Bias

1. Bias

2. Every epidemiological study should be viewed as a measurement exercise Kenneth J. Rothman, 2002

3. What epidemiologists �measure� Rates, risks Effect measures Rate Ratio Odds ratio ....... yet these are just estimates of the �true� value the amount of error cannot be determined

4. Objective of this session Define bias Present types of bias and influence on estimates in our studies Identify methods to prevent bias

5. Should I believe the estimated effect?

6. Errors (a review) Two broad types of error Random error: variability in our data that we cannot easily explain Chance? Systematic error (Bias)

8. Errors in epidemiological studies

9. Categories of bias Selection bias Information bias [Confounding]

10. Selection bias Errors in selecting the study population When ? Inclusion in the study How ? Preferential selection of subjects related to their Disease status cohort Exposure status case control

11. Selection bias When? How? Consequences?

12. Types of selection bias Sampling bias Ascertainment bias surveillance referral, admission Diagnostic Participation bias self-selection (volunteerism) non-response, refusal healthy worker effect, survival

13. Selection bias in case-control studies

14. Selection bias How representative are hospitalised trauma patients of the population which gave rise to the cases?

15. Selection bias Higher proportion of controls drinking alcohol in trauma ward than in non-trauma

16. SB: Diagnostic bias OC use ? breakthrough bleeding ? increased chance of detecting uterine cancer

17. Prof. �Pulmo�, head respiratory department, 145 publications on asbestos/lung cancer SB: Admission bias

18. SB: Survival bias Contact with risk �hospital� leads to rapid death

19. SB: Non-response bias Controls chosen among women at home: 13000 homes contacted ?1060 controls

20. Selection bias in cohort studies

21. SB: Healthy worker effect

22. Healthy worker effect

23. Non-response bias

24. SB: Non-response bias

25. Non-response bias

26. SB: Loss to follow-up Difference in completeness of follow-up between comparison groups e.g. study of disease risk in migrants

27. Minimising selection bias Clear definition of study population Explicit case and control definitions Cases and controls from same population Selection independent of exposure Selection of exposed and non-exposed without knowing disease status

28. Categories of bias Selection bias Information bias

29. Information bias Systematic error in the measurement of information on exposure or outcome When? During data collection How? Differences in accuracy of exposure data between cases and controls of outcome data between exposed and unexposed

30. Information bias When? How? Consequences?

31. Information bias: misclassification Measurement error leads to assigning wrong exposure or outcome category

32. Nondifferential misclassification Misclassification does not depend on values of other variables Exposure classification NOT related to disease status Disease classification NOT related to exposure status Consequence if there is an association, weakening of measure of association �bias towards the null�

33. Nondifferential misclassification Cohort study: Alcohol ? laryngeal cancer

34. Two main types of information bias Reporting bias Recall bias Prevarication Observer bias Interviewer bias Biased follow-up

35. Mothers of children with malformations remember past exposures better than mothers with healthy children IB: Recall bias

36. IB: Prevarication bias Relatives of dead elderly may deny isolation

37. Investigator may probe listeriosis cases about consumption of soft cheese (knows hypothesis) IB: Interviewer bias

38. IB: Biased follow-up Unexposed less likely diagnosed for disease than exposed

39. Minimising information bias Standardise measurement instruments Administer instruments equally to cases and controls exposed / unexposed Use multiple sources of information questionnaires direct measurements registries case records Cross reference information sources!!! Use multiple controls

40. Questionnaire Favour closed, precise questions; minimise open-ended questions Seek information on hypothesis through different questions Disguise questions on hypothesis in range of unrelated questions Field test and refine Standardise interviewers� technique through training with questionnaire

41. Bias Should be prevented !!!! At PROTOCOL stage Difficult to correct for bias at analysis stage

42. References

43. Last word Scepticism is the chastity of the intellect � Don�t give it away to the first attractive hypothesis that comes along (MB Gregg)

44. Bias in randomised controlled trials Gold-standard: randomised, placebo-controlled, double-blinded study Least biased Exposure randomly allocated to subjects - minimises selection bias Masking of exposure status in subjects and study staff - minimises information bias

45. Bias in prospective cohort studies Loss to follow up The major source of bias in cohort studies Assume that all do / do not develop outcome? Ascertainment and interviewer bias Some concern: Knowing exposure may influence how outcome determined Non-response, refusals Little concern: Bias arises only if related to both exposure and outcome Recall bias No problem: Exposure determined at time of enrolment

46. Bias in retrospective cohort & case-control studies Ascertainment bias, participation bias, interviewer bias Exposure and disease have already occurred ? differential selection / interviewing of compared groups possible Recall bias Cases (or ill) may remember exposures differently than controls (or healthy)