Fukushima Medical University Aya Goto Nguyen Quang Vinh Confounding and Bias Aya Goto Nguyen Quang Vinh

Key concepts Confounding  Indicative of true association. Can be controlled at the designing or analysis stage. Bias  Should be minimized at the designing stage. Random errors  Is the nature of quantitative data. Non-differential (random) misclassification  Is the nature of (inaccurate) measurement.

This is a revised version of an example given in a Supercourse lecture by Dr. Nigel Paneth from Michigan State University. http://www.pitt.edu/~super1/assist/topicsearch.htm EXAMPLES OF RANDOM ERROR, BIAS, MISCLASSIFICATION AND CONFOUNDING IN THE SAME STUDY: In a cohort study, babies of women who bottle feed and women who breast feed are compared, and it is found that the incidence of gastroenteritis, as recorded in medical records, is lower in the babies who are breast-fed.

EXAMPLE OF CONFOUNDING The mothers of breast-fed babies are of higher social class, and the babies thus have better hygiene, less crowding and perhaps other factors that protect against gastroenteritis. Crowding and hygiene are truly protective against gastroenteritis, but we mistakenly attribute their effects to breast feeding. This is called confounding because the observation is correct, but should be carefully interpreted to foresee the truth.

EXAMPLE OF BIAS The medical records of bottle-fed babies only are less complete (perhaps bottle fed babies go to the doctor less) than those of breast fed babies, and thus record fewer episodes of gastro-enteritis in them only. This is called bias because the observation itself is in error.

EXAMPLE OF RANDOM MISCLASSIFICATION EXAMPLE OF RANDOM ERROR By chance, there are more episodes of gastroenteritis in the bottle-fed group in the study sample. EXAMPLE OF RANDOM MISCLASSIFICATION Lack of good information on feeding history results in some breast-feeding mothers being randomly classified as bottle-feeding, and vice-versa. If this happens, the study finding underestimates the true RR.

“Mothers with unintended pregnancy tend to lose confidence.” Pregnancy intention Maternal confidence Pregnancy intention Maternal confidence Fist-time motherhood

Confounding Exposure Disease Confounder It occurs when there is a confounder, which is associated with both exposure and disease independently. Exposure Disease Confounder

http://www.amazon.co.jp/ Coffee-Cigarettes-Roberto- Benigni/dp/B0001XAO7U Does drinking coffee increase the risk of myocardial infarction? Coffee MI Smoking SLIDE 10

Control confounding at the designing stage Strategy Advantages Disadvantages Specification “Include only non-smokers.” Easily understood Limits generalizability May limit sample size Matching “Match smoking status of cases and controls” Useful for eliminating influence of strong constitutional confounders like age and sex Decision to match must be made when designing and can have irreversible adverse effects on analysis Time consuming Can not analyze associations of matched variables with the outcome

Control confounding at the analysis stage Strategy Advantages Disadvantages Stratification “Conduct analysis separately for smokers and non-smokers.” Easily understood Reversible May be limited by sample size for each stratum Difficult to control for multiple confounders Statistical adjustment “Conduct multivariate analysis controlling (adjusting) for smoking status.” Multiple confounders can be controlled. Need advanced statistical techniques Results may be difficult to understand

“Whichever method you choose, you have to know potential confounders reported in previous studies.”  Literature searching is important

Bias Selection bias Measurement bias Recall bias Observer bias Keys to a nicely designed study and collection of accurate data.

Selection bias Especially in case-control study, it occurs when cases and controls are selected related to exposure status. Example: Hospital-based case-control study on relationship of OC use and thromboembolism Cases (In-patients with thromboembolism) Controls Because physicians were already aware of a possible relationship between thromboembolism and OC use, patients with the disease were more likely admitted if they were using OC.

Obtained results: Relationship between thromboembolism and OC will be exaggerated. Method to minimize this selection bias Prepare and follow an established objective diagnostic criteria independent of exposure status for selecting cases.

NOTE for advance learners: Sampling is a different issue from selection bias. Prevalence of postpartum depression at Tu Du = Prevalence in HCMC? Pregnant women In HCMC Pregnant women delivering at Tu Du Hosp. Sampling influences generalizability (external validity) of the obtained results.

Is Reserpine a cause of breast cancer? All patients Patients at a hospital x Cases: Breast cancer patients Controls: Patients at the same hospital. (Except who have cardiovascular diseases to which Reserpine is likely to be prescribed.) Horwitz RI, Feinstein AR. Exclusion bias and the false relationship of reserpine and breast cancer. Arch Intern Med. 1985;145(10):1873-5. Selection bias influences internal validity of the obtained results.

Recall bias Especially in a case-control study, it occurs when disease status influences subjects’ recall of exposure status. Example: Case-control study on relationship of prenatal infections and congenital malformations. Cases (mothers of babies with defect) Controls (mothers of healthy babies) This bias can be minimized with using hospital control. They recall better about prenatal episode of infections since they tend to think about possible causes of their babies illness.

Method to minimize this recall bias Obtained results: Relationship between baby’s defect and prenatal infection will be exaggerated. Method to minimize this recall bias Consider using a hospital control. 2018/5/22

Observer bias Especially in a case-control study, it occurs when knowledge of disease status influences observer’s recording of exposure status. Example: Case-control study on relationship of OC & thromboembolism Cases (Out-patients with thromboembolism) Controls This bias can be minimized by blinding researcher of the disease status. Or by including dummy question on the use of other medicine, and compare obtained information with medical record. If cases and controls differ with respect to their reported use of OC but not in their use of the other drugs, these data would support the belief that the observed differences in reported OC use is biased. Physicians ask more carefully about OC use to women with symptoms of thromboembolism.

Obtained results: Relationship between thromboembolism and OC will be exaggerated. Method to minimize this observer bias  Hire interviewers. If investigators themselves are doing the interview, do it before diagnosing. Do not analyze the data until you collect all data.