Introduction to Clinical Research Design

1. Introduction to Clinical Research Design Lee E. Morrow, MD, MS Assistant Professor of Medicine Creighton University

2. Descriptive Describe incidence of outcomes over time Case Reports Case Series Registries Cross Sections Analytic Analyze associations between predictors and outcomes Observational Cohort Studies Case-Control Studies Experimental Clinical Trials Clinical Research Designs

3. Descriptive Studies • Often a first step in research • Doesn’t always have a specific hypothesis to be tested • Causality usually cannot be determined • Examples: • Case Reports/Series • Registries • Cross Sectional Studies

4. Case Reports/Series • Definition: A single/series of patients with or without a disease or exposure of interest for whom data are collected in any fashion • Sources: Clinics, hospitals, disease registries • Limitations: Not randomly selected, bias due to selection factors inherent in the source, not representative of the population from which they are selected

5. Case Reports/Series • Benefits: Easy to do, useful for exploring relationships and/or generating hypotheses • Key Point: Associations seen in case series are highly likely to be biased and frequently do NOT hold up in more rigorous studies

6. Cross-Sectional Studies • Definition: A study based on a sample selected at one point or period in time Risk Factor Present Risk Factor Absent Population

7. Cross-Sectional Studies • Definition: A study based on a sample selected at one point or period in time Risk Factor Present Risk Factor Absent Sample Population

8. Cross-Sectional Studies • Definition: A study based on a sample selected at one point or period in time Disease No Disease Risk Factor Present Disease No Disease Risk Factor Absent Sample Population

9. Cross-Sectional Studies • If looking at a specified moment in time: point prevalence • If looking at a specified moment in time plus all new cases during the specified time period: period prevalence • If looking only at new cases during the specified time period: incidence

10. Cross-Sectional Studies Which cases are included in 7/1/02 point prevalence? Which cases are included in 7/1/02-6/30/03 period prevalence? Which cases are included in incidence? 1 2 3 4 5 6 7 8 9 7/1/02 6/30/03

11. Cross-Sectional Studies 7/1/02 point prevalence cases: 1, 2, 8 7/1/02-6/30/03 period prevalence cases: 1, 2, 3, 4, 6, 8, 9 incidence cases: 3, 4, 6, 9 1 2 3 4 5 6 7 8 9 7/1/02 6/30/03

12. Cross-Sectional Studies Assuming N=100, calculate the 7/1/02 point prevalence. Calculate the 7/1/02-6/30/03 period prevalence. Calculate the incidence rate. 1 2 3 4 5 6 7 8 9 7/1/02 6/30/03

13. Cross-Sectional Studies 7/1/02 point prevalence: 3% 7/1/02-6/30/03 period prevalence: 7% incidence rate: 4% 1 2 3 4 5 6 7 8 9 7/1/02 6/30/03

14. Cross-Sectional Studies • Limitations: • Exposure and outcome are assessed at the same time by the investigator (no temporality) • Sample selection is not based on exposure or outcome • Prevalence estimate is affected by duration of disease: disease with longer duration is more likely to be detected • Must consider “at risk” population only

15. Cross-Sectional Studies • Benefits • Easy • Cheap • Gives a “snap-shot” of exposure and outcome • Good for hypothesis generation

16. Analytic Studies • Involve a specific hypothesis that can be tested using a statistical model • Involve assessing exposures as a predictor of outcomes • Examples: • Observational: Cohort Studies, Case-Control Studies • Experimental: Clinical Trials

17. Cohort Studies • Involve following a group (cohort) of subjects over time • Usually analytic but may be descriptive • Was a treatment specifically initiated for evaluation? • No: Simple Cohort Study • Yes: Clinical Trial • Randomized • Non-Randomized

18. Cohort Studies • Prospective Cohort Studies • Investigator defines sample and predictor variables before any outcomes have occurred • Retrospective Cohort Studies • Investigator defines sample and collects information about predictor variables after the outcomes have occurred

19. Prospective Cohort Studies Is a given Risk Factor associated with a given Disease? The Present Risk Factor Present Risk Factor Absent Population

20. Prospective Cohort Studies Is a given Risk Factor associated with a given Disease? The Present Risk Factor Present Risk Factor Absent Sample Population

21. Prospective Cohort Studies Is a given Risk Factor associated with a given Disease? The Present The Future Risk Factor Present Disease No Disease Disease No Disease Risk Factor Absent Sample Population

22. Retrospective Cohort Studies Is a given Risk Factor associated with a given Disease? The Present Disease No Disease Disease No Disease

23. Retrospective Cohort Studies Is a given Risk Factor associated with a given Disease? The Past The Present Risk Factor Present Disease No Disease Disease No Disease Risk Factor Absent Sample Population

24. Cohort Studies in General • Strengths • Powerful strategy for directly measuring the incidence of a disease • Can examine multiple outcomes and multiple exposures • Easier to establish temporal relationship: improves inference for causality

25. Cohort Studies in General • Weaknesses • Attrition of the sample • Level of exposure may change over time • Inability to identify presence of confounders and effect modifiers • Susceptible to follow-up bias: there may be a difference in the exposure-disease relationship for those who follow-up and those who do not • Cost and feasibility vs. representativeness: general population sample vs. restricted cohort sample

26. Prospective Cohort Studies • Strengths • Allows opportunity for complete and accurate measurement of risk factors • Uniquely valuable for studying the antecedents of fatal diseases • End-point unknown: can take a long time for sufficient number of cases to develop • Observer bias • Weaknesses • Expensive and inefficient for rare diseases • Observer bias

27. Retrospective Cohort Studies • Strengths • Much less costly and time consuming • Observer bias • Weaknesses • Less control over the nature and quality of predictor variable data collected • Incomplete data sets • Observer bias, recall bias

28. Risk Ratios in Cohort Studies • The Risk Ratio (RR) is the ratio of the incidence of disease in exposed persons to the incidence of disease in non-exposed persons Cumulative Incidence in Exposed RR = Cumulative Incidence in Non-Exposed

29. Risk Ratios in Cohort Studies • RR calculation requires incidence data • Used in cohort and intervention studies • Not used in Case-Control Diseased - + a b + a/(a+b) RR = Exposed c/(c+d) c - d

30. Risk Ratios in Cohort Studies • Is a measure of the strength of association between exposure and outcome: does not imply causality…

31. Case-Control Studies • Compares people with disease (cases) to people without disease (controls) with respect to history of exposure • If exposure is different between cases and controls, an association exists between exposure and disease • Cases must represent the population of all cases while controls must represent the population of all non-diseased

32. Case-Control Studies The Present Population with Disease Population without Disease

33. Case-Control Studies The Present Population with Disease Risk Factor Present Risk Factor Absent Population without Disease

34. Case-Control Studies The Present Select Cases Population with Disease Risk Factor Present Risk Factor Absent Select Controls Population without Disease

35. Case-Control Studies The Present The Past D+/RF+ D+/RF- Population with Disease Risk Factor Present Risk Factor Absent Population without Disease D-/RF+ D-/RF-

36. Case-Control Studies • Strengths • Shorter study period is possible • Rare diseases are more easily studied • Less expensive • Multiple risk factors may be studied • Particularly useful for studying new diseases about which little is known

37. Case-Control Studies • Weaknesses • Choice of appropriate controls is usually very difficult (selection bias) • Cases and controls do not usually come from the same population (selection bias) • May be difficult to assess whether exposure preceded disease (recall bias) • Incidence rates cannot be calculated directly

38. Odds Ratios in Case-Control Studies • The Odds Ratio (OR) provides an estimate of the Risk Ratio (RR) for Case-Control studies • OR is a good estimate of the RR if the disease is “rare” (incidence <10% per year in the population) • Is a measure of the strength of association between exposure and outcome: does not imply causality…

39. Nested Case-Control Studies • Select disease cases from within a cohort study • Controls are selected from non-diseased cases within the same cohort, within the same time period as the cases develop • If controls are randomly selected from within the cohort (i.e.: includes diseased subjects in the case group and the control group) it is a Case-Cohort Study

40. A Few Words About Controls • The most difficult aspect of Case-Control Studies is selecting appropriate controls • Matching is often used to eliminate the effect of potential confounders • Technically speaking, matching reduces the variance of the OR! • Matching is difficult to do correctly and may paradoxically worsen analysis problems if done incorrectly • Impossible to match for unknown confounders

41. Clinical Trials • Definition: A clinical trial is a scientific experiment involving human subjects which is designed to evaluate the effects of intervention(s) against a particular disease in order to elucidate the most appropriate care for future subjects

42. Clinical Trials • Controlled* or Uncontrolled • Is there a concurrent comparison group? • Randomized* or Nonrandomized • Are subjects randomly allocated to the control and experimental groups? • Parallel Group or Crossover • Parallel group implies each subject receives only one of the interventions • Crossover implies each subject receives successively each of the interventions *Hence the terminology RCT

43. Clinical Trials: Randomization • Participants are randomly assigned to “Exposure” or “No Exposure” • Randomization refers to assigning subject to an intervention arm without regard for baseline characteristics • Goal of randomization is to equalize all other exposures that may confound or bias the association between Treatment and Outcome

44. Clinical Trials: Blinding • Single Blinding: examiners do not know treatment assignment • Double Blinding: examiners and subjects do not know treatment assignment • Triple Blinding: examiners, subjects, and statisticians do not know treatment assignments • Blinding is not always possible…

45. Clinical Trials • Advantages • Minimizes confounding and bias through randomization • Allows clear assessment of temporal association • Permits a test of causality between exposure and disease

46. Clinical Trials • Disadvantages • Ethical considerations of treatment or with-holding treatment • Harms (drug side effects, emotional distress) may outweigh benefits • Expensive and time-consuming • Loss to follow up • Non-adherence to group assignment • Possible early termination • Cannot always randomize an exposure

47. Quasi-Experimentation • This is essentially a clinical trial without randomization • Not possible to randomize: patients being enrolled in a rare disease trial at a site which does not have access to a given intervention • Not ethical to randomize: patients with cancer who have already failed the chemo in one arm of a trial cannot ethically be randomized to that arm • Uses statistical deductive processes to rule out threats to plausibility • Causal inference is less strong

48. Factorial Designs Intervention - X a b Y • This is essentially an attempt to evaluate multiple interventions concurrently • Given costs and inconvenience of recruiting, this is particularly appealing • Not a valid model if interaction, adds complexity, potential for polypharmacy, reviewer skepticism Intervention c - d CellIntervention a X + Y b Y + Placebo c X + Placebo d Placebo

49. Example 1: Design Type? • Investigators obtained lists of RNs age 25-42 in the 11 most populous U.S. states • They mailed baseline questionnaires about diet and other risk factors • Follow-up questionnaires were sent every 2 years for 20 years assessing additional risk factors and the development of disease outcomes

50. Example 1: Nurses’ Health Study • Prospective Cohort Study • Assembled a cohort • Assessed baseline risk factors • In the future assessed disease outcomes • Repeated Cross Sectional Study • Described changes over time in characteristics of the same study population