1. OVERVIEW FOR EXAM 2

2. Study Designs Establish Causality Generate Hypotheses
Randomized Trials
Cohort Studies
Case Control Studies
Cross-Sectional Studies
Ecologic Studies
Generate Hypotheses

3. Randomized Controlled Trials

4. Investigator assigns exposure
Study Population
Investigator assigns exposure
RANDOMIZATION
Exposure 1
Exposure 2
Not Improved
Improved
Improved
Not Improved

5. Situations that favor the use of a RCT
Exposure of interest is a modifiable
Individuals are willing to relinquish control
Genuine uncertainties regarding the effects of the interventions
Effect of intervention on a rare outcome is of sufficient importance to justify a large study
Potential benefits must outweigh the risks

6. Typical comparison or control groups in RCTs
The Placebo (looks like intervention)
Alternative treatment
‘Usual care’

7. Source Population External Validity Study Population RANDOMIZED
New treatment
Current treatment
Internal validity

8. Source population: the population to whom the results of the intervention are thought to be applicable, and from whom the study population is drawn.
Study population

9. Generalizability (External validity)
Internal Validity

10. Consent to Participate = Study Population Decline participation
Are there significant differences between those that consent and those that do not?
Source
population
Eligible
Ineligible
Consent to Participate
= Study Population
Decline
participation
Random Allocation
Treatment A
Treatment B
Loss to follow-up? Measurement issues?

11. Internal Validity
Occurs when the study findings are close to the true association between exposure and disease
Relies on the ability of subjects to provide valid and reliable data
Mental/cognitive status, language fluency
Relies on compliance with a regimen
Failure to comply makes exposed and unexposed more similar
Low probability of dropping out
Residence, comorbidity

12. External Validity
Occurs when the results from the study can be applied to the larger (source) population
Are there demographic differences between eligible and ineligible subgroups?
Difference between those that consent and do not consent?
Does your intervention mirror what will happen in the community or source population?

13. MASKING (aka blinding)
Observers and/or subjects are kept ignorant
Single blind or mask subjects
Double blind or mask observer and subject
Triple blind or mask observer, subject and analyst
Helps improve internal validity of the study

14. How do we analyze the results of an RCT?

15. Measures of Association
• Risk Ratio: Ratio of the Cumulative Incidence among exposed versus those not exposed • Rate Ratio: Ratio of the Incidence Rate in those exposed versus those not exposed.

16. Risk Ratio= a/a+b = CIdrug A / CIplacebo
Developed Disease
Treatment
Yes:
No:
Total:
Drug A: a b
a+b
Placebo: c d
c+d
a+c
b+d
total
Risk Ratio= a/a+b = CIdrug A / CIplacebo
c/c+d

17. Interpreting Relative Risks
RR>1 The risk of X is RR times (or RR-1=>Y%)
more likely to occur in exposure A than B
RR=1 Null Value (no difference between groups)
RR<1 Either calculate the reduction in RR
(1-RR=>Y%) or invert (1/RR) to be interpreted
as “less likely” risk
RR =

18. Strengths of the RCT Study Population RANDOMIZATION Not exposed
Known and unknown confounders controlled for by design
Know that exposure preceded disease
Can estimate incidence
Can study rare exposures
Can study multiple outcomes
Study Population
RANDOMIZATION
Not exposed
Exposed
Event
No event
Event
No event

19. Limitations of The RCT Study Population RANDOMIZATION Not exposed
Cannot study all exposures for ethical and practical reasons
Inefficient for rare outcomes or outcomes with long latency periods
Prospective design is expensive
Prospective design can require long follow-up and if people drop out differently, internal validity can be compromised
Study Population
RANDOMIZATION
Not exposed
Exposed
Event
No event
Event
No event

20. Cohort Studies

21. Cohort Study Study Population Investigator Observes Or Recruits
No Exposure
Exposure
The researcher does not control the intervention/exposure, but instead OBSERVES its frequency and effects.

22. Define comparison groups here
Cohort Study Design
Disease
Exposure
No Disease
Disease
No Exposure
No Disease
Define comparison groups here
Watch over Time

23. Measuring Exposure Clear Objective Measurable
Smoked 100 cigarettes over the past month
Influenza vaccine in the last month

24. Measuring Outcome Clear Objective Measurable
Physician diagnosis in medical record
Specified ICD codes in hospital discharge data
Cause of death on death certificate

25. Strengths of Cohort Studies
1. Temporality (exposure before disease) 2. Efficient for rare or unusual exposures 3. Assess multiple outcomes from a single exposure 4. Can estimate incidence

26. Weaknesses of Cohort Studies
Expensive
Inefficient for studying rare diseases
Not good for diseases that take a long time to develop (e.g. long latency)
People can change their exposure classification (unlike an RCT)
Differential loss-to-follow-up between exposure groups can bias associations

27. Two Main Types of Cohort Studies
Prospective
Retrospective

28. Prospective Cohort Design
Disease
Exposure
No Disease
Disease
No Exposure
No Disease
Start Here:
Present
Future

29. Retrospective Cohort Design
Disease
Exposure
No Disease
Disease
No Exposure
No Disease
Past (t1) or Present or Future
Past (t0)

30. Prospective vs. Retrospective 10-year follow-up period
Prospective Cohort Study:
Retrospective Cohort Study:
Investigator
begins the study
Follow - Up
Selection of Exposed &
Unexposed Participants
End of Follow Up
2003
2013
Investigator
begins the study
End of Follow Up
2003
1993
Strategy 1: Exposure and outcome data from records
Strategy 2: Exposure data from records
Outcome data assessed directly via interview or other method

31. Prospective Cohort Studies
Exposure at initiation of study
Outcome that may occur in future
Followed over time

32. Retrospective Cohort Studies
Exposure recorded in past
Employment records
Med records
Typically not as good as in the prospective study
Disease incidence (or mortality) assessed from past, present, or future
Great for long latency diseases
Example: Followed over 10 year conceptually but can be actually assessed in one year (e.g. through record review)

33. Advantages of Retrospective Cohort Design
Timely and temporal
Less expensive than
Prospective cohort
Good for diseases of long latency

34. Disadvantages of Retrospective Cohort Design
Reliance on available information
Quality?
Ascertainment biases in outcomes
Exposure is known

35. Measures of Association for Cohort
Risk Ratio: Ratio of the cumulative incidence among exposed to cumulative incidence among unexposed Rate Ratio: Ratio of the incidence rate among exposed to incidence rate among unexposed

36. How to Set Up a 2 X 2 Table with Person-Time (Incidence Rate) Data
Outcome
Yes
PYO
Disease Rate
Exposure a
PYE
a / PYE No c
PYU
c / PYU
Rate Ratio = (a/PYe) / (c/PYu)

37. Disease = MI
Yes
PYO
Disease Rate
Exposure = HRT 30
54,310
30 / 54,310 No 60
51,470
60 / 51,470
Rate Ratio = IRe / IRu = (a/Pye) / (c/Pyu)
(30/54,310) / (60/51,470) = (protective effect)
Since it is RR<1, there are three choices for interpretation:
a) Use RR = 0.474
b) Invert it: 1/RR = 1 / = 2.11
c) Convert to percent reduction: = .526 = 52.6% reduction
The rate of developing MI from 2000 to 2010 was 2.11 times less among HRT users compared to non-HRT users in this study in Michigan over 10 years.

38. Case Control Studies

39. Basic Case-Control Design is Retro
Exp
Cases
Not Exp
Source Population
Exp
Controls
Not Exp
Controls should be as comparable to cases as possible.
Controls should have an equal theoretical probably of being exposed as cases

40. When to Conduct a Case-Control Study?
When the disease or outcome is rare
Ex: Studying risk factors for birth defects
When little is known about the disease
Ex. Early studies of AIDS

41. Selection of Cases Decide on a case definition
Decide whether PREVALENT or INCIDENT cases
Where will you get cases?
Think about who you want to generalize the results to in the future.

42. Selection of Controls
Controls should be as comparable to cases as possible.
Age, sex, ethnicity, geography, income, education
Controls should have an equal theoretical probability of being exposed as cases
Controls have to have the ability to be cases
General population set of controls used for prostate cancer case-control study?

43. Issues with Different Types of Controls
General population controls
May not be easy to get
More likely representative of source population
May not make for a valid comparison to cases (poorer recall of exposure) or not same possibility of being exposed
Hospital controls
Easier to get
More similar to cases making valid comparison more likely
Might not represent source population

44. Measure of Association in Case-Control Study
(cases) D-
(controls) E+
6 (a)
3 (b) 9 E-
4 (c)
7(d) 11 10 20
a/c
b/d
Odds of exposure in cases OR
The odds ratio is odd …so just keep at it.
Odds of exposure in controls
a *d
b * c
6 *7
4 * 3
OR=
= 3.5

45. Advantages of Case-Control
Relatively easy to conduct
The best design for rare diseases
An important foundational step to evaluate association to motivate cohort study

46. Disadvantages of Case-Control
Usually can’t estimate even basic population measures of disease or exposure frequency
usually no prevalence or incidence data
Typically, can’t separate forward causation from reverse causation
Increased breastfeeding associated with growth decline in toddlers (actually the toddlers that were sick with diarrheal diseases breastfeed more)

47. The Rare Disease Assumption
Odds ratio (OR) approximates risk ratio(RR) when disease is rare because
a / (a+b) ~ a / b (e.g. 5/(5+1000) ~ 5/1000)
c / (c+d) ~ c / d
Analogously, prevalence odds ratio approximates the prevalence ratio when the disease is rare

48. Cross-sectional and Ecological Study Design

49. Cross Sectional Studies:
Simultaneously assess disease and exposure in an individual
Occurs a single point of time (no follow-up)
A study of prevalences and their interrelationship
Measures of Association:
Prevalence odds ratio
Prevalence ratio

50. Advantages of Cross Sectional Studies
Faster and less expensive than cohort
Often done to get information to apply to the population at large (source population)
Get good estimates of prevalence of many exposures and outcomes simultaneously

51. Disadvantages of Cross Sectional Studies:
Temporality most often not known (but sometimes is known)
Can’t capture the change in risk factors or disease over time
Not good for rare diseases
Not good for rare exposures

52. Two Measures of Association Cross-Sectional Studies
Disease
No disease
Exposed a b
Unexposed c d
Two Measures of Association
Cross-Sectional Studies
a/(a+b)
c/(c+d)
1. Prevalence Ratio
Prevalence dx in exposed =
Prevalence dx in unexposed ad bc
2. Odds ratio =
No temporality (can refer to odds of disease in exposed or odds of exposure in diseased)

53. Ecologic Study
Uses group level or population level data to explore associations.
Usually, measures of disease frequency (prevalence, incidence, case fatality, mortality) are plotted against exposure frequencies
The measure of association is a correlation coefficient (r) or simple linear regression line
(y = a + bx ).

54. Prostate Cancer and Sugar Consumption

55. Ecologic Fallacy
Findings: Provinces with greater proportions of Protestants had higher suicide rates than Catholic provinces in France
Concluded: Protestants more likely to commit suicide than Catholics
May have actually been Catholics in predominantly Protestant provinces who were committing suicide
Ecologic Fallacy: Making an inference about individual level suicide patterns based on proportion of suicides in provinces
Schwartz S. The Fallacy of the Ecological Fallacy: The Potential Misuse of a Concept and the Consequences. American Journal of Public Health, May 1994, 84: and Durkheim E. Suicide. New York, NY: Free Press; 1951.

56. A few questions to consider
Where can incidence be estimated?
What designs are good for rare exposures?
What designs are good for rare outcomes?
Is randomization to ensure external validity or internal validity?
What designs can you estimate RR?
What designs do you need to use an OR?
What is the difference between an exposure OR and a disease OR?

57. Other Risk Estimates

58. How do we estimate public health effect of an exposure?
Attributable Risk Estimates of Effect
Attributable Risk (AR)
Attributable Risk Percent (AR%)
Population Attributable Risk (PAR)
Population Attributable Risk Percent (PAR%)
These statistics address the question:
How much of the disease that occurs can be attributed to a certain exposure?

59. AR and PAR tell us: how many cases of disease could be eliminated if we completely eliminate the exposure
AR% and PAR% tell us: what percent of cases could be eliminated if we completely eliminate the exposure

60. Measures of Attribution and Effect
• Attributable Risk (AR) is a Risk Difference (RD)
It estimates the excess risk of disease in those exposed compared with those non-exposed.
AR = Incidence Exposed – Incidence Not Exposed
Group of Interest: Exposed
Quantifies the risk of disease in the “exposed” group attributable to the exposure

61. Calculating Attributable Risk
Subtract away the background risk
Two measures of incidence: Incidence Rate (IR) or Cumulative Incidence (CI)
For Incidence Rate: AR = IRExposed – IR Unexposed
For Cumulative Incidence: AR = CIE – CIU

62. Assumptions
Interpretation of the AR is dependent on the assumption that a cause-effect relationship exists between exposure and disease.
If no association between the exposure and disease, IE – IU= 0 and therefore AR = 0.

63. How does AR compare to other measures of association?
The RR is a measure of the strength of the association and the possibility of a causal relationship.
The AR indicates the potential for prevention, if the exposure could be eliminated.

64. Example: Smoking and CHD
Exposure
CHD yes
CHD no
Total
Smokes 84
2,916
3,000
Doesn’t smoke 87
4,913
5,000
171
7,829
8,000
CIE = 84/3000 = 28.0 per 1000
CIU = 87/5000= 17.4 per 1000
AR = CIE-CIU = = 10.6 per 1000
Interpretation: The excess occurrence of CHD among smokers attributable to their smoking is 10.6 per 1,000 in Michigan in

65. Attributable Risk Percent (AR%)
What proportion of cases in exposed persons is due to the exposure?
AR% = ( IE – IU )/ (IE)
Can be interpreted as the proportion of the disease in the exposed that could be prevented by eliminating the exposure

66. How to Calculate AR%?
AR% = (IRE – IRU)/ IRE or
AR% = (CIE – CIU)/CIE

67. Recall Smoking and CHD AR = CIE-CIU = 28.0 - 17.4= 10.6 per 1000
AR% = (CIE – CIU)/CIE = ( )/28.0
= 10.6/28.0 = 37.9%
Interpretation: If smoking does cause CHD, 37.9% of CHD among smokers can be attributed to their smoking in Michigan OR
If we eliminated smoking in this group of smokers, 37.9% of the CHD morbidity could have been prevented in Michigan in

68. Population Attributable Risk (PAR)
The PAR estimates the excess rate of disease in the “total study population” of exposed and nonexposed that is attributable to the exposure.

69. How to Calculate?
PAR = IT – IU
PAR = IRT – IRU Or
PAR = CIT – CIU

70. PAR alternative calculation
Alternatively, the PAR can be calculated as
PAR = (AR)*Pe
Where AR is the attributable risk and Pe is the proportion of exposed people in the population.

71. How do we calculate PAR%?
PAR% = (IT – IU)/ IT or
PAR% = (CIT – CIU)/CIT
Note: In a case-control study, when the disease is rare, the OR may be substituted for the RR.

72. Summary of AR calculations
In Exposed Group
In Total Population
Incidence attributable to exposure (AR or PAR)
IE – IU
IT – IU
Proportion of incidence attributable to exposure (AR% or PAR%)
(IE – IU)/Ie
(IT – IU)/IT

73. A few AR – PAR questions
Can you use the odds ratio from a case-control study in an AR calculation?
Is the PAR larger than the AR? Why?
If Michigan and Ohio have the same cumulative incidence of disease in exposed and unexposed, will they have the same AR?

74. Begin by randomly assigning “healthy” people to exposure or none
RCT
Cohort
Case-control
Cross-sectional
Design
Begin by randomly assigning “healthy” people to exposure or none
Begin with “healthy” exposed and unexposed
Begin with sample of cases and controls
Begin with population sample
Follow-up for newly developed outcome
Obtain information on exposure
Cross-classify by exposure and outcome
Randomization of exposure
Yes No

75. Incidence (cumulative incidence or incidence rate)
RCT
Cohort
Case-control
Cross-sectional
Measure of Disease Frequency
Incidence (cumulative incidence or incidence rate)
Odds of exposure
Prevalence
Groups being compared
Exposed and unexposed
Cases and controls
Measure of Association
Risk or rate ratio
(relative risk)
Odds ratio
Prevalence ratio