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Dear Group,
Recently during one of our 3-way BE studies, 2 volunteers from a
group of 18 were absent for second period. However, these volunteers
agreed to participate in the study further and the study was
continued. Now the problem is as follows.
16 Volunteers: Washout between period 1 and 2: (x) days.
Washout between period 2 and 3: (x) days
Rest 2 Volunteers: Washout between period 1 and 2: (x + 7) days
Washout between period 2 and 3: (x) days
My first question is that, will this kind of unequal washout affect
the PK parameters measured during the study?
My second question is that how this kind of situations treated
statistically? (What I wanted to know is whether any special
statistical treatment has to be given during such situations)
Thanks and best regards,
Rhishikesh MANDKE
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Hello Rhishikesh,
There are two methods to do statistical analysis in this case. Either
you eliminate those two subjects who were absent during period II or
analyse all the 18 subject subjects. In the first case, you are
reducing power of your study. In second case your power will be more
but you are using missing value for two subjects in statistical
analysis. It is upto you how you want to go ahead.
Statistial purpose to give equal wash out period between each period
is to test: "Is there significant difference between carry over or
not if it exist?"
So unequal wash-out period won't affect much if you have given enough
washout period between each period in case of bioequivalence. if
there is any carry over then you will come to know in pre dose
sampling time point. if this situation is out of question then you
can go ahead with unequal wash-out period for statistical analysis.
All the best
Priti Pandey
Ranbaxy, India
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Hi
I would like to add in addition to what preeti just mentioned.
Before the study is initiated there has to be a mention in the
protocol how incomplete data (like missing samples or subjects not
completing the perioid) is going to be handled in the PK statistics.
One cannot make decisions after the study has been executed. Also
rejection of data cannot be according to ones wish.
hope this helps
Manish Issar, Ph.D
Sandoz
4700 Eon Drive
Wilson, NC-27893
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The following message was posted to: PharmPK
Dear Manish,
In addition one would want to define in the protocol how an outlier is
defined rather than doing it post hoc.
Jim
James D. Prah, PhD
US EPA
Human Studies Division MD (58B)
Research Triangle Park, NC, 27711
919 966 6244
919 966 6367 FAX
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