1. Intermediate methods in observational epidemiology 2008 Instructor: Moyses Szklo Bias

2. Eliminate alternative explanations; Hill’s criteria Causal relationship Quality assurance and Quality control Bias* Experimental design; adjustmentConfounding* Estimation of precision (95% confidence interval) and testing (p)‏ Random variability Assessment StrategyExplanation Possible Explanations for an Association Between a Risk Factor and a Disease

3. Eliminate alternative explanations; Hill’s criteria Causal relationship Quality assurance and Quality control Bias* Experimental design; adjustmentConfounding* Estimation of precision (95% confidence interval) and testing (p)‏ Random variability Assessment StrategyExplanation Possible Explanations for an Association Between a Risk Factor and a Disease *Main threats to causal inference

4. 1. Definition of Bias

5. Average bias Statistical definition of bias: Bias occurs when the average of study results obtained from an infinite number of studies is not the true value TRUTH Study Results Frequency Average of Results Distribution of an Infinite Number of Studies

6. TRUTH Study Results Frequency Average of Results Distribution of an Infinite Number of Studies Bias vs. Representativeness Biased, but representative

7. TRUTH Study Results Frequency Average of Results Distribution of an Infinite Number of Studies Bias vs. Representativeness Valid, but not representative

8. Epidemiological Definition of Bias Last J: A Dictionary of Epidemiology, ed. by J. Last, 3rd Edition, IEA “Deviation of results or inferences from the truth, or processes leading to such deviation. Any trend in the collection, analysis, interpretation, publication, or review of data that can lead to conclusions that are systematically different from the truth.”

9. 2. Main types of bias a. Selection bias b. Information bias

10. 2. Main types of bias a. Selection bias

11. Reference Population (Study Base)‏ Selection Bias: One group (cell) in the study base (e.g., exposed cases) has a greater likelihood of inclusion in the study sample, unbeknownst to the investigator Study Sample CASESCONTROLS ab c d CASES CONTROLS Exposed Unexposed AB CD Total CasesTotal Controls SELECT SAMPLES OF TOTAL CASES AND CONTROLS a

12. Unbiased exposure odds in cases Unbiased exposure odds in controls Unbiased odds ratio Conclusions 50/50 ÷ 180/720= 4.0Odds Ratio 180:720 = 1:450:50 = 1:1Exposure Odds 900100Total 72050Absent 18050Present ControlsCasesRisk Factor A Total Reference Population “Gold Standard”: Total Population Study A. Hypothetical Case-Control Study Including All Cases and Controls (Non-Cases) of a Reference Population

13. Unbiased exposure odds in cases Unbiased exposure odds in controls Unbiased odds ratio Conclusions 50/50 ÷ 180/720= 4.0Odds Ratio 180:720 = 1:450:50 = 1:1Exposure Odds 900100Total 72050Absent 18050Present ControlsCasesRisk Factor A Total Reference Population “Gold Standard”: Total Population Study A. Hypothetical Case-Control Study Including All Cases and Controls (Non-Cases) of a Reference Population

14. Unbiased exposure odds in cases Unbiased exposure odds in controls Unbiased odds ratio Conclusions 25/25 ÷ 18/72 = 4.0Odds Ratio 18:72 = 1:425:25 = 1:1Exposure Odds 900 × 0.10= 90100 × 0.50= 50Total 720 × 0.10= 7250 × 0.50= 25Absent 180 × 0.10= 1850 × 0.50= 25Present ControlsCasesRisk Factor A Total Reference Population Unbiased Case-Control(Non-case) Study B. Hypothetical Unbiased Case-Control Study Based on Samples of 50% of Cases and 10% of Controls

15. Unbiased Sampling of Cases and Controls When sampling is unbiased, it is expected that the total sampling fraction of the case group and the total sampling fraction of the control group also apply to each exposure category That is, selection of cases and controls must be done independently of the exposure

16. Odds Ratio Exposure Odds 900 × 0.10= 90100 × 0.50= 50Total Absent Present ControlsCasesRisk Factor A Total Reference Population Unbiased Case-Control(Non-case) Study B. Hypothetical Unbiased Case-Control Study Based on Samples of 50% of Cases and 10% of Controls

17. Odds Ratio Exposure Odds 900 × 0.10= 90100 × 0.50= 50Total 720 × 0.10= 7250 × 0.50= 25Absent 180 × 0.10= 1850 × 0.50= 25Present ControlsCasesRisk Factor A Total Reference Population Unbiased Case-Control(Non-case) Study B. Hypothetical Unbiased Case-Control Study Based on Samples of 50% of Cases and 10% of Controls Sampling fractions in cells are the same as the sampling fractions for the totals

18. Unbiased exposure odds in cases Unbiased exposure odds in controls Unbiased odds ratio Conclusions 25/25 ÷ 18/72 = 4.0Odds Ratio 18:72 = 1:425:25 = 1:1Exposure Odds 900 × 0.10= 90100 × 0.50= 50Total 720 × 0.10= 7250 × 0.50= 25Absent 180 × 0.10= 1850 × 0.50= 25Present ControlsCasesRisk Factor A Total Reference Population Unbiased Case-Control(Non-case) Study B. Hypothetical Unbiased Case-Control Study Based on Samples of 50% of Cases and 10% of Controls Sampling fractions in cells are the same as the sampling fractions for the totals

19. Biased exposure odds in cases Unbiased exposure odds in controls Biased odds ratio Conclusions 30/20 ÷ 18/72 = 6.0Odds Ratio 18:72 = 1:430:20 = 1.5:1Exposure Odds 900 × 0.10= 90100 × 0.50= 50Total 720 × 0.10= 7250 × 0.40= 20Absent 180 × 0.10= 1850 × 0.60= 30Present ControlsCasesRisk Factor A Total Reference Population Biased Case-Control(Non-case) Study C. Hypothetical Biased Case-Control Study Based on Samples of 50% of Cases and 10% of Controls

20. Biased exposure odds in cases Unbiased exposure odds in controls Biased odds ratio Conclusions 30/20 ÷ 18/72 = 6.0Odds Ratio 18:72 = 1:430:20 = 1.5:1Exposure Odds 900 × 0.10= 90100 × 0.50= 50Total 720 × 0.10= 7250 × 0.40= 20Absent 180 × 0.10= 1850 × 0.60= 30Present ControlsCasesRisk Factor A Total Reference Population Biased Case-Control(Non-case) Study C. Hypothetical Biased Case-Control Study Based on Samples of 50% of Cases and 10% of Controls

21. Biased exposure odds in cases Unbiased exposure odds in controls Biased odds ratio Conclusions 30/20 ÷ 18/72 = 6.0Odds Ratio 18:72 = 1:430:20 = 1.5:1Exposure Odds 900 × 0.10= 90100 × 0.50= 50Total 720 × 0.10= 7250 × 0.40= 20Absent 180 × 0.10= 1850 × 0.60= 30Present ControlsCasesRisk Factor A Total Reference Population Biased Case-Control(Non-case) Study C. Hypothetical Biased Case-Control Study Based on Samples of 50% of Cases and 10% of Controls Sampling fractions for cells in the case group are not the same as total sampling fraction

22. Biased exposure odds in cases Unbiased exposure odds in controls Biased odds ratio Conclusions 30/20 ÷ 18/72 = 6.0Odds Ratio 18:72 = 1:430:20 = 1.5:1Exposure Odds 900 × 0.10= 90100 × 0.50= 50Total 720 × 0.10= 7250 × 0.40= 20Absent 180 × 0.10= 1850 × 0.60= 30Present ControlsCasesRisk Factor A Total Reference Population Biased Case-Control(Non-case) Study C. Hypothetical Biased Case-Control Study Based on Samples of 50% of Cases and 10% of Controls Sampling fractions for cells in the case group are not the same as total sampling fraction

23. Biased exposure odds in cases Unbiased exposure odds in controls Biased odds ratio Conclusions 30/20 ÷ 18/72 = 6.0Odds Ratio 18:72 = 1:430:20 = 1.5:1Exposure Odds 900 × 0.10= 90100 × 0.50= 50Total 720 × 0.10= 7250 × 0.40= 20Absent 180 × 0.10= 1850 × 0.60= 30Present ControlsCasesRisk Factor A Total Reference Population Biased Case-Control(Non-case) Study C. Hypothetical Biased Case-Control Study Based on Samples of 50% of Cases and 10% of Controls Sampling fractions for cells in the case group are not the same as total sampling fraction

24. Exposure odds equally biased in cases and controls Unbiased odds ratio Conclusions 30/20 ÷ 24:66 = 4.0Odds Ratio 24:66 = 1:2.730:20 = 1.5:1.0Exposure Odds 900 × 0.10= 90100 × 0.50= 50Total 720 × 0.09= 6650 × 0.40= 20Absent 180 × 0.13= 2450 × 0.60= 30Present ControlsCasesRisk Factor A Total Reference Population Unbiased Case-Control(Non-case) Study? B. Hypothetical Case-Control Study Based on Samples of 50% of Cases and 10% of Controls with Compensating Bias

25. Exposure odds equally biased in cases and controls Unbiased odds ratio Conclusions 30/20 ÷ 24:66 = 4.0Odds Ratio 24:66 = 1:2.730:20 = 1.5:1.0Exposure Odds 900 × 0.10= 90100 × 0.50= 50Total 720 × 0.09= 6650 × 0.40= 20Absent 180 × 0.13= 2450 × 0.60= 30Present ControlsCasesRisk Factor A Total Reference Population Unbiased Case-Control(Non-case) Study? B. Hypothetical Case-Control Study Based on Samples of 50% of Cases and 10% of Controls with Compensating Bias

26. Exposure odds equally biased in cases and controls Unbiased odds ratio Conclusions 30/20 ÷ 24:66 = 4.0Odds Ratio 24:66 = 1:2.730:20 = 1.5:1.0Exposure Odds 900 × 0.10= 90100 × 0.50= 50Total 720 × 0.09= 6650 × 0.40= 20Absent 180 × 0.13= 2450 × 0.60= 30Present ControlsCasesRisk Factor A Total Reference Population Unbiased Case-Control(Non-case) Study? B. Hypothetical Case-Control Study Based on Samples of 50% of Cases and 10% of Controls with Compensating Bias

27. Exposure odds equally biased in cases and controls Unbiased odds ratio Conclusions 30/20 ÷ 24:66 = 4.0Odds Ratio 24:66 = 1:2.730:20 = 1.5:1.0Exposure Odds 900 × 0.10= 90100 × 0.50= 50Total 720 × 0.09= 6650 × 0.40= 20Absent 180 × 0.13= 2450 × 0.60= 30Present ControlsCasesRisk Factor A Total Reference Population Unbiased Case-Control(Non-case) Study? B. Hypothetical Case-Control Study Based on Samples of 50% of Cases and 10% of Controls with Compensating Bias

28. = True OR Important to distinguish between: Validity of each measure of frequency (e.g., exposure odds in cases)‏ and Validity of measure of association (e.g., odds ratio)‏

29. Coffee Drinking and Cancer of the Pancreas (New Eng J Med 1981;304:630) Cases: Patients newly diagnosed with pancreatic cancer admitted to 11 Boston and Rhode Island hospitals during 1974-1980 (n= 369). Controls: Controls were matched to cases by attending physician, hospital, and timing of interview (n= 644). AN EXAMPLE OF UNCOMPENSATED BIAS

30. Odds Ratios for Cancer of the Pancreas According to Coffee Drinking and Smoking 2.71.81.0Total 1.23.81.81.0Current smokers 1.03.12.11.0Never Total 3+1-20 Smoking Coffee intake (cups/day)‏ (Adapted from MacMahon et al, New Eng J Med 1981;304:630)‏ Problem? Controls: Controls were matched to cases by attending physician, hospital, and timing of interview (n= 644). Controls mostly had gastrointestinal conditions, or cancers other than pancreatic and biliary tract (n= 644)‏

31. Odds Ratios for Cancer of the Pancreas According to Coffee Drinking and Smoking 2.71.81.0Total 1.23.81.81.0Current smokers 1.03.12.11.0Never Total 3+1-20 Smoking Coffee intake (cups/day)‏ (Adapted from MacMahon et al, New Eng J Med 1981;304:630)‏ Problem? Controls: Controls were matched to cases by attending physician, hospital, and timing of interview (n= 644). Controls mostly had gastrointestinal conditions, or cancers other than pancreatic and biliary tract (n= 644)‏

32. Reference Population (Study Base)‏ Study Sample CASESCONTROLS ab c d CASES CONTROLS Exposed Unexposed AB CD Total CasesTotal Controls SELECT SAMPLES OF TOTAL CASES AND CONTROLS d

33. 2. Types of Bias a.Selection bias b. Information bias and misclassification

34. 2. Types of Bias a.Selection bias b. Information bias and misclassification

35. Information bias in case-control studies: It usually results from misclassification of exposure information (there could also be misclassification of case-control status, although it is relatively rare)‏ Study Sample CASESCONTROLS ab c d Exposed Unexposed Non-differential misclassification Differential misclassification

36. Examples of Information Bias in Case-Control Studies Exposure Identification Bias –Recall Bias –Interviewer Bias Case-Control Status Bias –Diagnostic criteria error –Interviewer error

37. Example of Recall Bias in a Study of Melanoma (Weinstock et al, Am J Epidemiol 1991;133:240-5)‏ Healthy cohort Data collection (questionnaire)on tanning ability Time (cohort follow-up)‏ Loss Questionnaire on tanning ability repeated in cases and controls after each case occurred Case Height and width of column denote cohort size

38. 79:155 (1:1.9)‏ 9:25 (1:2.8)‏ Exposure Odds 1.60.7Odds Ratios Ascertainment of Exposure 1571915525Medium, average, deep or dark (unexp.)‏ 7715799No, or light tan (exposed)‏ ControlsCasesControlsCasesTanning Ability Post-melanomaPre-melanoma* Example of Recall Bias in a Case-Control Study of Melanoma (Weinstock et al, Am J Epidemiol 1991;133:240-245)‏ *Gold standard Interview on tanning ability pre-melanoma

39. 79:155 (1:1.9)‏ 1.60.7Odds Ratios 9:25 (1:2.8)‏ Exposure Odds Ascertainment of Exposure 1571915525Medium, average, deep or dark (unexp.)‏ 7715799No, or light tan (exposed)‏ ControlsCasesControlsCasesTanning Ability Post-melanomaPre-melanoma* Example of Recall Bias in a Case-Control Study of Melanoma +6 (Weinstock et al, Am J Epidemiol 1991;133:240-245)‏ *Gold standard Interview on tanning ability post-melanoma

40. 79:155 (1:1.9)‏ 1.60.7Odds Ratios 15:19 (1:1.3)‏ 9:25 (1:2.8)‏ Exposure Odds Ascertainment of Exposure 1571915525Medium, average, deep or dark (unexp.)‏ 7715799No, or light tan (exposed)‏ ControlsCasesControlsCasesTanning Ability Post-melanomaPre-melanoma* Example of Recall Bias in a Case-Control Study of Melanoma +6 +2 (Weinstock et al, Am J Epidemiol 1991;133:240-245)‏ *Gold standard Interview on tanning ability post-melanoma

41. 79:155 (1:1.9)‏ 77:157 (1:2.0)‏ 1.60.7Odds Ratios 15:19 (1:1.3)‏ 9:25 (1:2.8)‏ Exposure Odds Ascertainment of Exposure 1571915525Medium, average, deep or dark (unexp.)‏ 7715799No, or light tan (exposed)‏ ControlsCasesControlsCasesTanning Ability Post-melanomaPre-melanoma* Example of Recall Bias in a Case-Control Study of Melanoma +6 +2 (Weinstock et al, Am J Epidemiol 1991;133:240-245)‏ *Gold standard Interview on tanning ability post-melanoma

42. 79:155 (1:1.9)‏ 77:157 (1:2.0)‏ 1.60.7Odds Ratios 15:19 (1:1.3)‏ 9:25 (1:2.8)‏ Exposure Odds Ascertainment of Exposure 1571915525Medium, average, deep or dark (unexp.)‏ 7715799No, or light tan (exposed)‏ ControlsCasesControlsCasesTanning Ability Post-melanomaPre-melanoma* Example of Recall Bias in a Case-Control Study of Melanoma +6 +2 (Weinstock et al, Am J Epidemiol 1991;133:240-245)‏ *Gold standard Interview on tanning ability post-melanoma

43. Types of Misclassification The type of misclassification is based on the notions of sensitivity and specificity: –Non-differential –Differential

44. To investigate the validity of self-reported acquired immunodeficiency syndrome (AIDS) symptoms in women with HIV infection, the authors compared the self-reported occurrence of AIDS-specific diagnoses with AIDS diagnoses reported by physicians, and documented by AIDS surveillance registries. (Hessel et al, Am J Epidemiol 2001;153:1128-1133)‏ “Test” “Gold Standard”

45. Sensitivity and Specificity of Diagnosis of Esophageal Candidiasis in AIDS patients Sensitivity: 46% Specificity: 84% (Adapted from: Hessol et al, Am J Epidemiol 2001;153:1128)‏

46. Hypothetical example: relationship between AIDS and esophageal candidiasis: “Gold Standard” 1,000500Total 1.0995480Absent 8.3520Present Odds Ratio Normal controls AIDS cases Esophageal candidiasis

47. Definitions of Sensitivity and Specificity Used for the Evaluation of Misclassification Sensitivity –Proportion of all truly infected (exposed) individuals correctly classified by the study Specificity –Proportion of all truly uninfected (unexposed) individuals correctly classified by the study MISCLASSIFICATION Non-differential: Sensitivity and specificity of exposure ascertainment are the same in cases and controls Differential: Sensitivity or specificity of exposure ascertainment differs between cases and controls

48. Relation Between AIDS and Esophageal Candidiasis Ascertained by Self- Reports (Questionnaire) with Sensitivity= 46% and Specificity= 84%. Assume non-differential misclassification (20/480)/(5/995)= 8.3Odds Ratio 1 000500Total 995480Absent 520Present ControlsCasesRegistry True Results (Gold Standard)‏

49. Relation Between AIDS and Esophageal Candidiasis Ascertained by Self- Reports (Questionnaire) with Sensitivity= 46% and Specificity= 84%. Assume non-differential misclassification (20/480)/(5/995)= 8.3Odds Ratio 1 000500Total 995480Absent 520Present ControlsCasesRegistry True Results (Gold Standard)‏

50. 50048020Total 41440311Absent 86779Present StudyAbsentPresentSelf-report of cases Truth in Cases Relation Between AIDS and Esophageal Candidiasis Ascertained by Self- Reports (Questionnaire) with Sensitivity= 46% and Specificity= 84%. Assume non-differential misclassification (20/480)/(5/995)= 8.3Odds Ratio 1 000500Total 995480Absent 520Present ControlsCasesRegistry True Results (Gold Standard)‏

51. 50048020Total 41440311Absent 86779Present StudyAbsentPresentSelf-report of cases Truth in Cases Relation Between AIDS and Esophageal Candidiasis Ascertained by Self- Reports (Questionnaire) with Sensitivity= 46% and Specificity= 84%. Assume non-differential misclassification (20/480)/(5/995)= 8.3Odds Ratio 1 000500Total 995480Absent 520Present ControlsCasesRegistry True Results (Gold Standard)‏

52. 50048020Total 41440311Absent 86779Present StudyAbsentPresentSelf-report of cases Truth in Cases 1 0009955Total 8398363Absent 1611592Present StudyAbsentPresentSelf-report of controls Truth in Controls Relation Between AIDS and Esophageal Candidiasis Ascertained by Self- Reports (Questionnaire) with Sensitivity= 46% and Specificity= 84%. Assume non-differential misclassification (20/480)/(5/995)= 8.3Odds Ratio 1 000500Total 995480Absent 520Present ControlsCasesRegistry True Results (Gold Standard)‏

53. 50048020Total 41440311Absent 86779Present StudyAbsentPresentSelf-report of cases Truth in Cases 1 0009955Total 8398363Absent 1611592Present StudyAbsentPresentSelf-report of controls Truth in Controls (86/414)/(161/839)= 1.1 Odds Ratio 1 000 500Total 839414Absent 16186Present ControlsCasesSelf-report Misclassified Results Relation Between AIDS and Esophageal Candidiasis Ascertained by Self- Reports (Questionnaire) with Sensitivity= 46% and Specificity= 84%. Assume non-differential misclassification (20/480)/(5/995)= 8.3Odds Ratio 1 000500Total 995480Absent 520Present ControlsCasesRegistry True Results (Gold Standard)‏ Non-differential misclassification with 2 exposure categories dilutes the association strength (Odds Ratio becomes closer to 1.0)‏

54. Examples of Differential Misclassification in a Case-Control Study. True Odds Ratio= 3.86; Prevalence of Exposure in Controls= 0.10 4.430.900.701.00 0.700.901.00 2.221.00 0.900.60 5.791.00 0.600.90 Odds Ratio ControlsCasesControlsCases SpecificitySensitivity Exposure Ascertainment

55. When the exposure is a continuous variable  Regression towards the Mean  Regression Dilution Bias Example: Hypertension as the exposure in a case-control examining its role in stroke A Bias Resulting in Non-Differential Misclassification

56. 135 145 140 Example of Regression Dilution (misclassification) Bias: Systolic Blood Pressure Intra-Individual Variability for a Case and a Control in a Case-Control Study of Stroke with Hypertension (Systolic Blood Pressure  140 mmHg) as the Exposure Time of measurement S B P (mm Hg)‏ Average case Average Control Time Cut-off point for definition of exposure Case incorrectly classified as unexposed Control incorrectly classified as exposed

57. Solutions to Regression Towards the Mean (Regression Dilution) Bias Best: Take several measurements and use the average. Use extreme values (i.e., increase specificity of definition of cases and controls). For example, define exposed as SBP  160 mmHg and unexposed as SBP <100 mmHg – Problem:   problems with generalizability (external validity) of results. Correct for regression dilution bias statistically.

58. 2. Types of Bias a. Selection bias b. Information bias and misclassification c. Mixed biases - Prevalence-Incidence bias - Temporal bias

59. 489339Total 1.6, 51.09.019DES 2.5, 7.54.31856Conjugated Reference1.0390274None 95% confidence intervals Odds Ratios No. of controls No. of cases Type of estrogen Number of Cases and Controls, and Odds Ratios for Endometrial Cancer According to Type of Estrogen Replacement Therapy, with 95% Confidence Intervals (Antunes et al, NEJM 1979)‏

60. Undiagnosed Endometrial Cancer Estrogen Use  Endometrial Cancer? Feinstein & Horowitz’ criticism or…? Bleeding Diagnosis of Endometrial Cancer Visit to gynecologist Estrogen Use Endometrial Cancer  Estrogen Therapy? (“Reverse Causality”)‏ Solution? Consider only cases and controls in whom estrogen was prescribed for prophylactic reasons (e.g., prevention of osteoporosis or menopausal symptoms)‏