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Intermediate methods in observational epidemiology 2008

Intermediate methods in observational epidemiology 2008. Interaction. Due to a study defect. Found in nature. Threats to Causal Inference in Epidemiologic Studies. Threats to causal inferences in epidemiologic studies - outline. Lack of precision Lack of internal validity

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Intermediate methods in observational epidemiology 2008

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  1. Intermediate methods in observational epidemiology 2008 Interaction

  2. Due to a study defect Found in nature Threats to Causal Inference in Epidemiologic Studies Threats to causal inferences in epidemiologic studies - outline Lack of precision Lack of internal validity Selection bias Information bias Confounding Interaction or “effect” modification is not on this list

  3. The Sun, September 29, 1995 THUS, ASPIRIN MODIFIES THE “EFFECT” OF ANGER ON THE RISK OF A HEART ATTACK

  4. The Sun, September 29, 1995 A BETTER DEFINITION FOR OBSERVATIONAL DATA: THUS, ASPIRIN MODIFIES THE STRENGTH OF THE ASSOCIATION OF ANGER WITH THE RISK OF A HEART ATTACK

  5. Note: to assess interaction, a minimum of 3 variables were needed in this study: • Aspirin • Anger • Coronary Heart Disease (CHD) Aspirin Anger Anger Interaction = “Effect” modification: The “effect” of the risk factor -- anger – on the outcome – CHD -- differs depending on the presence or absence of a third factor (effect modifier) --aspirin. The third factor (aspirin) modifies the “effect” of the risk factor (anger) on the outcome (CHD). Stronger association Weaker association CHD CHD Heterogeneous Associations

  6. Terminology Observed heterogeneity • True (biological, sociological, psicological, etc.) Other than true, it can be due to: • Bias • Confounding • Chance • Differences in level of exposure between the categories of the effect modifier “Effect Modification” “Interaction” Heterogeneous Associations Effect Modification The “effect” of an exposure on an outcome depends on (is modified by) the level (or presence/absence) of a third factor. The third factor modifies the effect of the exposure on the outcome.

  7. Risk associated with environmental exposure depends on genotype (gene-environment interaction) One in 15,000 people may not properly metabolize phenylalanine, an essential amino acid found in aspartame. • Individuals WITH this genotype WILL develop symptoms IF EXPOSED to phenylalanine. • Individuals WITH this genotype WILL NOT develop symptoms WITHOUT exposure to phenylalanine. • Individuals WITHOUT this genotype WILL NOT develop symptoms, even WITH exposure to phenylalanine. • Both the gene AND environmental exposure are required for symptoms to occur. PHENYLKETONURICS: CONTAINS PHENYLALANINE

  8. True effect modification is NOT a nuisance to be eliminated • Biases and confounding effects distort true causal associations • Strategies: avoid, eliminate, reduce, control • Effect Modification is informative • Provides insight into the nature of the relationship between exposure and outcome • May be the most important result of a study • It should be reported and understood

  9. True effect modification is NOT a nuisance to be eliminated • Biases and confounding effects distort true causal associations • Strategies: avoid, eliminate, reduce, control • Effect Modification is informative • Provides insight into the nature of the relationship between exposure and outcome • May be the most important result of a study • It should be reported and understood

  10. FROM NOW ON, THE WORD “EFFECT(S)” WILL BE USED LOOSELY, EVEN WHEN DESCRIBING RESULTS OF OBSERVATIONAL RESEARCH IN OTHER WORDS, FOR PRACTICAL PURPOSES, “EFFECT(S)” WILL REFER TO ASSOCIATIONS THAT MAY OR MAY NOT BE CAUSAL Word of caution: true effects cannot be inferred from observational data obtained in single studies.

  11. Interaction: Two definitions of the same phenomenon • When the effect of factor A on the probability of the outcome Y differs according to the presence of Z (and vice-versa) • When the observed joint effect of (at least) factors A and Z on the probability of the outcome Y is different from that expected on the basis of the independent effects of A and Z

  12. Interaction

  13. Interaction

  14. Interaction

  15. Interaction

  16. Interaction

  17. Interaction

  18. Interaction

  19. How is effect measured in epidemiologic studies? • If effect is measured on an additive or absolute scale (attributable risks)  additive interaction assessment (Attributable Risk model: based on absolute differences between cumulative incidences or rates). • If effect is measured on a relative (ratio) scale (relative risks, odds ratios, etc.)  multiplicative interaction assessment (Relative Risk model).

  20. Two strategies to evaluate interaction based on different, but equivalent definitions: • Effect modification (homogeneity/heterogeneity of effects) • Comparison between joint expected and joint observed effects The two definitions and strategies are completely equivalent. It is impossible to conclude that there is (or there is not) interaction using one strategy, and reach the opposite conclusion using the other strategy! Thus, when there is effect modification, the joint observed and the joint expected effects will be different.

  21. First strategy to assess interaction:Effect Modification ADDITIVE (attributable risk) interaction Hypothetical example of presence of additive interaction 5.0 20.0 Conclude: Because AR’s associated with A are modified by exposure to Z, additive interaction is present.

  22. First strategy to assess interaction:Effect Modification MULTIPLICATIVE (ratio-based) interaction Hypothetical example of presence of multiplicative interaction 2.0 5.0 Conclude: Because RR’s associated with A are modified by exposure to Z, multiplicative interaction is present.

  23. Two strategies to evaluate interaction based on different, but equivalent definitions: • Effect modification (homogeneity/heterogeneity of effects) • Comparison between joint expected and joint observed effects 

  24. Expected 10.0 Joint observedAR = 25% Joint expected AR = ARA+Z- + ARA-Z+= 10% Conclude: Because the observed joint AR is different from that expected by adding the individual AR’s, additive interaction is present (that is, the same conclusion as when looking at the stratified AR’s) Second strategy to assess interaction:comparison of joint expected and joint observed effects Additive interaction 5.0 5.0 25.0

  25. 5.0 Joint observedRRA+Z+ = 12.5 Joint expected RRA+Z+ = RRA+Z-× RRA-Z+= 2.0 × 2.5 = 5.0 Conclude: Because the observed joint RR is different from that expected by multiplying the individual RR’s, there is multiplicative interaction (that is, the same conclusion as when looking at the stratified RR’s) Second strategy to assess interaction:comparison of joint expected and joint observed effects Multiplicative interaction 2.0 2.5 12.5

  26. How can interaction be assessed in case-control studies?

  27. Case-control study Prospective study First strategy to assess interaction:Effect Modification Additive interaction cannot be assessed in case-control studies by using the effect modification (homogeneity/heterogeneity) strategy, as no incidence measures are available to calculate attributable risks in the exposed

  28. Case-control study First strategy to assess interaction:Effect Modification Layout of table to assess MULTIPLICATIVE interaction

  29. Odds Ratios for the Association of Maternal Smoking with Isolated Clubfoot, by Family History of Clubfoot, Atlanta, Georgia, 1968-80 (Honein et al, Am J Epidemiol 2000;152:658-665) • Hypothesis: Family history of clubfoot is a potential modifier of the association of maternal smoking with clubfoot. • Use the “effect” modification strategy to evaluate the presence of multiplicative interaction. For this strategy, two reference categories are used. Conclusion: Because the stratified ORs are different (heterogeneous), there is multiplicative interaction. Now evaluate the same hypothesis using the second strategy: comparison between joint observed and joint expected “effects”.

  30. Note common reference category Case-Control Study Second strategy to assess interaction: comparison between joint observed and joint expected effects Layout of table to assess both ADDITIVE and MULTIPLICATIVE interaction

  31. Case-Control Study Second strategy to assess interaction: comparison between joint observed and joint expected effects Layout of table to assess both ADDITIVE and MULTIPLICATIVE interaction

  32. Case-Control Study Second strategy to assess interaction: comparison between joint observed and joint expected effects Layout of table to assess both ADDITIVE and MULTIPLICATIVE interaction

  33. Case-Control Study Second strategy to assess interaction: comparison between joint observed and joint expected effects Layout of table to assess both ADDITIVE and MULTIPLICATIVE interaction

  34. Case-Control Study Second strategy to assess interaction: comparison between joint observed and joint expected effects Layout of table to assess both ADDITIVE and MULTIPLICATIVE interaction

  35. Case-Control Study Second strategy to assess interaction: comparison between joint observed and joint expected effects Layout of table to assess both ADDITIVE and MULTIPLICATIVE interaction

  36. Under ADDITIVE MODEL: Exp’d OR++ =OR+- + OR-+ - 1.0 Case-Control Study Second strategy to assess interaction: comparison between joint observed and joint expected effects Layout of table to assess both ADDITIVE and MULTIPLICATIVE interaction

  37. Derivation of formula for expected joint OR RR-+ RR++ RR+- 1.0 1.0 1.0 If disease is “rare” (e.g., <5%): observed

  38. 3.5 EXCA 2.5 2.0 EXCZ EXCZ EXCA BL BL BL Two baselines! OR+- OR-+ Exp’d OR++ [EXCA+BL] + [EXCZ+BL] - BL Baseline + Excess due to A Baseline + Excess due to Z One baseline has to be removed Derivation of formula: Expected OR++ = OR+- + OR-+ - 1.0 Intuitive graphical derivation: OR 1.0 BL OR-- Baseline Expected OR++= OR+- + OR-+ - 1.0

  39. OR Observed OR++ 3.5 3.5 2.5 2.0 1.0 OR-- OR-+ OR+- Exp’d OR++ Conclude: If the observed joint OR is the same as the expected under the additive model, there is no additive interaction

  40. Excess due to interaction (“interaction term”) Excess due to the joint effects of A and Z Observed OR++ 6.0 OR 3.5 2.5 2.0 1.0 OR-- OR-+ OR+- Exp’d OR++ Conclude: If the observed joint OR is different than the expected under the additive model, there is additive interaction

  41. Effect Modification Strategy 1.0 1.0 Odds Ratios for the association among isolated clubfoot, maternal smoking, and a family history of clubfoot, Atlanta, Georgia, 1968-80 (Honein et al. Family history, maternal smoking, and clubfoot: an indication of gene-environment interaction. Am J Epidemiol 2000;152:658-65.)

  42. Effect Modification Strategy 1.0 1.0 Odds Ratios for the association among isolated clubfoot, maternal smoking, and a family history of clubfoot, Atlanta, Georgia, 1968-80 Two reference categories (Honein et al. Family history, maternal smoking, and clubfoot: an indication of gene-environment interaction. Am J Epidemiol 2000;152:658-65.)

  43. Second Strategy: Comparison between joint expected and joint observed effects -- allows assessment of both ADDITIVEandMULTIPLICATIVE interactions-- 1.0 1.0 Odds Ratios for the association among isolated clubfoot, maternal smoking, and a family history of clubfoot, Atlanta, Georgia, 1968-80 (Honein et al. Family history, maternal smoking, and clubfoot: an indication of gene-environment interaction. Am J Epidemiol 2000;152:658-65.)

  44. Second Strategy: Comparison between joint expected and joint observed effects -- allows assessment of both ADDITIVEandMULTIPLICATIVE interactions-- 1.0 1.0 Odds Ratios for the association among isolated clubfoot, maternal smoking, and a family history of clubfoot, Atlanta, Georgia, 1968-80 (Honein et al. Family history, maternal smoking, and clubfoot: an indication of gene-environment interaction. Am J Epidemiol 2000;152:658-65.) Independent effect of family history (i.e., in the absence of maternal smoking)

  45. Second Strategy: Comparison between joint expected and joint observed effects -- allows assessment of both ADDITIVEandMULTIPLICATIVE interactions-- 1.0 1.0 Odds Ratios for the association among isolated clubfoot, maternal smoking, and a family history of clubfoot, Atlanta, Georgia, 1968-80 (Honein et al. Family history, maternal smoking, and clubfoot: an indication of gene-environment interaction. Am J Epidemiol 2000;152:658-65.) Independent effect of maternal smoking (i.e., in the absence of family history)

  46. Second Strategy: Comparison between joint expected and joint observed effects -- allows assessment of both ADDITIVEandMULTIPLICATIVE interactions-- 1.0 1.0 Odds Ratios for the association among isolated clubfoot, maternal smoking, and a family history of clubfoot, Atlanta, Georgia, 1968-80 (Honein et al. Family history, maternal smoking, and clubfoot: an indication of gene-environment interaction. Am J Epidemiol 2000;152:658-65.) Joint effect of family history and maternal smoking

  47. Second Strategy: Comparison between joint expected and joint observed effects -- allows assessment of both ADDITIVEandMULTIPLICATIVE interactions-- 6.26 1.0 1.45 + 5.81 – 1.0= 1.0 Odds Ratios for the association among isolated clubfoot, maternal smoking, and a family history of clubfoot, Atlanta, Georgia, 1968-80 Yes (Honein et al. Family history, maternal smoking, and clubfoot: an indication of gene-environment interaction. Am J Epidemiol 2000;152:658-65.) Joint effect of family history and maternal smoking Independent effect of family history (i.e., in the absence of maternal smoking) Independent effect of maternal smoking (i.e., in the absence of family history) Conclude: Since the observed joint OR(20.3) is different from the joint OR expected under the additive model (6.26), there is additive interaction

  48. Under ADDITIVE MODEL:Exp’d OR++ =OR+- + OR-+ - 1.0 Case-Control Study Second strategy to assess interaction: comparison between joint observed and joint expected effects Layout of table to assess both ADDITIVE and MULTIPLICATIVE interaction Under MULTIPLICATIVE MODEL: Exp’d OR++ =OR+-  OR-+

  49. Second Strategy: Comparison between joint expected and joint observed effects -- allows assessment of both ADDITIVEandMULTIPLICATIVE interactions-- 8.42 1.0 5.81 x 1.45= 1.0 Odds Ratios for the association among isolated clubfoot, maternal smoking, and a family history of clubfoot, Atlanta, Georgia, 1968-80 Yes (Honein et al. Family history, maternal smoking, and clubfoot: an indication of gene-environment interaction. Am J Epidemiol 2000;152:658-65.) Joint effect of family history and maternal smoking Independent effect of family history (i.e., in the absence of maternal smoking) Independent effect of maternal smoking (i.e., in the absence of family history) Conclude: Since the observed joint OR(20.3) is different from the joint OR expected under the multiplicative model (8.4), there is multiplicative interaction. This inference is consistent with the inference made based on the effect modification strategy (heterogeneity of odds ratios when examining strata of family history).

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