1. Evaluating Effect Measure Modification

2. Review of Confounding
Alternate explanation for observed exposure disease association
Distortion of true effects by a third factor
Must be associated with disease
Can be a risk factor, preventive, or a marker for a cause of disease
Independent of exposure

3. Example Confounder Exposure – carrying a lighter Outcome – lung cancer
Crude Risk Ratio: 9.0
What are potential confounders of this relationship?
Smoking status
Smokers carry lighters
Smoking is associated with lung cancer
Lighter  Lung Cancer
Smoking
Adjust for smoking status – adjusted RR = 1.1

4. Review or Confounding
A variable cannot be a confounder if it is a step in the causal chain or pathway.
Alcohol
CHD
HDL Cholesterol
On the causal pathway

5. Controlling for Confounding by Stratification
Involves evaluating the association within homogeneous categories (strata) of the confounding variable
TOTAL DATA (One 2 x 2 Table)
Crude OR = 2.2

6. Stratified Data (Two 2 x 2 Tables)
Age< 40
Age 40 and over
Stratum-specific OR = 2.8
Stratum-specific OR = 2.8
Note each stratum is like a restricted analysis. There is a narrow range of the confounder. The stratum specific ORs (2.8) differ from the crude OR (2.2) by about 25%. This difference indicates that there is
confounding by age.

7. Controlling for confounding by stratification
When confounding is present you can pool stratum specific estimate into one estimate using various methods including the Mantel-Haenszel method.
Effect Modification is when stratum-specific estimates are appreciably different.

8. Effect Measure Modification
The relation between body mass index (a measure of obesity) and breast cancer varies according to menopausal status. Among pre-menopausal women, higher BMI decreases risk. Among post-menopausal women, higher BMI increases (or does not affect) risk.
Pre-menopausal women: ↑ BMI  ↓ breast cancer
Post-menopausal women: ↑ BMI  ↑ breast cancer

9. Effect Measure Modification
Like confounding, it involves a third variable and is often evaluated by conducting a stratified analysis but…it is a biological phenomenon that should be carefully described, not controlled.

10. Example of Effect Measure Modification
Case-Control Study of Relationship Between Chronic Hypertension, Smoking and Abruptio Placenta (Williams et al., 1991)
Abruptio placenta is the premature separation of normally implanted placenta. Occurs during second half of pregnancy.
Known risk factors include trauma, advanced maternal age, cocaine use, cigarette smoking and chronic hypertension. These risk factors may damage the uterine arteries.
The Williams et al. case-control study examined the interaction between chronic hypertension and smoking.

11. Case-Control Study of Relationship Between Chronic Hypertension, Smoking and Abruptio Placenta
Crude OR = 1.8
Crude OR = 2.2

12. Stratified Analysis Stratum-specific OR = 3.3 Stratum-specific
Hypertension -Yes
Hypertension- No
Stratum-specific
OR = 3.3
Stratum-specific
OR = 1.8
State in words an interpretation of each OR.

13. Stratified Analysis
In people with hypertension, the odds of abruptio placenta are 3.3 times higher in those who smoke than in those who do not smoke.
Or In people with hypertension, compared with non-smokers there was a 3.3-fold increased odds of abruptio placenta among smokers.
In people without hypertension, the odds of abruptio placenta are 1.8 times higher in those who smoke than in those who do not smoke.
Or In people without hypertension, compared with non-smokers there was a 1.8-fold increased odds of abruptio placenta among smokers.

14. Stratified Analysis
The stratum specific odds ratios are different from one another (3.3 vs. 1.8).
Effect modification of the cigarette association by the presence of hypertension.
How would you present these results?
Pooled estimate?

15. The authors chose to summarize their results in this way:
# Cases
# Controls
Crude OR
Both HBP & Smoking 5 9
Only Smoking
253
1875
Only HBP 21
125
Neither
664
8639
1.0
* Calculate OR’s comparing to those who don’t smoke and without HBP.

16. The authors chose to summarize their results in this way:
# Cases
# Controls
Crude OR
Adjusted* OR
Both HBP & Smoking 5 9
7.2
5.9
Only Smoking
253
1875
1.8
2.1
Only HBP 21
125
2.2
1.7
Neither
664
8639
1.0
* Adjusted for age, race, marital status, payment methods, diabetes

17. How strong is the interaction between smoking and hypertension?
Odds Ratios
Smoking
Yes No
Hypertension
5.9
1.7
2.1
1.0
Use Excess Relative Risk (ERR) to determine the strength of the interaction: ERR=RR-1 (Here, the excess OR=OR-1)
Excess OR of having both factors is = 4.9
Excess OR of only smoking is = 1.1
Excess OR of only hypertension is = 0.7
Sum of the two excess ORs is = 1.8

18. How strong is the interaction between smoking and hypertension?
4.9 is much larger than 1.8, indicating that there is strong positive interaction or effect modification.
This is on the additive scale
Positive interaction is also known as synergy, which means that the excess OR for both factors is greater than the sum of the excess OR of each factor considered in isolation.
This analysis provides additional evidence of the understanding of the patho-physiologic processes underlying placental abruption.

19. How strong is the interaction between smoking and diabetes and heart disease?
Risk
Smoking
Yes No
Diabetes ?
15%
10% 5%
What is the risk difference for diabetes in non-smokers?
What is the risk difference for smoking in non-diabetics?
If we don’t have interaction on the additive scale what would the risk be in those with both?
What risk difference does this category have?

20. How strong is the interaction between smoking and diabetes and heart disease?
Yes No
Diabetes ?
15%
10% 5%
What is the risk ratio for diabetes in non-smokers?
What is the risk ratio for smoking in non-diabetics?
If we don’t have interaction on the multiplicative scale what would the risk be in those with both?
What RR does this category have relative to those without diabetes who don’t smoke?

21. Summary: Types of “Third” Variables
Confounders: a nuisance that you want to control. Can be controlled via stratified analysis.
Effect modifiers: a biological phenomenon that you want to understand. Can also be assess by a stratified analysis.
Other variables: You don’t have to “worry” about variables that are not confounders or effect modifiers.

22. Practice
Consider each of the following scenarios and state whether the variable in question is a confounder.
A study of the relationship between contract lens use and the risk of eye ulcers. Crude RR=3 and the age-adjusted RR is 1.5. Is age a confounder?

23. Practice
A case-control study of the relationship between cigarette smoking and pancreatic cancer. In this study, coffee drinking is associated with smoking and is a risk factor for pancreatic cancer among both smokers and non-smokers. Is coffee drinking a confounder in this study.

24. Practice
A study of the relationship between exercise and heart attacks that is conducted among men who do not smoke. Is gender a confounder in this study? Is gender an effect modifier.

25. Practice
A cohort study of the risk of liver cirrhosis among female alcoholics. Incidence rates of cirrhosis among alcoholic women are compared with those among nonalcoholic women. Non-alcoholics are individually matched to alcoholics on month and year of birth. Is age a confounder in this study?

26. Practice
State which method to control for confounding is being used in the following scenarios. In each scenario, exercise is the exposure, myocardial infarction in the disease, and gender is the confounder.
A study of exercise and MI that is limited to men.
A case-control study of exercise and MI that includes men and women. Controls are selected so that the proportion of male and female subject groups are identical.
A study of exercise and MI that includes men and women. The study determines the relative risk separately for men and women and compares these with the crude RR.

27. Practice Indicate whether the following statements are true or false:
All high-quality epidemiology studies include techniques for controlling for confounding.
Intermediate variables in a causal pathway are special types of confounders.
The counterfactual ideal is used to guide the selection of a comparison group in order to minimize confounding.
Epidemiologist can tell if confounding is present by examining the strength of the crude measure of association.
Experimental studies always have less confounding than observational studies.

28. Practice Define each of the following terms:
Effect measure modification
Heterogeneity and homogeneity of effect
Synergy
Antagonism

29. Practice
A case-control study was conducted to determine if the relationship between cigarette smoking and lung cancer is modified by the presence of asbestos exposure. The following results were obtained:
Exposed to Odds ratio for lung cancer
Both smoke and asbestos
Only smoking
Only asbestos
Neither
Is asbestos an effect measure modifier of the relationship between smoking and lung cancer?
State the reason for your answer.
Calculate the OR for smoking in those exposed and unexposed to asbestos.

30. Practice True or false:
If effect measure modification is present using a ratio measure of comparison, then it will also be present using a difference measure.
Statistical test are sometimes useful for assessing the presence of effect measure modification.
Departure form additively is a higher degree of effect measure modification than departure from multiplicity.