Advantages [Two-Stage / GS Designs]

posted by d_labes  – Berlin, Germany, 2015-06-05 11:35 (3220 d 02:26 ago) – Posting: # 14914
Views: 17,954

Hi Helmut, hi Dan,

Sorry for participating late on this thread.
Was on Holidays these times.

❝ ❝ Chance of approval in the first go is low, but you will have a comfortable CI in the second stage.


❝ Correct. If one does not want to take the chance to show BE already in the first stage and has enough time to almost always proceed to the second stage, why not? The first stage serves only to get an estimate of the CV and can be seen as an “internal pilot study”. Compared to published methods with an equal split of alphas the sample size penalty is lower.

Emphasis by me

This is exactly the reason why my Brötchengeber (man who signs the paycheck) recommend this settings. Especially for cases where the information about the variability of the drugs under consideration is very vague and would require on the classical way a pilot study and afterwards a pivotal study.

Let's see if this expectation is real:
Type 1 TSD (Potvin B) with n1=12.
Somewhat small IMHO, but you have to choose a small n1 to not waste money and due to ethical reasons if the variability proved to be small, for which already 12 subjects are sufficient.

Judging this as advantage or practically not is up to you.
Nominal alpha's like Pocock (0.0294, 0.0294) or adj. Haybittle/Peto (0.001, 0.0416 to control the overall TIE), targetpower 80%. Assume we have a bioequivalent product.

                      sample size  p stop at
CV    alpha's  power   mean   p95%  interim
--------------------------------------------
0.15   Poc    88.13%   13.5    22    79.3%   
       adjHP  88.32%   14.2    22    56.2%
0.25   Poc    81.17%   32.3    60    18.6%
       adjHP  79.91%   30.5    54     3.9%
0.4    Poc    74.95%   78.8   142     1.0%
       adjHP  75.18%   70.5   128     0.1%
0.7    Poc    72.42%  207.3   378     0%
       adjHP  72.93%  185.1   338     0%


With the exception of small variability, where the Pocock settings have a slight advantage w.r.t expected sample size and chance of stopping at interim the "asymmetric" alpha split proved to be really somewhat better w.r.t to sample size. Differences in power or probability to stop at interim are of no practical relevance I think.

Judging this as advantage or practically not is up to you :cool:.

Regards,

Detlew

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