Case-control studies

• Case-control studies:

  • Start with people with disease [outcome]
  • Two groups:
  • Cases those with disease
  • Controls those without disease
  • Collect data on risk factors [exposures] of interest
  • Compare odds of exposure in two group
  • Research question: Are those with disease “x” more likely, than those without disease x, to have been exposed to risk factor “y”?
• Key features of case-control studies:

  • Observational design ~ hypothesis generating
  • Identification of subjects with disease X (or other outcome of interest)
  • Identification of suitable control group without disease X
  • For both groups, past exposure is then determined
  • Retrospective or historical in nature of enquiry
• Model of case-control studies:

  • starts with population of interest in the present
  • see who are cases (have the disease) and who are controls (dont have the disease)
  • look back into the past to see if there was a factor that all cases had/didnt have and a factor that all controls had/didnt have - correlation between this factor and the disease

  
• Historical example: case-control study:

  • 1960 - 1961 in Hamburg, obstetricians noted 27 infants born with severe malformations
  • Rare condition, no cases observed between 1930 - 1958
  • German study recruited mothers of affected infants & sample of mothers of healthy infants
  • Detailed investigation of behaviours & practices during pregnancy; documentation of multiple exposures in both groups of women

  
• Historical example: case-control study:

  • Identified higher use of drug thalidomide in cases
  • Sleeping pill introduced in late 1950s, safer than barbiturates – did not induce coma
  • Prescribed for pregnant women, anti-emetic taken between 27 – 40 th week of pregnancy
  • Drug had been used in 46 countries - led to overhaul of drug development & licensing, withdrawn 196

  
• Selection of cases & controls

  • Most critical stage in a case-control study
  • Selection of cases
  • clearly define ‘cases’
  • specify inclusion & exclusion criteria
  • where is the ‘source’ population? e.g. residents from geographical region, patients recruited from a hospital ward or clinic
  • Selection of controls
  • same source as the cases
  • random selection of controls from source population
  • or matching (age, sex, SE status.....)
  • increase comparator group e.g. > 2 controls : 1 case
• Case-control cont.

  • Data collection & measurement
  • Collecting information about the past:
  • questionnaires / face to face interviews
  • GP or hospital records
  • medical examination
  • occupational records
  • or other previously collated data e.g. blood tests, biological markers
  • may be missing or incomplete
• Strengths of case-control design:

  • Very useful for investigating rare diseases or diseases with a long induction period e.g. some cancers
  • Time and cost efficient – when compared to cohort studies
  • Existing records /database can be used
  • Permits investigation of multiple risk factors /exposure
• Weaknesses of case-control design:

  • selection bias (poor case definition, difficulty finding representative controls)
  • observer bias (awareness of hypothesis, exposure or outcome status)
  • recall bias (incomplete, unreliable recall of past events, incomplete records, worse without blinding)
  • cofounder bias (controls not matched on important variables or unknown variables not included in analysis)
  • very prone to systematic error - efficient but vulnerable