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Back to the forum  Query: 2017-12-11 18:15 CET (UTC+1h)
 

forced BE? [Design Issues]

posted by Helmut Homepage - Vienna, Austria, 2017-08-07 13:31  - Posting: # 17667
Views: 1,608

Hi David,

» Portuguese Ethics Committee has a lot of members with an amazing knolwedge (even a priest!), …

Like in Austria (#9 of above). Catholic Church still strong. Not so in Germany. ;-)

» The only field where there is a lack of expertise (imo, of course) is statistics.

That’s a pity.

» […] I had never found any comment from SPE to relevant guidelines nor have received any e-mail as member to provide insights into any sort of coordinated review.

No surprise. I’m a member of the IBS. When the BE-GL was drafted I suggested to compile comments from the society. Response: Zero, niente, nada. Seemingly they considered BE too trivial.

» As regards to the portuguese authority, in my experience in the assessment of clinical trial applications (not MA), we never receive any questions from the statistical part of the study (either they don't have experts for this or they rely on the assessment of the EC).

One regulator once told me that he is interested in α not β.

» I will hope that the relevance of the theme and the academic part of the job might sensitize them on this :-D

Yep. As a side note: The European Community is a founding member of ICH. E9, Section 3.5 states:

The number of subjects in a clinical trial should always be large enough to provide a reliable answer to the questions addressed. […]
The method by which the sample size is calculated should be given in the protocol, together with the estimates of any quantities used in the calculations (such as variances, mean values, response rates, event rates, difference to be detected). The basis of these estimates should also be given. It is important to investigate the sensitivity of the sample size estimate to a variety of deviations from these assumptions and this may be facilitated by providing a range of sample sizes appropriate for a reasonable range of deviations from assumptions. In confirmatory trials, assumptions should normally be based on published data or on the results of earlier trials. […] Conventionally the probability of type I error is set at 5% or less or as dictated by any adjustments made necessary for multiplicity considerations; the precise choice may be influenced by the prior plausibility of the hypothesis under test and the desired impact of the results. The probability of type II error is conventionally set at 10% to 20%; it is in the sponsor’s interest to keep this figure as low as feasible especially in the case of trials that are difficult or impossible to repeat.

Did you ever see that in a protocol? I didn’t.

» Don't know if assuming the same GMR as in the planned sample size calculation and the observed CV might be a solution - still a long way to go from idea to practice.

Power is much more sensitive to the GMR than to the CV. Maybe looking at it the other way ’round would be better. If you are not a hard-core frequentist, going Bayesian might be an option.

» The primary purpose will be to sensitize the regulators/EC to studies …

I think this is very important indeed!

» … that they approve with a justification like "Assuming a GMR of 0.95 and a CV of XX%, a total of XX patients will be included in the study" which after conduct have a result with 99.99% power. …

Again: Post hoc power. How relevant is it?
IMHO, ECs should simply follow ICH E9. Which are the assumptions, how sensitive is the sample size to deviations, …? It is the job of the EC to protect the health of subjects in the study. Hence, it is desirable to keep the sample size as small as possible but as large as necessary.

[image]Regards,
Helmut Schütz 
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