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Printable Handouts
Navigable Slide Index
- Introduction
- Contents
- Background on randomization in clinical trials
- A historical perspective on randomization
- Why is randomization important in clinical trials?
- What other considerations are important? (1)
- What are the regulatory perspectives on randomization?
- What types of randomization designs are available?
- Focus on 1:1 randomized controlled trial (RCT)
- Mathematics of randomization
- Mathematics: randomization sequence
- Different types of 1:1 randomization designs
- Complete randomization (CR)
- Procedures that achieve exact balance (n/2 E’s and n/2 C’s)
- Maximum tolerated imbalance (MTI) procedures
- Procedures that maintain near-balanced allocation
- Selecting a randomization design: balance–randomness tradeoff
- Randomization designs vary in the degree of balance they induce
- Treatment balance and allocation randomness
- How do we choose a randomization procedure?
- PBD vs. BSD: probability distribution
- PBD vs. BSD: expected imbalance |D|
- PBD vs. BSD: allocation randomness
- Summary: PBD vs. BSD
- Selecting a randomization design: validity and efficiency considerations
- Beyond balance and randomness?
- Statistical inference after RCT: approach 1
- Statistical inference after RCT: approach 2
- Randomization-based inference (RBI)
- Which randomization designs are robust & efficient?
- Eleven randomization designs
- Three statistical tests
- Not all designs are ‘the same’!
- Some important findings: M1 and M2
- Some important findings: M3 and M4
- Summary of findings
- Randomization and covariate adjustment
- Why is covariate adjustment important? survival trial
- Why is covariate adjustment important?
- Why is covariate adjustment important? serum bilirubin
- Some additional important topics in randomization
- Designing an RCT with a very small sample size
- Analysis of RCTs with data missing not at random (MNAR)
- A fresh look at the concept of randomization
- Thank you!
Topics Covered
- Background on randomization in clinical trials
- Complete randomization (CR)
- Maximum tolerated imbalance (MTI) procedures
- Selecting a randomization method: balance-randomness tradeoff
- Selecting a randomization method: validity and efficiency considerations
- Randomization and covariate adjustment
Links
Series:
Categories:
Talk Citation
Sverdlov, A. (2024, July 31). Randomization in clinical trials: time for fresh consideration? [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved December 23, 2024, from https://doi.org/10.69645/GSCG6201.Export Citation (RIS)
Publication History
Financial Disclosures
- Oleksandr Sverdlov is an employee and holds stock at Novartis.
Other Talks in the Series: The Risk of Bias in Randomized Clinical Trials
Transcript
Please wait while the transcript is being prepared...
0:00
Hello everyone,
my name is Oleksandr Sverdlov,
and I'm a Senior Director of
Biostatistics at Novartis.
Today, my presentation is on
Randomization in Clinical Trials:
Time for Fresh Consideration?
0:17
Here's the outline
of my presentation.
I'll start with some background
on randomization in
clinical trials.
Then I'll describe the
balance-randomness tradeoff.
Then I'll talk about
validity and efficiency
considerations.
After that, I'll describe
the importance of
covariate adjustment
in the context of
randomized clinical trials.
Finally, some additional
important topics
on randomization.
0:47
Here's the background on
randomization in
clinical trials.
0:53
Some historical perspective
on randomization.
We are really standing on
the giant's shoulders.
The work of Ronald Fisher,
"The Design of Experiments",
Sir Bradford Hill's work,
and Jerome Cornfield's work,
"Principles of Research",
they all form an
important basis for
the theoretical approach
on randomization method.
1:19
Why is randomization
important in clinical trials?
There are three main reasons.
The first one is that
randomization helps
mitigate selection
bias in the design.
Especially when the study
is an open-label study.
Second, randomization promotes
the similarity of
treatment groups with
respect to known and
unknown confounders.
Third, it contributes
to the validity of
statistical estimators
and tests, and in fact,
it can form the basis for
re-randomization tests.
What are other important
considerations