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posted by Helmut Homepage – Vienna, Austria, 2020-12-02 11:34 (53 d 00:52 ago) – Posting: # 22103
Views: 853

Hi Nastia,

» » The problem starts already here. How reliable is Oodendijk’s result? Is it the only one?
»
» The reliability of someone else's data - that is the question (especially when one of the authors says "waouf" :-)

Willard Oodendijk twittered and Nemo Macron said “waouf”.

» » The crucial point is what we consider a “clinically not relevant \(\small{\Delta}\)”
»
» As far as we (and the Agency) proclaim 25% to be clinically not relevant there is no difference in the rate of the harm for the customer's health independently from the a- or b- approach. For the b-approach he'll just receive not worser drug or doesn't receive it at all.

Here you err. In (a) all is good. In (b) everything is in a flux; the applicant and agency agree only that the acceptable risk may be either 20% or 25%.
We are dealing with average BE. Classifying HVD(P)s based on CVwR is fine in principle. However, once we make this classification post hoc (based on \(\small{\widehat{CV_\textrm{wR}}}\)), troubles start. Hence, I don’t like* the reference-scaling methods and (b) as well.

» » Try the function CVCL() in PowerTOST.
» I try:
»

library(PowerTOST)
» CVCL(CV = 0.3, df = 3*40-4, side ="2-sided")
»  lower CL  upper CL
» 0.2646219 0.3466708


» As CI is shifted to the right …

Skewed to the right because the variance follows a \(\small{\chi^2}\)-distribution.

» … does it mean that for these initial conditions the probability of the conclusion of HV is higher?

Yes (for any condition).

» (By the way shouldn't we lower the degrees of freedom for the CV of the reference drug? 3*40-3 should correspond to the common CV of the Test and Reference, shouldn't it?)

Oops, one more degree of freedom! In the 2-sequence 4-period replicate design we have df = 3n – 4 for the pooled CVw. Following the EMA’s model for the estimation of CVwR we have one factor (the treatment) less in the model and therefore, df = 3n – 3:

library(PowerTOST)
CVCL(CV = 0.3, df = 3*40-3, side = "2-sided")
 lower CL  upper CL
0.2647549 0.3464397




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