Loading…

Flash Player 9 (or above) is needed to view presentations.
We have detected that you do not have it on your computer. To install it, go here.

Like this presentation? Why not share!

Randomization and Comparative Trials

on

  • 252 views

 

Statistics

Views

Total Views
252
Views on SlideShare
252
Embed Views
0

Actions

Likes
0
Downloads
5
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Randomization and Comparative Trials Randomization and Comparative Trials Presentation Transcript

  • 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?
    • 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?
    View slide
  • 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!
    View slide
  • 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.
  • 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
  • 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
    • 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
    • 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