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Bias and Confounder

Asst. Prof. Mathuros Tipayamongkholgul, PhD

Department of Epidemiology,

Faculty of Public Health

Mahidol University

Do you believe in this statement?

• Smokers has higher risk of liver cancer than non-smoker by 4 times.

• Lack of physical activity increased risk of CHD by 10 times.

It would be probably true if the study has validity or

NO BIAS and NO CONFOUNDER.

Objectives of Epidemiologic Research

To examine magnitude of the problems

– Prevalence of CKD in DM patient

– Proportion of CKD with appropriated care

To identify magnitude of association between factors and outcome

– Smoking increase risk of Lung cancer

– Different treatment cause different survival time

Study Validity

Distortion

Observed value

True value

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Validity in Epidemiologic research

• External validity (Generalization)

• Internal validity (how close study findings are to the TRUTH )

To identify association between DM and CKD

Effect

• CKD• Disease• Death• Intermediate outcomes

• CD4+ count• Underlying disease

Cause

• DM• Exposure• Risk factor• Covariate

• Age• Gender• Smoking

Threats to Internal Validity

A study’s internal validity can be compromised by three things….

I. Chance/Random error

II. Bias

III. Confounder

Chance error

• Measurements are based on a sample.

• Number of selected samples is important for the validity of the measurements

• Number of sample == Validity

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Sample 1: prevalence = 0%

Sample 2: prevalence = 20%

Sample 3: prevalence = 40%Population: prevalence = 20%

I. Chance error: Sampling I. Chance: Precision of CI

Larger sample size provides more narrow interval

N=1000 : 30% (95%CI 25 - 36%)

N=100 : 30% (95% CI 9 - 58 %)

30%

N = 1000

N = 100

I. Chance: P-value

• For comparison of 2 or more

• Tell the probability (percentage) of a wrong conclusion of study result

• Association between

– Number coffee drinking per day

– Developing CA stomach

– RR = 3.6

- c2 , P value = 0.35

II. BiasBIAS Systematic deviation of results or inferences from

truth.

Processes leading to such deviation. An error in the conception and design of a study—or in the collection, analysis, interpretation, reporting, publication, or review of data—leading to results or conclusions that are systematically (as opposed to

randomly) different from truth (Portal, 2008 A dictionary of

Epidemology 5th ed.)

Note: Chance is random error -- not systematic.

Therefore, tests exist based on probability

There is no way to correct for bias later!

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II. Bias

Systematic error is caused by 2 main steps:

I. Selection of study sample (Selection bias)

II. Inaccuracy of exposure or outcome measurements (Information bias)

II. Bias

• Wrong selection of comparison groups

• Selecting in different ways

• Give you the wrong answer for the association

• A mistaken estimate of an exposure’s effect on the risk of a disease

Selection Bias:Unrepresentative nature of sample

Cancer of the pancreas VS Coffee consumptionExample:

Cases: Histological confirmed diagnosis of

pancreatic cancer

Controls: Hospitalized patients admitted during

the same time as cases

OR of drinking coffee > 5 cups/day = 2.6

Do you agree with the results? Why?

Selecting Controls

• Coffee and pancreatic cancer, MacMahon B et al. NEJM 1981

– Coffee consumption was associated with pancreatic cancer

– Controls were selected from other patients admitted to the

hospital by the same physician as the case, often

gastroenterologist

– This specialist would admit patients with other diseases

(gastritis or esophagitis) for which he or the patient would

reduce coffee intake

– Controls intake of coffee not representative of population at

risk

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Pancreatic CA No Pancreatic CA

Coffee Consumption

Unrealistically Odds Ratio (BIAS)

NO Coffee Consumption

Case Control

Exposed

Not Exposed

A B

C D

Information Bias

• Interview mothers about the history of x-ray exposure comparing between 2 groups

• A mother who had a child with a birth defect often tries to identify some unusual event that occurred during her pregnancy with that child.

• While a mother with a normal child do not try that much.

Malformation+ No Malformation

Hx of radiation

No Hx of radiation

Unrealistically Odds Ratio (BIAS)

Case Control

Exposed

Not Exposed

A B

C D

III. Confounder

• An observed significant association may be

attributable to another unconsidered factor.

• Alcohol Drinking VS Lung Cancer

• The third variable Cigarette smoking

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III. Confounder

• The third factors affected the association;

– Confounder

– Effect modifier or Interaction

Alcohol VS Lung Cancer

CA Lung+ CA Lung-

Alcohol+ 71 52

Alcohol- 29 48

100 100

OR = 71x48 = 2.352x29

•This effect is from an unbiased Case-Control study•It is a true effect from the study But is it OK to report this result?

Alcohol VS CA Lung

• Is it possible that the obtained association was actually due the effect of the other factor?

• In the reality Alcohol may not lead people to develop CA Lung.

• Alcohol is just a coincidence of the other true association!!!!

• Let’s think about the effect of Smoking on this association

CA Lung+

CA Lung-

Alcohol+

71 52

Alcohol-

29 48

100 100

OR = 71x48 = 2.352x29

CA Lung+

CA Lung-

Alcohol+ 63 36

Alcohol- 7 4

70 40

OR = 1

SMOKE NON-SMOKE

CA Lung+

CA Lung-

Alcohol+ 8 16

Alcohol- 22 44

30 60

OR = 1

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III. Confounder

• Smoking Alcohol Drinking

• Smoking CA Lung

• Smoking is a confounder for the association between Alcohol and CA lung

III. Confounder

• Association between CHD and Smoking

smokers nonsmokers

CHD 305 58 363

no CHD 345 292 637

650 350 1000

• RR = 2.8

III. Confounder

• Gender M/F might be a confounder of the association

• Gender CHD

• Gender Smoking

What is the RR among Men?

What is the RR among Women?

Calculate stratum-specific measures of association...

STRATUM 1: MEN

smkrs nonsmkrs

CHD 300 50 350

NO CHD 300 150 450

600 200 800

STRATUM 2: WOMEN

smkrs nosmkrs

CHD 5 8 13

NO CHD 45 142 187

50 150 200

RR = 2.0

RR = 1.9

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IS THERE A CONFOUNDER?

CRUDE RR for smoking and CHD =2.8

STRATUM-SPECIFIC RR for smoking and CHD with gender as a potential confounder...

MEN RR = 2.0

WOMEN RR = 1.9

Do Breslow- Day tests

Gender confounds the association between smoking and CHD because the crude RR of 2.8 is NOT the same as the stratum-specific RR’s of approx. 2.0

roughly the same

Smoking VS CHD

• Smoking CHD : RR = 2.8 (Crude RR)

• After adjusting for gender

• Smoking CHD : RR ~ 2 (Adjusted RR)

• Gender confound the association between smoking and CHD

• Gender or Sex increases the effect of smoking

CONTROL FOR CONFOUNDERS

• Review for the potential confounder of the association you are going to find.

• Restriction

• Matching (in case-control study)– Matched by Smoking status

– Matched by Gender

• Stratified analysis Mantel Haenszel Method

• Multivariate analysis

Criteria of Confounder

• Related to the disease outcome

• Related to the exposure

SMOKING CA Lung

OR or RR > 1

SMOKING Alcohol

OR or RR > 1

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Criteria of Confounder

• Not be an intermediate of the association between the exposure and the outcome

CHDHigh Fat Diet

Serum Cholesterol

IV. Effect Modification

• In the process of stratification to look at the RR or OR in each subgroup, what is the explanation when the RRs or ORs in each subgroup are not the same?

IV. Effect Modification

• You were going to find the association between Aflatoxin and liver cancer

• You conducted a cohort study

• Crude RR of Aflatoxin = 5.8

• You would like to know if HBsAG was a confounder for the association or not

• You performed STRATIFIED ANALYSIS

CA Liver+

CA Liver-

Aflatoxin +

Aflatoxin -

1000 1000

RR = 5.8

OR = 3.4

HBsAg-

CA Liver+

CA Liver-

Aflatoxin +

Aflatoxin -

OR = 8.3

HBsAg+

CA Liver+

CA Liver-

Aflatoxin +

Aflatoxin -

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IV. Effect Modification

• Crude RR; Aflatoxin:CA Liver = 5.8

• Stratum specific: HBs Ag +– RR = 3.4

• Stratum specific: HBs Ag -– RR = 8.3

• HBs Ag is not the confounder of the association (3.4 ≠ 8.3 ; not homogeneous)

• HBs Ag is the effect modifier of the association• No adjustment required• Report stratum specific RR

IV. Effect Modification

Hbs Ag

CA LiverAflatoxin

Exercise

• You are interested in the association of non-regular exercise during young adult and MI

• What is your method to identify the association?

• Design?

• Outcome of interest?

• Exposure of interest?

• Measurement of association of interest?

Exercise

• The Crude OR of non regular exercise on the development of MI = 3.5

• What do you need to do before reporting the result?

• What is the potential confounders?

– Smoking

– Diet

– Age

– Gender

MINon Reg Excs

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Exercise

• Crude OR = 3.5 (Non-reg Excs VS MI)

• Stratified Analysis for Smoking status

• Among Smoke+; OR = 1.80

• Among Smoke-; OR = 1.78

• What is your conclusion?

SMOKING

MINon Reg Excs

ORMH = 1.79

Exercise

• What is the potential confounders?

– Smoking

– Diet

– Age

– Gender

Exercise

Crude OR = 3.5 (Non-reg Excs VS MI)

Stratified Analysis for Smoking status

Among Men; OR = 4.8

Among Women; OR = 1.7

What is your conclusion?

Exercise

• The effect of Non-regular exercise during young adult on the development of MI was different in each gender

• The effect was higher among Men than Women.

• Among men, those who had a history of non-regular exercise during young adult had 4.8 times more likely to develop MI than those who had a history of regular exercise

• Among women, those who had a history of non-regular exercise during young adult had 1.7 times more likely to develop MI than those who had a history of regular exercise

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CONTROL FOR CONFOUNDERS

• Review for the potential confounder of the association you are going to find

• Restriction.

• Matching (in case-control study)– Matched by Smoking status

– Matched by Gender

• Stratified analysis Mantel Haenszel Method

• Multivariate analysis