Critical review of EU BE guideline (Rev.1), tmax, MRT, LZ [Regulatives / Guidelines]

posted by Helmut Homepage – Vienna, Austria, 2008-08-25 15:10 (6141 d 19:06 ago) – Posting: # 2253
Views: 24,771

Dear D. Labes!

Statistical analysis, page 13 (lines 504-505)

❝ A nonparametric analysis is not acceptable.


❝ This cannot be discussed seriously without crying.


Join the party. In the past I have evaluated about 300 BE studies nonparametrically (additive model for tmax, multiplicative for AUC and Cmax); ANOVA was only given in an annex essentially to get the CV and have a look whether my sample size assumptions turned out to be justified and have it ready for future studies. Sometimes I was asked to make the ANOVA the primary analysis post hoc. This was the crying phase.
Later on driven by both regulators and sponsors I retreated to:This was the screaming phase (but covered by ICH-E9):

‘In the choice of statistical methods due attention should be paid to the statistical distribution […]. When making this choice (for example between parametric and non-parametric methods) it is important to bear in mind the need to provide statistical estimates of the size of treatment effects together with confidence intervals […].’


Since regulators hate pretesting (even one of the advocates of nonparametrics in the field of BE, Dieter Hauschke wouldn't do it), right now I'm with nonparametrics for tmax, parametrics for AUC and Cmax. Still I'm looking at the residuals. Quoting Jones and Kenward (Design and Analysis of Cross-Over Trials, 2nd ed. 2003):

“No analysis is complete until the assumptions that have been made in the modeling have been checked. Among the assumptions are that the repeated measurements on each subject are independent, normally distributed random variables with equal variances. Perhaps the most important advantage of formally fitting a linear model is that diagnostic information on the validity of the assumed model can be obtained. These assumptions can be most easily checked by analyzing the residuals.”


In the worst case I present two evaluations; a full data set and another one with the potential outlier removed (only if it’s a failure of the reference). But this is unplanned and stupid anyway.
This is the current phase of hating pragmatism.

But the new Guideline will lift any need for thinking from my side; being part of the flock I only have to follow the shepherd to be happy.

❝ Also note that MRT has disappeared.


Interesting. Maybe, because the Guideline deals only with IR formulations - and the group didn't consider it of any importance? For MR formulations there’s a reference to CPMP/EWP/280/96 included.

❝ Newly mentioned is LambdaZ, which is nearly the same, but on an inverse scale, as half live t1/2.


Yes, but how to deal with it? Strictly speaking, if half lives are different - BE testing does not make sense. For an IR formulation both AUC and Cmax should be influenced only by absorption; elimination is drug-specific. If the apparent elimination is different, it would mean that we are trapped by flip-flop PK, i.e., the late phase of the profile represents absoption rather than elimination. In such a case the main parameter AUCt and the last sampling at 72 hours are debatable.
What should we do now? Come up with some descriptive statistics and :blahblah:, or run a pretest to show there's no difference before proceeding? If yes, what’s the distribution of lambdaZ/t1/2? I used to give the harmonic means* in a table - but I’m not sure about a transformation useful in a comparison…



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