Registration for a live webinar on 'Neuroleptic malignant syndrome' is now open.
See webinar detailsWe noted you are experiencing viewing problems
-
Check with your IT department that JWPlatform, JWPlayer and Amazon AWS & CloudFront are not being blocked by your network. The relevant domains are *.jwplatform.com, *.jwpsrv.com, *.jwpcdn.com, jwpltx.com, jwpsrv.a.ssl.fastly.net, *.amazonaws.com and *.cloudfront.net. The relevant ports are 80 and 443.
-
Check the following talk links to see which ones work correctly:
Auto Mode
HTTP Progressive Download Send us your results from the above test links at access@hstalks.com and we will contact you with further advice on troubleshooting your viewing problems. -
No luck yet? More tips for troubleshooting viewing issues
-
Contact HST Support access@hstalks.com
-
Please review our troubleshooting guide for tips and advice on resolving your viewing problems.
-
For additional help, please don't hesitate to contact HST support access@hstalks.com
We hope you have enjoyed this limited-length demo
This is a limited length demo talk; you may
login or
review methods of
obtaining more access.
Printable Handouts
Navigable Slide Index
- Introduction
- Bayesian methods
- Bayesian vs. frequentist
- Bayesian vs. frequentist example
- Bayesian: pros and cons
- Bayesian inferences
- Baye’s theorem
- Bayesian methods: prior
- Bayesian methods: the impact of prior
- A simple example - diagnosing lung cancer
- The basket design
- The bayesian basket design – example
Topics Covered
- Bayesian vs. frequentist perspective
- Learning as data accumulate
- Bayesian inferences
- Baye’s theorem
- The Impact of prior
- A simple example: lung cancer and smokers
- Bayesian Basket design
Talk Citation
Ye, F. (2018, July 31). Phase II clinical trials - Bayesian methods [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved October 12, 2024, from https://doi.org/10.69645/ZWHL9009.Export Citation (RIS)
Publication History
Financial Disclosures
- Prof. Fei Ye has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.
Phase II clinical trials - Bayesian methods
Published on July 31, 2018
23 min
Other Talks in the Series: Adaptive Clinical Trial Design
Transcript
Please wait while the transcript is being prepared...
0:00
Hi, this is Fei Ye,
from Vanderbilt University Medical Center.
In the second part of my lecture,
I will be focusing on using the Bayesian methods to design phase II clinical trials.
0:13
As I mentioned at the previous lecture,
adaptive designs have emerged rapidly during the last two decades.
But mostly with Frequentist approach,
often as an effective way to speed up the evaluation process because of
the flexibility and the more intuitive way
of interpreting the results with Bayesian methods.
Many Bayesian designs have also been
proposed and conducted for phase II clinical trials.
However, it has been reported that they are still poorly used in
practice mainly because many clinicians do not fully understand the Bayesian methods.
So, many statisticians, as well as clinicians,
are putting a lot of effort into promoting
all phases of clinical trials to use Bayesian methods.
First, I'm going to explain the differences between a Bayesian and a Frequentist approach.
Then, I'm going to talk about Bayes' theorem,
the impact of prior distribution and then I will give an example of Bayesian trial,
and the last I will introduce the very new Bayesian basket design.
1:22
From a Frequentist perspective,
we draw conclusions from sample data,
from data we collect in the current study with
the emphasis on the frequency or proportion of the data.
For example, we can calculate the response rate,
we can calculate the adverse event rate from the current trial.
This is the inference framework in which
the well-established methodologies of statistical hypothesis testing including p-values,
including confidence intervals are based upon.
With a Frequentist approach we write the probability P of an uncertain event A,
P of A, which is defined by the frequency of
that event based on the data we observed during the trial.
In other words, based on previous observations.
For example, in the United States,
48.8 percent of all babies born are girls;
and suppose that we are interested in the event A,
which is a randomly selected baby is a girl.
According to the Frequentist approach,
this P of A equals point four eight eight.