CASE-CONTROL STUDIES

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CASE-CONTROL STUDIES

• Nigel Paneth

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EVOLUTION OF THE CASE-CONTROL STUDY

•   1. CASE
• What is a case?
• Consolidating several different signs and
  symptoms into "caseness" was a key development in
  medicine.
• (for more details see Paneth N, Susser E,
  Susser The early history and development of the
  case-control study. Social Preventive Medicine
  2002 47 282-288 and 359-365)

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• 2. CASE-SERIES
• Aggregating many individual cases into a group,
  and describing the features of the group, began
  in earnest in the 18th century.
• Key figure - PCA Louis in France.
  "The numerical method".
• Currently perhaps the single commonest kind of
  medical article.

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• 3. CASE-CONTROL STUDY
• In its simplest form, comparing a case series to
  a matched control series.
• Possibly the first c-c study was by Whitehead in
  Broad Street pump episode, 1854 (Snow did not do
  a c-c study).
• First modern c-c study was Janet Lane-Claypons
  study of Breast cancer and reproductive history
  in 1926.
• Four c-c studies implicating smoking and lung
  cancer appeared in 1950, establishing the method
  in epidemiology.

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FEATURES OF CASE-CONTROL STUDIES

• 1. DIRECTIONALITY
• Outcome to exposure
• 2. TIMING
• Retrospective for exposure, but
  case-ascertainment can be either retrospective or
  concurrent.
• 3. SAMPLING Almost always on outcome, with
  matching of controls to cases

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TWO CHARACTERISTICS OF CASES

• 1. REPRESENTATIVENESS
• Ideally, cases are a random sample of all cases
  of interest in the source population (e.g. from
  vital data, registry data). More commonly they
  are a selection of available cases from a medical
  care facility. (e.g. from
  hospitals, clinics)

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• 2. METHOD OF SELECTION
• Selection may be from incident or prevalent
  cases
• Incident cases are those derived from ongoing
  ascertainment of cases over time.
• Prevalent cases are derived from a
  cross-sectional survey.

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CHARACTERISTICS OF CONTROLS

• Who is the best control?
• Where should controls come from?
• If cases are a random sample of all cases in the
  population, then controls should be a random
  sample of all non-cases in the population sampled
  at the same time (i.e. from the
  same study base)
• But if study cases are not a random sample of the
  university of all cases, it is not likely that a
  random sample of the population of non-cases will
  constitute a good control population.

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•  THREE QUALITIES NEEDED IN CONTROLS
• Key concept Comparability is more important than
  representativeness in the selection of controls
• The control must be at risk of getting the
  disease.
• The control should resemble the case in all
  respects except for the presence of disease

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COMPARABILITY VS. REPRESENTATIVENESS

• Usually, study cases are not a random sample of
  all cases in the population, and therefore
  controls must be selected so as to mirror the
  same biases that entered into the selection of
  cases

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•  
• It follows from the above that a pool of
  potential controls must be defined.
• This pool must mirror the study base of the
  cases.

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STUDY BASE

•   Therefore, imagining the study base is a useful
  exercise before deciding on control selection.
• The study base is composed of a population at
  risk of exposure over a period of risk of
  exposure.

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•   Cases emerge within a study base. Controls
  should emerge from the same study base, except
  that they are not cases.
• For example, if cases are selected exclusively
  from hospitalized patients, controls must also be
  selected from hospitalized patients.

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• If cases must have gone through a certain
  ascertainment process (e.g. screening), controls
  must have also. (e.g. mammogram-detected breast
  cancer)
• If cases must have reached a certain age before
  they can become cases, so must controls. (thus we
  always match on age)
• If the exposure of interest is cumulative over
  time, the controls and cases must each have the
  same opportunity to be exposed to that exposure.
  (if the case has to work in a factory to be
  exposed to benzene, the control must also have
  worked where he/she could be exposed to benzene)

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SIX ISSUES IN MATCHING CONTROLS IN CASE-CONTROL
STUDIES

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• 1. Identify the pool from which controls may
  come. This pool is likely to reflect the way
  controls were ascertained (hospital, screening
  test, telephone survey).
• 2. Control selection is usually through
  matching.
• Matching variables (e.g. age), and matching
  criteria (e.g. control must be within the same 5
  year age group) must be set up in advance.

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• 3. Controls can be individually matched or
  frequency matched
• INDIVIDUAL MATCHING search for one (or more)
  controls who have the required MATCHING CRITERIA.
  PAIRED or TRIPLET MATCHING is when there is one
  or two controls individually matched to each
  case.
• FREQUENCY MATCHING select a population of
  controls such that the overall characteristics of
  the group match the overall characteristics of
  the cases. e.g. if 15 of cases are under age 20,
  15 of the controls are also.

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•   4. AVOID OVER-MATCHING. match only on factors
  known to be causes of the disease.
• 5. Obtain POWER by matching MORE THAN ONE
  CONTROL PER CASE. In general, N of controls
  should be lt 4, because there is no further gain
  of power above four controls per case.
• 6. Obtain GENERALIZABILITY by matching more than
  ONE TYPE OF CONTROL

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ADVANTAGES AND DISADVANTAGES OF C-C STUDIES

• Advantages
•   1. only realistic study design for uncovering
  etiology in rare diseases
• 2. important in understanding new diseases
• 3. commonly used in outbreak investigation
• 4. useful if induction period is long
• 5. relatively inexpensive

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• Disadvantages
•   1. Susceptible to bias if not carefully
  designed (and matched)
• 2. Especially susceptible to exposure
  misclassification
• 3. Especially susceptible to recall bias
• 4. Restricted to single outcome
• 5. Incidence rates not usually calculable
• 6. Cannot assess effects of matching variables

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EXAMPLES OF PROBLEMS

• Dolls 1951 study of smoking and lung cancer. The
  problem was that the control population (lung
  diseases other than cancer) was biased in
  relation to the exposure.
• McMahons 1981 study of coffee and pancreatic
  cancer. Problem was that some of the controls
  may have been biased in relation to the exposure,
  because gastro-intestinal diseases were excluded
  from the control series, and these diseases might
  have people who reduced coffee intake on medical
  advice or because of symptoms.

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SOME IMPORTANT DISCOVERIES MADE IN CASE CONTROL
STUDIES

•   1950's
• Cigarette smoking and lung cancer
• 1970's
• Diethyl stilbestrol and vaginal adenocarcinoma
• Post-menopausal estrogens and endometrial cancer

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•   1980's
• Aspirin and Reyes syndrome
• Tampon use and toxic shock syndrome
• L-tryptophan and eosinophilia-myalgia syndrome
• AIDS and sexual practices
• 1990's
• Vaccine effectiveness
• Diet and cancer

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BASIC ANALYSIS OF CASE CONTROL STUDIES

• FOR ONE CONTROL
• Data is expressed in a four-fold table, and an
  odds ratio is calculated (relative risks have no
  meaning here why?). 
• Cases Controls
• Exposed a b
• Unexposed c d
• OR ad/bc

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PAIRED ANALYSIS

• FOR ONE CONTROL
• Data is expressed in a four-fold table, and the
  number of concordant and discordant pairs are
  calculated. Test is McNemars chi squared test
  for paired data.
• Case Exposed Unexposed
• Exposed Both Mixed
• Controls
• Unexposed Mixed Neither

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PAIRED ANALYSIS

• FOR ONE CONTROL
• Case Exposed Unexposed
• Exposed r s
• Controls
• Unexposed t u
• McNemar chi2 (t s)2
• (t s)

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• MORE POINTS ABOUT
• CASE-CONTROL ANALYSIS
• The odds ratio is a good estimate of the relative
  risk when the disease is rare (prevalence lt 20).
  
• Can be extended to N gt 1 controls.
• statistical testing is by simple chi-square
  (unmatched analysis) or by McNemars chi square
  (matched-pairs analysis).
• Can be extended to multiple strata
  (Mantel-Haenzel chi-square)

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THEORETICAL FOUNDATIONof case-control
studiesper McMahon and Trichopoulos

•   1. "Case-control studies should be viewed as
  efficient sampling schemes of the disease
  experience of the underlying open or closed
  cohorts" (McMahon Trichopoulos, p. 230)
• 2. "The exposure odds ratio derived from
  case-control studies equals the disease odds
  ratio derived from cohort studies" (p.231)

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• 3.The incidence rate ratio
• Xe divided by Xo
• Te To
• can also be written as
• Xe divided by Te
• Xo To

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•  
• 4. "In a case-control study based on a dynamic
  population, Xe and Xo (exposed and unexposed
  cases) are directly ascertained, and the ratio
  Te/To can be estimated in an unbiased way not
  dependent on any rare disease assumption by the
  ratio of exposed versus unexposed prevalent
  individuals at risk in the study base (the total
  study period cancels out).

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• 5. "any particular group of prevalent
  individuals at risk for the disease in the source
  population during the study period (i.e. the
  study base) that correctly reflects the ratio of
  exposed to unexposed person-time in this
  population over this period can be used for this
  purpose."
• 6. "To the extent that Ye/Yo (the exposure odds
  among the controls) is an unbiased estimate of
  Te/To, controls may be viewed as reflecting the
  person-time by exposure status," (p.231)