Mutasim
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Jordan,
2019-08-07 11:16

Posting: # 20484
Views: 799
 

 Group by sequence interaction [General Sta­tis­tics]

Dear Members,
What is the explanation for and the impact of having a significant group by sequence interaction in a study with 4 groups and 2 sequences and 4 periods (HVD).
Helmut
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Vienna, Austria,
2019-08-07 12:35

@ Mutasim
Posting: # 20485
Views: 693
 

 Group by sequence interaction, an urban myth?

Salam Mutasim,

» What is the explanation for …

Chance.

» … and the impact of having a significant group by sequence interaction in a study with 4 groups and 2 sequences and 4 periods (HVD).

If you are dealing with ABEL (the EMA’s method) chances than any (!) European agency will ask for a group-term in the analysis are close to nil. When I gave my first presentation about it in Budapest 2017 in front of European regulatory (!) statisticians they were asking in disbelieve “What the hell are you talking about?” See what the BE-GL states:

The study should be designed in such a way that the formulation effect can be distinguished from other effects.
The precise model to be used for the analysis should be pre-specified in the protocol. The statistical analysis should take into account sources of variation that can be reasonably assumed to have an effect on the response variable.

Is it reasonable to assume that groups or sequences have an effect on the PK response? Heck, no way! Same inclusion-/exclusion-criteria and hence, similar demographics, same clinical site, same bioanalytical method. Hundreds (thousands?) of studies performed in multiple groups and accepted by European agencies based on pooled data. OK, I know of two cases where the EMA (centralised procdure) asked for something similar. Both were complicated drugs (a biosimilar and a liposomal product) and multi-centric. Hence, the EMA asked for a site term.*
This is in line what is stated in the Q&A document about Two-Stage Designs:

A model which also includes a term for a formulation*stage interaction would give equal weight to the two stages, even if the number of subjects in each stage is very different. The results can be very misleading hence such a model is not considered acceptable. […] this model assumes that the formulation effect is truly different in each stage. If such an assumption were true there is no single formulation effect that can be applied to the general population, and the estimate from the study has no real meaning.

Replace formulation*stage by formulation*group and you get the idea.

But all of this is about a group-by-treatment interaction. Sometimes in conventional 2×2×2 crossovers we see a significant sequence (better unequal carry-over) effect. Since it can only be avoided by design (sufficiently long washout) any test for it is futile. Check for eventual residual concentrations in higher period(s) and exclude subjects with pre-dose concentrations >5% of their Cmax-values. In analogy the same can be said about the group-by-sequence interaction. Occasionally you will see a significant result. Ignore it.
Only if you prefer braces plus suspenders: Go with the FDA’s model II. But no pre-test and no interaction! The loss in power as compared to the pooled analysis is negligible.
Degrees of freedom in a 2×2×2 design:

Model III: n1 + n2 – 2
Model II:  n1 + n2 – (Ngroups – 1) – 2

Or in the 4-period full replicate:

Model III: 3(n1 + n2) – 4
Model II:  3(n1 + n2) – (Ngroups – 1) – 4

Am I right that you had to deal with 128 subjects? Then the 90% CI with model II will be just 0.002% (!) wider than the one with model III.
What you never ever should do: Evaluate groups separately. Power will be terrible. Even if you are extremely lucky and one of them passes, what will you do? Submit only this one? Any agency will ask for the others as well. Guess the outcome.

If you are thinking about the FDA’s group models I–III: There were very few deficiency letters (all with the same text) issued to US and Canadian companies. On the other hand, many European CROs have such letters collecting dust in archives. Politics? Even if you follow this track, model III (pooling) is justified since the conditions are practically always fulfilled. The sequential procedure (test for a group-by-treatment interaction at the 10% level) as any pre-test might inflate the type I error. I even have a statement from the EMA that such a procedure is not acceptable. Group-by-sequence interaction? Forget it.


  • Proposed all-fixed effects model:
    Site+Sequence+Sequence(Site)+Period(Site)+Subject(Sequence×Site)+Treatment

Cheers,
Helmut Schütz
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ElMaestro
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Belgium?,
2019-08-08 08:06

@ Helmut
Posting: # 20486
Views: 634
 

 pristine, genuine, holy, magnificent, inexplicable beautiful variation

Hi Hötzi,

» The precise model to be used for the analysis should be pre-specified in the protocol. The statistical analysis should take into account sources of variation that can be reasonably assumed to have an effect on the response variable.
» Is it reasonable to assume that groups or sequences have an effect on the PK response? Heck, no way! Same inclusion-/exclusion-criteria and hence, similar demographics, same clinical site, same bioanalytical method. Hundreds (thousands?) of studies performed in multiple groups and accepted by European agencies based on pooled data.

But on the other hand: Why then then include e.g. period.

Let us for a moment disregard the actual wording. I don 't think this is about assuming that some factor has or hasn't an effect (and not about significance in the statistical sense either). As I see it I want to construct a CI which is as wide as my real uncertainty dictates. I start out with a whole bunch of ugly variation and in the fashion of Michelangelo working on his crude blocks of marble I chip parts and bits away from my bulk of variation by applying my model. What I have left of my variation is a chunk of pristine, genuine, holy, magnificent, beautiful variation. What a sight to behold :-), and whose origin my experimental setup cannot account for, which I therefore use for my CI. My confidence interval now is as wide as just exactly that uncertainty merits.

For a crossover this is of little practical importance since subjects are in groups. For a parallel trial I think I want group in the model. If regulators don't like this, they can ask me to take it away. I happily do so without protesting. I am a sheep at that point. But not until then. :-D

I could be wrong, but...
Best regards,
ElMaestro
Helmut
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Vienna, Austria,
2019-08-08 08:31

@ ElMaestro
Posting: # 20487
Views: 629
 

 I love your subject line!

Ahoy, my Capt’n,

» » The precise model [:blahblah:]
»
» But on the other hand: Why then then include e.g. period.

[image]Cause otherwise eventual period effects would not mean out. ;-)

Given, sometimes one has to assume lacking period effects and everybody is happy with that. If an originator explores whether the drug follows linear PK, we have a paired design (SD → saturation → steady state) and compare AUC0–τ with AUC0–∞. A crossover would be a logistic nightmare.

» Let us for a moment disregard the actual wording. [lengthy beautiful explanation]

Exactly.

» […] For a parallel trial I think I want group in the model. If regulators don't like this, they can ask me to take it away. I happily do so without protesting. I am a sheep at that point. But not until then. :-D

Agree again.

Cheers,
Helmut Schütz
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