Bioequivalence and Bioavailability Forum

Hi HS,

that's a complex area.
I can understand why regulators prefer to stay with things they know, like Pocock's 0.0294. But as you say, in the context of equivalence there is no proof that this value provides superior protection against inflated type I error. In my humble experience method C and B perform equally well by and large, possibly with a little advantage in terms of type I error to method B on the whole cf. table I in their first publication.
Or perhaps the logic is that if you use alphas of 0.05 first and 0.0294 next (= method C) then the overall type I error cannot be less than 0.05? This latter argument is flawed as the tables show.

We have an analogous situation with endpoints in pharmacodynamic asthma equivalence studies. The classical endpoint in asthma is FEV1 (a measure of lung function), but it turns out in practice that this endpoint is rather useless once we enter the field of equivalence. It took EU regulators more than 10 years to realise this after these facts were widely published (and trust me, in the name of self-criticism, it took me very long time to realise it myself).

On one hand we/they/someone need to be very careful when we/they/someone just blindly assume that what works with superiority will also work for equivalence. On the other hand, we should appreciate signals from regulators. They give us something we can base our actual plans on. And besides, I could be completely wrong as I usual am, in practice I think it is just as easy to plan a mehod B study as a method C study and their sample sizes appear equal also. I am happy with either.

I have a feeling the two-stage approaches are going to become more and more prominent for generic developers so there is certainly a need to have these debates.