PE vs GMR [R for BE/BA]

posted by roman_max – Russia, 2018-12-12 16:31  – Posting: # 19683
Views: 4,635

Dear Ohlbe,

thanks a lot for clarification and the post provided. Because I`m using R/bear package seems that terminology in terms of MEANS are similar with SAS (LSMEAN). I`m not familiar with the latter software.

Very often I face with that in BE study reports submitted to EMA/FDA by different companies GMR is the metric, not PE (along with its CIs). This is the reason why I interested in what we really "calculate" and why, is it specific of particular software or using of different terminology or something else.

In a BE study report there is a summary table for presenting BE results, where geometric means (or LSMEANs?) in natural scale, GMR (%) (or PE(%)?) and CI(%) should be reported.

In my example with R/bear for Cmax and log(Cmax) in output file I have the following data (designations "as is" in the output file):
Dependent Variable: log(Cmax)
n1(R -> T) = 23
n2(T -> R) = 22
N(n1+n2) = 45
Lower criteria = 80.000 %
Upper criteria = 125.000 %
MEAN-ref = 3.970504
MEAN-test = 4.097524
MSE = 0.1563787
SE = 0.08338823
Estimate(test-ref) = 0.1282001

* Classical (Shortest) 90% C.I. for log(Cmax) *

Point Estimate CI90 lower CI90 upper
113.678 98.809 130.785

As Yung-jin explained me that PE in R/bear is not a direct arithmetic difference, and it is estimated in a specific linear model in ANOVA.

MEAN-ref and MEAN-test are correspond to each LSMEAN in PK Parameter Summaries, it is OK.

<< PK Parameter Summaries >>

summary Test Ref Ratio
LSMEAN 4.097 3.971 1.043
This is for logarithms

So, Exp(LSMEAN[T])=60.159 and Exp(LSMEAN[R])=53.038, and these are geometric means, right?
So, the ratio of geometric means (GMR) is 60.159/53.038=113.428

Does my understanding correct now?

But what to report to authorities? PE or GMR? For balanced study they are equal, but for imbalanced they are slightly different.
And what about CIs? Should I construct them for GMR as well?

Thanks in advance for further clarifications.

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