – Confounding

48. Types of Bias Hawthorne effect: participants’ behavioral changes as a result of their knowledge of being in a study Recall bias: Cases may remember an exposure more clearly than controls. Selection bias: “Distortions that result from procedures used to select subjects and from factors that influence participation in the study….”

49. Types of Bias (cont.) Healthy worker effect: the “observation that employed populations tend to have a lower mortality experience than the general population.” Confounding: “…the distortion of a measure of the effect of an exposure on an outcome due to the association of the exposure with other factors that influence the occurrence of the outcome.” Example: age as a confounder.

50. Conclusion Descriptive and analytic approaches – One of the most common approaches of epidemiologic research is the use of observational study designs. Examples of observational analytic studies include: – Ecologic studies – Case-control studies – Cohort studies Experimental designs (intervention studies) include: – Randomized control trials (RCTs) – Quasi-experimental designs