Educate the IEC and regulators [Power / Sample Size]

posted by Helmut Homepage – Vienna, Austria, 2017-12-28 11:30 (1126 d 03:00 ago) – Posting: # 18111
Views: 28,049

Hi Yura,

» You are considering the power after the study at n = 28 (which were calculated before the study: GMR=0.95, CV=0.25, β=0.80). The question is whether it is possible to carry out a study at n = 50 and will this be forced bioequivalence?

As I wrote above the IEC and the authority should judge this before the study is done. I agree that in many cases the statistical knowledge of IECs is limited. However, once the protocol was approved by both, I don’t see a reason to talk about “forced BE” any more.

BTW, I don’t see a problem if a study is designed for 90% power (80% is not carved in stone). Let’s assume a dropout rate of 15% and we will already end up with 46 subjects:

CV     <- 0.25 # CV-intra
theta0 <- 0.95 # T/R-ratio
target <- 0.90 # desired (target) power
dor    <- 15   # expected dropout rate in percent
n      <- sampleN.TOST(CV=CV, theta0=theta0, targetpower=target,
                       print=FALSE)[["Sample size"]]
ceiling(n/(1-dor/100)/2)*2 # round up to next even

Considering your example and assuming that the GMR and CV turn out exactly as assumed, no dropouts (n=50): The 90% CI will be 87.47–103.18%. Fine with me. Not even a significant difference (100% included). If the drop­out-rate is as expected (n=38) the 90% CI will be 86.36–104.51%. If the assessor is not happy with that, he should have a chat with his colleague who approved the protocol and enlighten him about potential “over-powering” in study planing.
According to all guidelines (CI within the acceptance range) I can’t imagine a justification to reject the study. If the study is not accepted only due to the high sample size in the EEA the applicant might go for a referral (with extremely high chances of success) and in the USA the FDA will be sued right away. :-D

Dif-tor heh smusma 🖖
Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes

Complete thread:

 Admin contact
21,316 posts in 4,446 threads, 1,489 registered users;
online 5 (1 registered, 4 guests [including 1 identified bots]).
Forum time: Wednesday 14:30 CET (Europe/Vienna)

Nothing fails like success because you do not learn anything from it.
The only thing we ever learn from is failure.
Success only confirms our superstitions.    Kenneth E. Boulding

The Bioequivalence and Bioavailability Forum is hosted by
BEBAC Ing. Helmut Schütz