Evaluating the Role of Bias

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Evaluating the Role of Bias
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Definition of Bias

• Bias is a systematic error that results in an
  incorrect (invalid) estimate of the measure of
  association
• A. Bias can create spurious association when
  there really is none (bias away from the null)
• B. Bias can mask an association when there
  really is one (bias towards the null)
• C. Bias is primarily introduced by the
  investigator or study participants

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Definition of Bias (contd)

• D. Bias does not mean that the investigator is
  prejudiced.
• E. Bias can arise in all study types
  experimental, cohort, case-control
• F. Bias occurs in the design and conduct of a
  study. It can be evaluated but not fixed in the
  analysis phase.
• G. Two main types of bias are selection and
  observation bias.

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Selection Bias

• A. Results from procedures used to select
  subjects into a study that lead to a result
  different from what would have been obtained from
  the entire population targeted for study
• B. Most likely to occur in case-control or
  retrospective cohort because exposure and outcome
  have occurred at time of study selection

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Selection Bias in a Case-Control Study

• A. Occurs when controls or cases are more (or
  less) likely to be included in study if they have
  been exposed -- that is, inclusion in study is
  not independent of exposure

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Selection Bias in a Case-Control Study

• B. Result Relationship between exposure and
  disease observed among study participants is
  different from relationship between exposure and
  disease in individuals who would have been
  eligible but were not included.
• The odds ratio from a study that suffers from
  selection bias will incorrectly represent the
  relationship between exposure and disease in the
  overall study population

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• Question Do PAP smears prevent cervical cancer?
  Cases diagnosed at a city hospital. Controls
  randomly sampled from household in same city by
  canvassing the neighborhood on foot. True
  relationship

OR (100)(100) / (150)(150) .44 There is a
54 reduced risk of cervical cancer among women
who had PAP smears vs. women who did not. (40
of cases had PAP smears versus 60 of controls)
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• Recall Cases from the hospital and controls come
  from the neighborhood around the hospital.
• Now for the bias Only controls who were at home
  at the time the researchers came around to
  recruit for the study were actually included in
  the study. Women at home were less likely to
  work and less likely to have regular checkups and
  PAP smears. Therefore, being included in the
  study as a control is not independent of the
  exposure.

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The resulting data are as follows
OR (100)(150) / (150)(100) 1.0 There is no
association between PAP smears and the risk of
cervical cancer. Here, 40 of cases and 40 of
controls had PAP smears.
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• Ramifications of using women who were at home
  during the day as controls
• These women were not representative of the whole
  study population that produced the cases. They
  did not accurately represent the distribution of
  exposure in the study population that produced
  the cases, and so they gave a biased estimate of
  the association.

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Selection Bias in a Cohort Study

• Selection bias occurs when selection of exposed
  and unexposed subjects is not independent of
  outcome (so, it can only occur in a retrospective
  cohort study)

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Selection Bias in a Cohort Study

• Example
• A retrospective study of an occupational exposure
  and a disease in a factory setting.
• The exposed and unexposed groups are enrolled on
  the basis of prior employment records.
• The records are old, and many are lost, so the
  complete cohort working in the plant is not
  available for study.
• If people who did not develop disease and were
  exposed were more likely to have their records
  lost, then there will be an overestimate of
  association between the exposure and the disease.

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True relationship, if all records were available
RR (50/1000) / (50/1000) 1.00
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200 records were lost, all among exposed who did
not get the disease
RR (50/800) / (50/1000) 1.25 If more records
were lost in this category (exposed subjects who
did not get the disease), the bias would be even
greater.
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Selection Bias What are the solutions?

• Little or nothing can be done to fix this bias
  once it has occurred.
• You need to avoid it when you design and conduct
  the study by, for example, using the same
  criteria for selecting cases and controls,
  obtaining all relevant subject records, obtaining
  high participation rates, and taking in account
  diagnostic and referral patterns of disease.

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Observation Bias

• An error that arises from systematic differences
  in the way information on exposure or disease is
  obtained from the study groups
• Results in participants who are incorrectly
  classified as either exposed or unexposed or as
  diseased or not diseased

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Observation Bias

• Occurs after the subjects have entered the study
• Several types of observation bias recall bias,
  interviewer bias, loss to follow up, and
  differential and non-differential
  misclassification

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Observation Bias

• Recall bias - People with disease remember or
  report exposures differently (more or less
  accurately) than those without disease.
• Can result in over- or under-estimate of measure
  of association.

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Observation Bias

• Solutions Use controls who are themselves sick
  use standardized questionnaires that obtain
  complete information, mask subjects to study
  hypothesis

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Classic recall biasCases underreport exposure
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Observation Bias

• Interviewer bias - Systematic difference in
  soliciting, recording, interpreting information.
• Can occur whenever exposure information is sought
  when outcome is known (as in case-control), or
  when outcome information is sought when exposure
  is known (as in cohort study).

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Observation Bias

• Interviewer bias
• Solutions mask interviewers to study hypothesis
  and disease or exposure status of subjects, use
  standardized questionnaires or standardized
  methods of outcome (or exposure) ascertainment

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Observation Bias

• Loss to follow up - A concern in cohort and
  experimental studies if people who are lost to
  follow up differ from those that remain in the
  study.
• Bias results if subjects lost differ from those
  that remain with respect to both the outcome and
  exposure.
• Solution Since that information cannot be known,
  you must achieve high and equal rates of follow
  up for the exposed and unexposed groups.

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Observation Bias

• Misclassification - Subjects exposure or disease
  status is erroneously classified.
• Two types of misclassification non-differential
  and differential. We will cover only the more
  common form non-differential misclassification.

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Observation Bias

• Non-differential misclassification
• Inaccuracies with respect to disease
  classification are independent of exposure.
• Or, inaccuracies with respect to exposure are
  independent of disease. Will bias towards the
  null if the exposure is has two categories.
  Non-differential misclassification makes the
  groups more similar.

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Observation Bias

• Misclassification-
• Example Study of vaginal spermicides and
  congenital disorders (Jick et al., 1981).
• Solutions Use multiple measurements, most
  accurate source of information

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When interpreting study results, ask yourself
these questions

• Given conditions of the study, could bias have
  occurred?
• Is bias actually present?
• Are consequences of the bias large enough to
  distort the measure of association in an
  important way?
• Which direction is the distortion? Is it
  towards the null or away from the null?