Let’s forget the Group-by-Treatment interaction, please! [Regulatives / Guidelines]

posted by Helmut Homepage – Vienna, Austria, 2017-04-30 15:54 (2524 d 08:46 ago) – Posting: # 17284
Views: 30,173

Hi mittyri,

❝ Your opinion is very important for Russian BEBAC amateurs, so I'm expecting your approach will be 'carved in Russian stone'


If they are following the forum (are they?) I want to make one point clear:

I do not advocate routinely using the group procedures of the FDA!
On the contrary, all criteria for not using them are usually fulfilled (i.e., the simple model of pooled data can be used).

I did so in dozens of studies without ever getting a single (‼) deficiency letter. And my CRO was just a tiny one… Many thousands of BE studies were accepted by a multitude of agencies without asking for an ‘analysis’ of the group effect. :thumb up:
I would say that the EMA accepts without reservation that the group effect “cannot be reasonably assumed to have an effect on the response variable.”

❝ ❝ The nasty thing is that the Group-by-Treatment interaction test has low power (therefore, testing at the 0.1 level). You should expect a false positive rate at the level of the test …


❝ Could you please clarify this point? I saw many times the problem of power for Sequence term for simple model …


Senn1 (who always strongly argued against testing the sequence – or better unequal carryover – effect!) writes:

Because the power of the test is low, being based on between-patient difference, a high nominal level of significance (usually 10%) is used.

An interesting statement by the EMA2 concerning the treatment by covariate interaction:

The primary analysis should include only the covariates pre-specified in the protocol and no treatment by covariate interaction terms. […] Tests for interactions often lack statistical power and the absence of statistical evidence of an interaction is not evidence that there is no clinically relevant interaction. Conversely, an interaction cannot be considered as relevant on the sole basis of a significant test for interaction. Assessment of interaction terms based on statistical significance tests is therefore of little value [sic].

(my emphases)

❝ … and Group-by-Treatment interaction for FDA model I. Is it possible to prove that with sims? Or somebody did this work analytically?


Don’t know. I’m in contact with a Canadian CRO to collect empiric evidence (like D’Angelo et al.3 did for carryover). We will include only studies where groups were separated by just a couple of days and all of the FDA’s criteria for pooling were fulfilled. A great deal of work but seemingly ~⅒ of studies show a significant group-by-treatment interaction. :crying:

❝ I suspect a lot of fun with replicate designs. Your model specification with group […] works well even there, but it doesn't mean that this model is applicable for replicate designs (as we discussed elsewhere).


Yep.


  1. Senn S. Crossover Trials in Clinical Research. Chichester: Wiley; 2nd ed. 2002. p. 58.
  2. EMA. Guideline on adjustment for baseline covariates in clinical trials. London: 26 February 2015. EMA/CHMP/295050/2013.
  3. D’Angelo G, Potvin D, Turgeon J. Carryover effects in bioequivalence studies. J Biopharm Stat. 2001; 11(1–2): 35–43. doi:10.1081/BIP-100104196.

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