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Randomization and Comparative Designs. Oncology Journal Club April 5, 2002. Comparative Designs. “Compare”: need more than one group Different types historical control two+ treatment groups treatment and placebo groups “Phase III”. Was this study comparative?.

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randomization and comparative designs

Randomization and Comparative Designs

Oncology Journal Club

April 5, 2002

comparative designs
Comparative Designs
  • “Compare”: need more than one group
  • Different types
    • historical control
    • two+ treatment groups
    • treatment and placebo groups
  • “Phase III”
was this study comparative
Was this study comparative?
  • What are the “groups” that are being compared?
  • Treatment 1 vs. treatment 2?
  • Was it randomized?
    • What was were they randomized to?
    • Did they show a difference in the two groups under consideration?
    • Did they show that the groups being compared were comparable with regard to pertinent factors?
randomization
Randomization
  • Why? What’s the big deal?
  • Reduces potential for bias
  • “Ensures” that groups being compared are likely to be similar to each other.
  • Example of violation of randomization bias:
    • selection bias: the physician decides which patients are assigned to which treatment
    • i.e. physician decides which patients get high versus low radiotherapy!
randomization1
Randomization
  • What if physicians tend to give sicker patients less radiotherapy?
  • Now, there is a “correlation” between being sick and treatment.
  • Is it so strange to imagine that the sicker patients would tend to have shorter survival?
  • Now that they have “confounded” sick status with treatment, they CANNOT conclude anything about treatment.
randomization2
Randomization
  • Idea of Confounders: many variables may be associated with outcome. By randomly assigning individuals to treatment groups, we decrease likelihood of making an error due to a confouding variable
randomization3
Randomization
  • Randomization to low versus high radiotherapy WOULD have made illness and treatment independent.
  • How could this have been helped?
    • Inclusion/exclusion criteria so that only kids who were “healthy” enough could receive full dose
    • Stratify by stage: ensure that comparable numbers of sick and less sick kids are in each arm.
final comments on randomization
Final Comments on Randomization
  • It does not guarantee that groups are “the same,” but the principle is that for large numbers of patients, the groups will even out.
  • For small studies, might be a good idea to stratify to really ensure balance.
  • Randomization isn’t always truly random
    • blocking
    • stratification
final comments on comparative trials
Final Comments on Comparative Trials
  • Selection bias: not just physician choice
    • center (e.g. multi-center study)
    • patient (think about ITT vs. actual received)
  • Blinding/Masking:
    • when possible, it is generally a good idea for patient (blinded) or patient and physician (double-blinded) to not know which group patient is assigned to
    • avoids sub-concious effects
    • avoids cross-over