1. Classification Schemes for Error in Clinical Research  Szklo and Nieto –Bias »Selection Bias »Information/Measurement Bias –Confounding –Chance  Other Common Approach –Bias »Selection Bias »Information/Measurement Bias »Confounding –Chance

2. Confounding and Interaction I  Confounding: one of the central problems in observational clinical research –What is it? What does it do? –What kind of variables act as confounders? –Which variables to consider as confounders? –Which variables not to consider as confounders? »Emphasis on specifying the research question

3. Smoking, Matches, and Lung Cancer  A tobacco company researcher believes that exposure to matches is the cause of lung cancer  He conducts a large case-control study to test this hypothesis

4. Smoking, Matches, and Lung Cancer  The researcher has located 1000 cases of lung cancer from a population-based registry, of whom 820 have a history of carrying matches.  Among 1000 reference (control) patients (selected randomly from the population and determined to have normal chest x-rays), 340 carry matches.  Quantitate the relationship between matches and lung cancer in your colleague’s data.

5. Matches and Lung Cancer  Exposure odds ratio = (820/180) / (340/660) = disease odds ratio  OR = 8.8  95% CI (7.2, 10.9)

6. Smoking, Matches, and Lung Cancer  You decide to look at the relationship between matches and lung cancer in the smokers separately from the non-smokers.  You find that among the 1000 cases, 900 are smokers and 810 (OF THE 900) carry matches.  Among the 1000 control patients, 300 are smokers and 270 (OF THE 300) carry matches.  Draw the necessary stratified tables and calculate the relevant measure of association

7. Smoking, Matches, and Lung Cancer Stratified Crude Non-SmokersSmokers OR crude OR CF+ = OR smokers OR CF- = OR non - smokers  Stratification produces two 2-by-2 tables  In each stratum, all subjects are homogeneous with respect to smoking  We have adjusted or controlled for smoking  OR crude = 8.8 (7.2, 10.9)  OR smokers = 1.0 (0.6, 1.5)  OR non-smoker = 1.0 (0.5, 2.0)

8. Confounding: Smoking, Matches, and Lung Cancer  Illustrates how confounding can create an apparent effect even when there is no actual true effect –Can also be opposite: confounding can mask an effect when one is truly present  Proper terminology –In the relationship between matches and lung cancer, smoking is a confounding factor or a confounder –Smoking confounds the relationship between matches and lung cancer  In clinical research, confounding has a very specific meaning

9. Estes continues to be confounding puzzle Ray RATTO Ray RATTO SHAWN ESTES seemed loath to analyze his own performance last night, for fear that people would see the first three innings and use them to obscure the last four. But that's what made his outing so perfectly Estes-like -- an ongoing argument with himself that he eventually won. Well, an argument in which he held his own and his teammates won for him in the bottom of the ninth. Ramon Martinez lined a game-tying single with two outs, and Jeff Kent followed two batters later with a bases- loaded walk off Juan Acevedo to give the Giants a 2-1 victory against Colorado and move them to within 4 1/2 games of division leader Arizona. It was in many ways an eye-opening victory for a team that hadn't had one of this type for a while.

10.  Finding: “After an initial course of post-exposure prophylactic (PEP) medication following a sexual exposure to HIV infection, gay men reported a decrease in the practice of high-risk behavior over the following year.”  Reviewer: “Perhaps the men simply withheld the real amount of high-risk behavior they had in order to be eligible for future courses of PEP. How do you account for this confounding?”

11. Smoking, Matches, and Lung Cancer  The study is not over!  To be complete, you also decide to examine the relationship between smoking and lung cancer independent from the use of matches.  What tables should you construct to do this?

12. Smoking, Matches, and Lung Cancer Stratified Crude Matches Absent Matches Present OR crude OR CF+ = OR matches OR CF+ = OR no matches  OR crude = 21.0 (16.4, 26.9)  OR matches = 21.0 (10.7, 41.3)  OR no matches = 21.0 (13.1, 33.6)

13. Confounding: Smoking, Matches, and Lung Cancer  Interpretation?  What is the effect of matches on the relationship between smoking and lung cancer? Matches have no effect on the relationship  Effect of matches could have been predicted based on matches — lung cancer relationship –Illustrates one important component in the requirements of a confounder (aka a confounding factor) - A confounder must be associated with the outcome

14. Confounding: Examples of Magnitude and Direction Stratified (adjusted) Crude (unadjusted) Potential Confounder Absent Potential Confounder Present OR crude OR CF+ OR CF-

15. Nightlights Let there be light!

16. Nightlights and Myopia  Quinn et al. Nature 1999  Prevalence Ratio =

17.  Insert picture with nightlight off Lights are off and the stumbling around begins.

18. Nightlights and Myopia:  Two subsequent studies found no association and explained the prior result by confounding –Zadnik et al. and Gwiazda et al. Nature, 2000

19. Child’s Myopia Night Light Parental Myopia X X

20.  Insert picture with nightlight on again Let there be light (again)!

21. AZT to Prevent HIV After Needlesticks  Case-control study of whether post-exposure AZT use can prevent HIV seroconversion after needlestick (NEJM 1997) Crude OR crude = 0.61 (95% CI: 0.26 - 1.4) Interpretation? Could confounding be present? Interpretation? Could confounding be present?

22. HIV AZT Use Severity of Exposure ? ?

23. Adjustment for Confounder  Potential confounder: severity of exposure Minor Severity Major Severity Crude Stratified OR crude =0.61 OR adjusted = 0.30 (95% CI: 0.12 – 0.79) Negative Confounding

24. What kind of variables act as confounders?  Properties of a True Confounder –A true confounder (C) must be associated with: »the exposure (E) in question and »the disease (D) under study Confounder D D ANOTHER PATHWAY TO GET TO THE DISEASE ANOTHER PATHWAY TO GET TO THE DISEASE RQ: Is E associated with D independent of C?

25. C C ? ? E E D D Causal Diagrams  Formally called directed acyclic graphs (DAGs)  Frontier of epidemiologic theory  Use for identifying pitfalls of adjusting and not adjusting for certain variables (see text)

26. Lung Cancer Matches Smoking ? ? RQ: Are matches associated with lung cancer independent of smoking?

27. Properties of a True Confounder Refined Properties: Association with Exposure  A confounding variable can be either: – the cause of – the result of, or, – simply associated in a non-causal manner with the exposure in question Confounder D D

28. C causes E ? [via cardiovascular work-out] RQ: Is sexual activity associated with survival independent of general health?

29. Non-causal relationship between C and E Coronary Artery Disease Other Meds (e.g., ASA) Ca channel Blockers GI Bleeding ? RQ: Are Ca channel blockers associated with GI bleeding independent of other med use?

30. E causes C Poor Diet Poverty Mortality ? [access to care] RQ: Is poverty associated with survival independent of effects on diet?

31. Properties of a True Confounder Refined Properties: Association with Disease  A confounding variable must be associated with the disease. –It can be a “cause” of disease, or –associated in a non-causal manner Confounder D D

32. Hep B and C virus infection C causes D IDU Early Mortality ? [via bacterial infections] RQ: Is injection drug use associated with survival independent of effect on hepatitis infections?

33. Maternal Age Unknown biologic factor(s) C as a marker for D Birth Order Down Syndrome ? RQ: Is birth order associated with survival independent of maternal age?

34. General Health Unknown biologic factor(s) C as a marker for D Sexual Activity ? [via cardiovascular work-out] Mortality RQ: Is sexual activity associated with survival independent of general health?

35. Suicide Anti-depressant use in children Depression ? ?

36. Serious Head Injury Use of Helmets in Motorcyclists Safety- oriented Personality ? ? Safe Driving

37. Cardio- vascular Disease Anti-retroviral Drugs for HIV Aging ? ? Unknown Biological Factors

38. What is NOT a Confounder?  A variable that is an intermediate step in the causal path under study between the exposure in question and a disease is not a confounding variable. E E D D factor I Despite being associated with both exposure and outcome, Factor I is not a confounder It is on the pathway under study. It is an intermediary variable Despite being associated with both exposure and outcome, Factor I is not a confounder It is on the pathway under study. It is an intermediary variable

39. CCR5 and HIV Disease Progression CCR5 (receptor) defect AIDS  How should CD4 count be handled in assessing the association between CCR5 defect status and progression in HIV disease to AIDS? ? ?  CCR5: the human cellular receptor for HIV –found on CD4 cells  Genetic defects in CCR5 now described  CD4 count potent predictor of time-to-AIDS  CCR5: the human cellular receptor for HIV –found on CD4 cells  Genetic defects in CCR5 now described  CD4 count potent predictor of time-to-AIDS CD4 count

40. CCR5 and HIV Disease Progression CCR5 (receptor) defect AIDS  How should CD4 count be handled in assessing the association between CCR5 defect status and progression in HIV disease to AIDS? CD4 count  CCR5: the human cellular receptor for HIV –found on CD4 cells  Genetic defects in CCR5 now described  CD4 count potent predictor of time-to-AIDS  CCR5: the human cellular receptor for HIV –found on CD4 cells  Genetic defects in CCR5 now described  CD4 count potent predictor of time-to-AIDS

41. It depends upon the research question CCR5 defect ? [Other mechanisms] ? [CD4 count] AIDS #1: Is CCR5 associated with progression to AIDS, irrespective of mechanism? CCR5 defect Low CD4 count AIDS Do not adjust for CD4 count ! High CD4 count CD4 count Do Adjust ! #2: Is CCR5 associated with progression to AIDS, independent of CD4 count?

42. RQ 1: What if you did adjust for CD4 count? CCR5 defect AIDS #1: Is CCR5 associated with progression to AIDS, irrespective of mechanism? Low CD4 count High CD4 count If “via CD4 count” was only pathway, no effect for CCR5 would be observed after stratification ? [CD4 count]

43. Taylor et al. JAIDS 2003 CCR5 defect Other mechanism #2 ? ? CD4 count AIDS #1 CCR5 defect ? ? AIDS Do not adjust ! CD4 count Adjust ! Crude (unadjusted) association: - Relative hazard: 0.71 Crude (unadjusted) association: - Relative hazard: 0.71 Stratified (adjusted) by CD4 count - Relative hazard: 0.93 Stratified (adjusted) by CD4 count - Relative hazard: 0.93

44. Exercise and CAD  When evaluating the relationship between exercise and CAD, is HDL a confounder or an intermediary? Exercise CAD HDL cholesterol

45. It depends on the pathway under investigation  If interest is in a pathway other than through HDL, then HDL is a confounder  Therefore, HDL is extraneous to pathway under study  Confounding factors are extraneous factors Exercise CAD [not yet specified mechanism] HDL ? ?

46. Exercise and CAD  If HDL is on the pathway in question, then HDL is an intermediary variable.  e..g., Does exercise influence CAD risk in a newly studied population (elderly Asians)?  Hence, classification of HDL as confounder or intermediary depends upon the biological pathway under investigation Exercise CAD HDL is not a confounder here [HDL..+.. other mechanisms]

47. When Planning a Study, Which Factors Should be Considered as Potential Confounders?  With previously studied exposures-diseases: –consider/measure any factor for which prior evidence indicates is a confounder »e.g., effect of diet on CAD? must deal with smoking as potential confounder  When studying new exposures for which little is known: –plan on measuring ALL factors associated with the disease –i.e. If you don’t, you may regret it later  Confounding can be dealt with in the analysis phase of a study but NOT if the confounder is not measured

48. Seeking cause of high Marin cancer rates Activists canvass residents to search for trends Thousands of volunteers scattered across Marin County under baleful skies Saturday in an unprecedented grassroots campaign against the region's soaring cancer rate. Armed with surveys, some 2,000 volunteers went door to door in every neighborhood in the county.... The volunteers hope to collect enough money to hire an epidemiologist...