A short introduction to epidemiology Chapter 2b: Conducting a casecontrol study

1
A short introduction to epidemiologyChapter 2b
Conducting a case-control study

• Neil Pearce
• Centre for Public Health Research
• Massey University
• Wellington, New Zealand

2
Chapter 2 (additional material)Case-control
studies

• This presentation includes additional material on
  conducting a case-control study
• More information on data analysis is given in
  chapter 9

3
Chapter 2 (additional material)Case-control
studies

• Reasons for doing a case-control study
• Basic study design
• Selection of cases
• Selection of controls
• control sampling strategies
• sources of controls
• issues in control selection

4
Birth
End of Follow up
Death other death lost to follow up
non-diseased symptoms severe disease
5
A Hypothetical Incidence Study
6
A Hypothetical Case-Control Study

• 1813/8187 a/c ad
• Odds ratio ---------------- ----- ----
• 952/9048 b/d bc
• 1813/952 a/b ad
• ---------------- -----
  ---- 8187/9048 c/d bc

7
Reasons for Doing a Case-Control Study

• It may be inefficient to have to obtain exposure
  information on all people in the source
  population
• It is sufficient to obtain information on all of
  the 2,765 deaths and a control sample (e.g. 2,765
  controls) of the 17,235 survivors
• We therefore only need to get exposure
  information on 5,530 people instead of 20,000
• This gain in efficiency is much greater when the
  disease is rare (e.g. if it were 1/10th as
  common then we would have 277 cases and 277
  controls)

8
Reasons for Doing a Case-Control Study

• Rare disease
• long induction time
• smaller study size permits collection and
  analysis of more detailed exposure information
• cohort difficult to enumerate (registry-based
  studies)

9
Chapter 2 (additional material)Case-control
studies

• Reasons for doing a case-control study
• Basic study design
• Selection of cases
• Selection of controls
• control sampling strategies
• sources of controls
• issues in control selection

10
Basic Case-Control Study Design

• Every study is based on a particular source
  population followed over a particular period of
  time (the risk period)
• Ideally the study base should be made explicit
• We study all cases of the outcome and a sample of
  controls drawn from the source population
• The case-control design thus involves all of the
  potential biases involved in a full cohort study,
  as well as additional biases involved in sampling
  controls
• Information bias is not an inherent feature of
  such studies

11
Cohort-Based (Nested) Case-Control Studies

• Enumerate the cohort (source population) and its
  experience over time (the risk period)
• Ascertain all cases generated by this study base
• Sample controls from the person-time (or persons)
  that generated the cases

12
Registry-Based Case-Control Studies

• Ascertain all cases appearing in the registry
  during a specified period of time
• Sample controls from the source population for
  the registry

13
Chapter 2 (additional material)Case-control
studies

• Reasons for doing a case-control study
• Basic study design
• Selection of cases
• Selection of controls
• control sampling strategies
• sources of controls
• issues in control selection

14
Selection of Cases

• Cohort-based
• All cases (or deceased cases) generated by the
  cohort study
• Living cases may be added from other sources
  (e.g. hospital records, cancer registrations)
• Registry-based
• All eligible cases appearing in the
  registryduring a specified period of time

15
Chapter 2 (additional material)Case-control
studies

• Reasons for doing a case-control study
• Basic study design
• Selection of cases
• Selection of controls
• control sampling strategies
• sources of controls
• issues in control selection

16
Control Sampling Strategies

• Cumulative incidence sampling
• Case-base sampling
• Density sampling

17
Birth
End of Follow up
Death other death lost to follow up
non-diseased symptoms severe disease
18
A Hypothetical Incidence Study
19
Cumulative Incidence Sampling

• Traditional method of control selection in
  nested case-control studies
• Controls are sampled from the non-cases, those
  free of disease at the end of the follow-up
  period, i.e. the survivors
• I.e. controls are sampled from the denominators
  for (cohort) odds ratio analyses

20
A Hypothetical Incidence Study
21
A Hypothetical Case-control Study
22
Cumulative Incidence Sampling

• Estimates the (cohort) odds ratio (without any
  rare disease assumption)
• Estimates the risk ratio and rate ratio
  approximately (with a rare disease assumption)
• May involve matching on age, etc
• Exposure is usually only considered up to the
  time (year or age) that the case occurred

23
Case-cohort Sampling

• Controls can be selected from those at risk at
  the beginning of the follow-up period, I.e. from
  the entire source population
• I.e. controls are selected from the denominators
  for (cohort) risk ratio analyses

24
A Hypothetical Incidence Study
25
A Hypothetical Case-control Study
26
Case-cohort Sampling

• Estimates the risk ratio (without any rare
  disease assumption)
• Requires minor modifications to the standard
  formulas for confidence intervals and p-values
• May involve matching on age, etc
• Once again, exposure is usually only considered
  up until the time that the case occurred

27
Birth
End of Follow up
Death other death lost to follow up
non-diseased symptoms severe disease
28
Density Sampling

• Controls are selected longitudinally throughout
  the course of the study, i.e. from the
  person-time of the study base
• I.e. controls are sampled from the denominators
  for the rate ratio analyses
• In general, controls are selected from the risk
  set of persons at risk at the time that each
  case occurred

29
A Hypothetical Incidence Study
30
A Hypothetical Case-control Study
31
Density Sampling

• The time variable is usually taken to be age
  rather than calendar time (year)
• Estimates the rate ratio (without any rare
  disease assumption)
• Matching may also be done on other time-related
  factors, although this is usually not necessary
• Usual method of sampling in registry-based
  studies

32
Selecting Controls

• Cohort-based studies
• Sample of the cohort (preferably by density
  sampling on age)
• Registry-based studies
• Sample of the source population for the Registry
  (usually by density sampling on year, perhaps
  with matching on age)

33
Selecting Controls in Registry-Based Studies

• Cases chosen from all lung cancer cases at
  hospitals in the City
• Controls chosen from general population of the
  City?

34
Selecting Controls in Registry-Based Studies

• All lung cancer cases at all hospitals in the
  City
• Controls chosen from general population of the
  City?
• Restrict cases to those living in the City
  (exclude those who have come to the City for
  treatment)
• Restrictions that apply to one group (e.g. having
  a telephone, being on Electoral Roll, having
  health insurance) should also be applied to the
  other

35
Selecting Controls in Registry-Based Studies

• Cases chosen from all lung cancer cases at the
  main hospital in the City
• What is the source population for these cases?

36
Selecting Controls in Registry-Based Studies

• Cases chosen from all lung cancer cases at the
  main hospital in the City
• What is the source population for these cases?
• All those who would have come to the main
  hospital in the City for treatment if they had
  developed lung cancer

37
Issues in Control Selection

• Controls are usually sampled at random from the
  entire study base
• However, it is sometimes desirable to restrict
  the controls to a sample of a subset of the study
  base
• In particular, we may select controls from
  persons with other diseases generated by the same
  study base (e.g. other deaths, other cancers,
  other hospital admissions)

38
Other Disease Controls

• All other diseases
• All other diseases except those known to be
  related to exposure
• A disease known to be unrelated to exposure

39
Reasons for Using Other Disease Controls

• The cohort (source population) is not enumerated
• E.g. if the cases are identified from hospital
  admissions (e.g. for lung cancer) then the study
  base is all persons who would have been admitted
  to this hospital if they had developed lung
  cancer
• Controls might be selected from other admissions
  to the same hospital

40
Reasons for Using Other Disease Controls

• Comparability of information
• E.g. in a case-control study of non-Hodgkins
  lymphoma and pesticide exposure, cases might be
  more likely to recall brief exposures
• We might therefore select controls from other
  cancer registrations rather than from the entire
  source population for the Cancer Registry

41
Selection Bias in Case-Control Studies

• In a case-control study, the controls are a
  sample of the source population
• Selection bias can occur if the sample is
  non-random, and the selection of controls is
  related to exposure status
• In other words, selection bias can occur if the
  controls are not representative of the exposure
  in the source population

42
Selection Bias in Case-Control Studies Solutions

• Selection bias can occur if the selection of
  controls is related to exposure status
• In the analysis, we can control for the
  determinants of control selection (e.g. social
  class)
• An exception is when we have chosen other
  disease controls and the other diseases are
  directly caused by the main exposure of interest
  this selection bias cannot be removed

43
General Population and Other Cancer Controls

• General population
• Represents study base
• May be more prone to recall bias if cases are
  more likely to recall exposures
• Difficult to keep interviewer blind, and may get
  interviewer bias

• Other cancers
• Other diseases may be caused by exposure
  (selection bias)
• Equal motivation and recall in cases and
  controls
• Easier to keep interviewer blind

44
Reasons for Matching

• Practical efficiency
• e.g. if we are using hospital controls then it is
  usually more efficient to select a control
  admitted on the same day as the case, rather than
  sampling at random from all admissions for the
  year

45
Reasons for Matching

• Statistical efficiency
• e.g. if we select general population controls at
  random in a lung cancer case-control study then
  the cases will be mostly old and the controls
  will be mostly young. It will therefore be
  difficult to stratify on, and control for, age

46
Reasons for Not Matching

• Practical efficiency
• matching can be costly and time-consuming and is
  usually not necessary since we can adjust for the
  major matching factors (e.g. age, gender, smoking
  status) in the analysis

47
Reasons for Not Matching

• Statistical efficiency
• Matching on a weak risk factor (or a non-risk
  factor) that is strongly correlated with the main
  exposure can dramatically reduce efficiency

48
Matching

• Only match on risk factors that are
• Not of intrinsic interest in themselves (e.g.
  age)
• Strong risk factors for disease
• Not too difficult to match on

49
Common misconceptions about case-control studies

• Fundamentally different type of study design that
  proceeds from disease to exposure (I.e. reverse
  causality)
• Inherently less valid (more biased) than cohort
  studies
• Require a rare-disease assumption
• Odds ratio only approximates the rate ratio or
  risk ratio (under the rare disease assumption)

50
A short introduction to epidemiologyChapter 2b
Conducting a case-control study

• Neil Pearce
• Centre for Public Health Research
• Massey University
• Wellington, New Zealand