Bias

1
Bias
M.Valenciano, 2006 A. Bosman, 2005
T. Grein, 2001- 2004
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• Every epidemiological study should be viewed as a
  measurement exercise
• Kenneth J. Rothman, 2002

.. in order to understand the truth
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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 type of bias and influence in estimates
• Identify methods to prevent bias

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Should I believe my measurement?
Mayonnaise Salmonella
RR 4.3
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Errors

• Two broad types of error
• Random error reflects amount of variability
• Chance?
• Systematic error (Bias)

Definition of bias Any systematic error in
an epidemiological study resulting in an
incorrect estimate
of association between exposure and risk of
disease
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Errors in epidemiological studies
Error
Random error (chance)
Systematic error (bias)
Study size
Source Rothman, 2002
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Categories of bias

• Selection bias
• Information bias
• Confounding

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Selection bias

• Errors in the process of identifying
  the study population
• When ?
• Inclusion in the study
• How ?
• Preferential selection of subjects
  related to their
• Disease status cohort
• Exposure status case control

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Selection bias

• When?
• How?
• Consequences?

frequency of disease (cohort) frequency of
exposure (case control) different among
- those included in the study - those
eligible
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Types of selection bias

• Sampling bias
• Ascertainment bias
• surveillance
• referral, admission
• diagnostic
• Participation bias
• self-selection (volunteerism)
• non-response, refusal
• healthy worker effect, survival

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Selection bias in case-control studies
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Selection bias
e.g alcohol and cirrhosis?
OR 6

• How representative are hospitalised trauma
  patients of the
  population which gave rise to the cases?

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Selection bias
OR 6 OR 36

• Higher proportion of controls drinking alcohol
  in trauma ward
• than in non-trauma

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SB Diagnostic bias
Diagnostic approach related to knowing exposure
status e.g OC and uterine cancer?

• OC use ? breakthrough bleeding ? increased chance
  of detecting uterine cancer

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SB Admission bias
Exposed cases different chance of admission
than controls e.g asbestos and lung
cancer?

• Prof. Pulmo, head respiratory department,
  145 publications on
  asbestos/lung cancer

• Lung cancer cases exposed to asbestos
  not representative of lung
  cancer cases

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SB Survival bias
Only survivors of a highly lethal disease enter
study e.g. Hospital and haemorrhagic fever?

• Contact with risk hospital leads to rapid death

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SB Non-response bias

• Controls chosen among women at home
  13000 homes contacted ?1060 controls

• Controls mainly housewives with lower chance of
  test

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Selection bias in cohort studies
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SB Healthy worker effect
Source Rothman, 2002
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Healthy worker effect
Source Rothman, 2002
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Non-response bias
lung cancer yes no
Smoker 90 910
1000 Non-smoker 10 990
1000
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SB Non-response bias
lung cancer yes no
10 of smokers dare to respond
Smoker 9 91
100 Non-smoker 10 990
1000
No bias !
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Non-response bias
lung cancer yes no
Smoker 45 910
955 Non-smoker 10
990 1000
50 of cases that smokedlost to follow up
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SB Loss to follow-up

• Difference in completeness of follow-up between
  comparison groups
• Example
• study of disease risk in migrants
• migrants more likely to return to place of origin
  when having disease ? lost to follow-up?
  lower disease rate among exposed (migrant)

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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

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Categories of bias

• Selection bias
• Information bias

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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

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Information bias

• When?
• How?
• Consequences?

• Misclassification
• Study subjects are classified
  in the wrong category
• Cases / controls
• Exposed / unexposed

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Information bias misclassification

• Measurement error leads to assigning wrong
  exposure or outcome category

• Non-differential
• Random error
• Missclassifcation exposure EQUAL
  between cases and controls
• Missclassification outcome EQUAL
  between exposed nonexp.
• gt Weakness measure
  of association

• Differential
• Systematic error
• Missclassification exposure DIFFERS
  between cases and controls
• Missclassification outcome DIFFERS
  between exposed nonexposed
• gt Measure association
  distorted in any direction

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Two main types of information bias

• Reporting bias
• Recall bias
• Prevarication
• Observer bias
• Interviewer bias
• Biased follow-up

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IB Recall bias
Cases remember exposure differently than
controls e.g. risk of malformation

• Mothers of children with malformations remember
  past exposures better than
  mothers with healthy children

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IB Prevarication bias
Cases report exposure differently than
controls e.g. isolation and heat related death

• Relatives of dead elderly may deny isolation

• Underestimation a ? underestimation of OR

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IB Interviewer bias
Investigator asks cases and controls differently
about exposure e.g soft cheese and
listeriosis
Cases of
Controls
listeriosis
Eats soft cheese
a
b
Does not eat
c
d
soft cheese

• Investigator may probe listeriosis cases
  about consumption of
  soft cheese

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IB Biased follow-up

• Unexposed less likely diagnosed
• for disease than exposed

• Cohort study risk factors for mesothelioma
• Difficult histological diagnosis
• gt Histologist more likely
  to diagnose specimen as
  mesothelioma
• if asbestos exposure kown

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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

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Nondifferential misclassification

• Cohort study Alcohol ? laryngeal cancer

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Nondifferential misclassification

• Cohort study Alcohol ? laryngeal cancer

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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
• Use multiple controls

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Questionnaire (tomorrow)

• 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

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Bias

• Should be prevented !!!!
• protocol
• If bias
• incorrect measure of association
• should be taken into account
  in the interpretation of the results
• magnitude?
• overestimation? underestimation?

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References
Rothman KJ Epidemiology an introduction. Oxford
University Press 2002, 94-101 Smith (1984)
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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

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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

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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)

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Question to you

• Suppose a computer error in data entry
• Exposed group classified as unexposed
• Unexposed group classified as exposed
• What effect has this error on the result?
• Is it bias?
• If so what type
• If not, what type of error?