1. JOSE RONILO G. JUANGCO, MD. MPH. Department of Preventive and Community Medicine UERMMMC

2. Learning Objectives At the end of the lecture the students should be able to: differentiate among the different epidemiologic study designs being used on medical research. know the advantages and disadvantages of the different study designs. decide on what particular research design is best suited for their research proposal. 10/4/20152

3. REVIEW ! ! ! 10/4/20153 1.What are the two types of epidemiological studies? 2.What are the two types of Observational Studies? 3.What are the types of Descriptive Studies? 4.What types of Descriptive designs may also be classified as analytical?

4. 5.What are the types of analytical designs? 6.What are the types of Cohort Studies 7.What are the types of Experimental Studies? 10/4/20154

5. APPROACH OBSERVATIONAL Descriptive Case Report Case Series Ecological* Cross Sectional* Analytical Case Control Cohort EXPERIMENTAL Clinical Trials (RCT) Therapeutic Trial Field Trial Prevention Community Trial Intervention 10/4/20155

6. Types of Studies A. Experimental - study factor is manipulated by the investigator Types Laboratory versus real world B. Observational - no manipulation of study factor by the investigator 1. Descriptive versus Analytic 2. Retrospective versus Prospective 10/4/20156

7. A-Case report Description Is a brief objective report of clinical characteristic or outcome from a single clinical subject or event Study question : It is commonly used to report unusual or unexpected events Examples: A report of advanced diabetic retinopathy in a patient with no other clinical evidence of diabetes. - 10/4/20157

8. Strengths and limitation : No statistical analysis or comparative group It provides the first report of unexpected event, hypotheses for testing and definition of issue for further study, but the results are rarely generalized 10/4/20158

9. B-Case series report: -Description: An objective report of a clinical characteristic or outcome from a group of clinical subjects. -Study question : Report new disease or health related problem. -Examples : The identification of several children with birth defects who were born to mothers who took thalidomide during pregnancy. -.-. 10/4/20159

10. Strength and limitation : Control or comparison group is not included Generalization of the results is limited because the selection of study subjects is unrepresentative This study design has case selection bias and lacks statistical validity 10/4/201510

11. When the goal of research is to test a hypothesis about the relationship between variables No manipulation of variables Variables must have values along a numeric scale Different ways to describe relationships… 10/4/201511

12. Increase in the values of one variable is associated with increase in the second variable 10/4/201512

13. Increase in the value of one variable is associated with decrease in the second variable 10/4/201513

14. Increase in the value of one variable is associated with both increase and decrease of the second variable 10/4/201514

15. There is no relationship between two variables 10/4/201515

16. Observations are collected and a Pearson correlational coefficient (r) is computed to specify the nature of the relationship between variables -1 0 +1 10/4/201516

17. Cross-Sectional Study – Prevalence Study Cross-Sectional Studies measure existing disease and current exposure levels. This study analyzes data collected on a group of subjects at one time rather than over a period of time 10/4/201517

18. Strength and Limitations It is quick, cheap and easy True rates are determined (the prevalence). Can study multiple exposure and multiple diseases. 10/4/201518

19. Strength and Limitations Impractical for rare diseases Not useful for establishing causal relationships. It does not allow us to answer the question,which came first (which caused which) Data are particularly susceptible to distortion through the introduction of bias into the research during sampling questionnaire and interviewing. 10/4/201519

20. APPROACH OBSERVATIONAL Descriptive Case Report Case Series Ecological* Cross Sectional* Analytical Case Control Cohort EXPERIMENTAL Clinical Trials (RCT) Therapeutic Trial Field Trial Prevention Community Trial Intervention 10/4/201520

21. CASE CONTROL 10/4/201521 EXPOSED NOT EXPOSED EXPOSED CASES (+) DISEASE CONTROL (-) DISEASE POPULATION TIME DIRECTION OF STUDY

22. Purpose Descriptive Describe the risk factor profile for an outcome. Analytic Analyze associations between outcome and risk factors. How do we analyze the data?

23. ANALYSIS OF CASE-CONTROL STUDY ODDS RATIO – the measure of association between the factor/predictor and the outcome. = ODDS OF Case being exposed ODDS OF Control being exposed

24. Doll and Hill’s Data

25. Cases Controls Exposed Not Exposed a b c d OR = a x d  b x c Using Doll & Hill’s data: OR = 647 x 27 = 14.04 622 x 2 Note: the odds ratio of the Doll & Hill data shows clearly how much smoking increases the risk of lung cancer.

26. Interpretation OR = 1 no association OR> 1 presence of association, more factor among cases vs. controls OR<1 presence of inverse association, lesser factor in cases compared to controls

27. Bias in data collection The study is unmasked. ( since the presence or absence of disease is known to the subject and the observer). Recall bias may also occur because exposure to risk factor is often dependent on memory of subjects. 10/4/201527

28. Bias in the selection of subjects -(Non-representativeness of cases) since a case control study is not population – based study (Berkson Fallacy). 10/4/201528

29. Berkson Fallacy As example, suppose a collector has 1000 postage stamps, of which 300 are pretty and 100 are rare, with 30 being both pretty and rare. 10% of all her stamps are rare and 10% of her pretty stamps are rare, so prettiness tells nothing about rarity. She puts the 370 stamps which are pretty or rare on display. Just over 27% of the stamps on display are rare, but still only 10% of the pretty stamps on display are rare (and 100% of the 70 not-pretty stamps on display are rare). If an observer only considers stamps on display, he will observe a spurious negative relationship between prettiness and rarity as a result of the selection bias (that is, not-prettiness strongly indicates rarity in the display, but not in the total collection). 10/4/201529

30. Disadvantage Data Quality Data with inadequate detail, questionable reliability, or use a different standard to judge disease severity. Other Capable of studying only one outcome at a time Cannot calculate prevalence or incidence. Subject to confounding factors. Cannot prove contributory cause. 10/4/201530

31. COHORT 10/4/201531 DISEASEDISEASE EXPOSUREEXPOSURE TIME DIRECTION OF STUDY

32. Concurrent Cohort Study (Prospective) Time Present2025 Defined Population Fertilizer Exposure No Fertilizer Exposure Cancer No Cancer Cancer No Cancer

33. Nonconcurrent Cohort Study (Historical) Time 19852010 Defined Population Fertilizer Exposure No Fertilizer Exposure No Cancer Cancer No Cancer Cancer

34. ANALYSIS OF COHORT STUDIES RELATIVE RISK - measures the strength of relationship or the association between the factor/predictors and the outcome. = Incidence Rate of outcome in EXPOSED IR outcome in UNEXPOSED GRP.

35. Cohort Study (+) disease (-) disease (+) exposur e ABA + B (-) exposur e CDC + D A + CB + D

36. Cohort Study Incidence Rates: exposed: IR exposed = A ÷ (A + B) unexposed: IR unexposed = C ÷ (C + D) Relative Risk (RR): RR = (IR exposed ) ÷ (IR unexposed ) RR = [A ÷ (A + B)] ÷ [C ÷ (C + D)]

37. Relative risk 1: No difference in outcome between 2 groups < 1: Less risk of developing outcome > 1: Higher risk of developing outcome 10/4/201537

38. Low probability of selection and recall bias Provide the probability of estimating the attributable risk More conclusive results Inefficient for rare diseases Not always feasible Long term follow up Require a large sample size High Cost 10/4/201538

39. Experimental Therapeutic Trial Field Trial Community Trial 10/4/201539

40. Selected Concepts The Design of Trials 1.The control group 2.Randomization 3.Admissibility criteria 4.Outcome ascertainment 5.Ethics

41. The Need for Controls Placebo effect – inert substances are associated with improvement Hawthorne effect – observation improves behavior Conditions improve on their own over time Use of a proper control group neutralizes all these effects

42. Element 2. Randomization Groups must not differ with respect to relevant characteristics other than the exposure being studied Otherwise, results can be confounded by extraneous factors that lurk in the background Randomization encourage the balancing of measured and unmeasured potential confounders, neutralizing their effects Randomization is the second leading principle of experimentation

43. Experimental Design time Study begins here (baseline point) Study population Intervention Control outcome no outcome outcome no outcome baseline future RANDOMIZATION

44. Element 3. Admissibility Criteria Restriction of subjects to those with uniform characteristics Types of admissibility criteria Person, place and time Prior conditions (e.g., having or lacking a particular condition) Risk factor restriction (non- smokers)

45. Element 4. Outcome Ascertainment Outcome ascertainment validity and reproducibility Blinding balances inaccuracies Of course, blinding is not always possible Accurate outcome ascertainment is the third principle

46. Types: Single blind:When the subjects do not know whether they belong to the treatment or the control group. Double blind: When both the subject and the researcher has no knowledge. Triple blind:When this knowledge is not known by all the three parties; the subject, the researcher, and the statistician. 10/4/201546

47. 5. Ethics = Equipoise A condition of equipoise (balanced doubt) must exist for a human experiment can take place You cannot knowingly expose a participant to known harm You cannot knowingly withhold a known benefit

48. Ability to assign the independent variable Ability to randomize subjects to random and control Ability to control confounding variable Ability to replicate findings Difficulty of extrapolation Ethical problems Non representability of samples 10/4/201548

49. Clinical Trial There are several variations on the randomized trial design that can substantially increase efficiency, under the right circumstances: matched-pair randomization time-series design cross-over design

50. Clinical Trial

52. How do we Analyze Clinical Trial? Relative Risk (RR): RR = (Risk Treatment ) ÷ (Risk Control ) For positive outcome: RR < 1 treatment is harmful RR = 1no significant difference RR > 1 treatment is beneficial

53. Clinical Trial Relative Risk (RR): RR = (Risk Treatment ) ÷ (Risk Control ) For negative outcome: RR < 1 treatment is beneficial RR = 1no significant difference RR > 1 treatment is harmful

54. Measures of treatment derived benefit Absolute Risk Reduction (ARR) = Risk exposed – Risk unexposed Relative Risk Reduction (RRR) = Risk exposed – Risk unexposed Risk exposed

55. Basic Arithmetic Suppose you have $2 and I have $1 Absolute comparison  made by subtraction $2 – $1 = $1 “I have $1 more than you” (in absolute terms) Relative comparison  made by division $2 ÷ $1 = 2 [unit-free] “I have twice as much as you” (relatively speaking)

56. Basic Arithmetic Suppose the 5-year risk of disease In smokers is 2 per 100 In nonsmokers is 1 per 100 Absolute contrast (Risk Difference): (2 per 100) – (1 per 100) = 1 per 100 There is one addition case per 100 exposures Relative contrast (Risk Ratio): (2 per 100) ÷ (1 per 100) = 2 The exposure doubled risk (equivalently, there is a 100% increase in risk in relative terms) Apply this scheme to risk estimates

57. Preventive Measure Disease +- +aba+b -cdc+d a+cb+d Disease Rate in Experimental Group P1 = a/a+c Disease Rate in Control Group P2 = b/b+d Protective Value = P2- P1/P2 How do we analyze Prophylactic Trial?

58. In Summary OBSERVATIONAL Descriptive Case Report Case Series Ecological* Cross Sectional* Analytical Case Control Cohort EXPERIMENTAL Clinical Trials (RCT) Therapeutic Trial Field Trial Prevention Community Trial Intervention 10/4/201558

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