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0:00
Hello, I am Ying Yuan.
I'm a professor in Biostatistics
at MD Anderson Cancer Center.
In the first part,
we have talked about the three designs
to find a single MTD or MTD contour.
So in this part we're going to focus on
how to implement those three designs
using our existing software.
So we are going to go through each of them
and show you how to use the software
to design specific trial examples.
0:27
So right now, we switch to the software.
So, so far we have talked about several designs
to find the MTD or MTD contour.
And from a practical point of view,
the important thing is that
we have the software to implement the design,
and how can we use it in practice.
So the important reason
we chose those three designs
is because it is very easy
to use the software for those designs.
And essentially they can be implemented
using the R package "BOIN"
available from the CRAN.
And then in addition, if you don't like R,
there is also Standalone, a graphic user
interface-based software available
from MD Anderson Biostatistics Software
downloaded from the website.
Here I give the link,
if you are interested, you can download it.
And in addition,
we also provide a statistical tutorial
and protocol template.
So this is listed on my website
- you can check it out.
1:18
Okay, so right now we are
going to demonstrate
how to use the software to design
combination trials, step-by-step.
The first design we are going to talk
about is the linearization design.
So this is the design used to find a
single MTD for the combination trial.
And because this linearization design
uses the BOIN design,
it is very simple,
because essentially the first thing
you need is to get a boundary.
So recall, for this BOIN design,
what you really need
is that escalation boundary
and a de-escalation boundary.
Once you have those two
boundaries, you can make a decision
of dose assignment.
So that is why the first function
is "get.boundary."
It is used to generate escalation
and de-escalation boundaries
So once we have a boundary,
we can conduct a trial.
Once we finished the trial,
the only thing we need is to select the MTD.
So that's why we have a second function
called "select.mtd."
So essentially what it does is
it helps you select MTD at the end of trial
based on isotonically transformed estimates.
So, those two functions are enough
to conduct the trial in practice,
but when we prepare a protocol a lot of times
we have to show the
operating characteristics of the design.
So essentially, we want to do a simulation
to show the performance of the design.
So that's why we have a third function
called "get.oc."
So this is used to generate the
operating characteristics,
you can use it for simulation purposes.
