Deep shit [RSABE / ABEL]

posted by Mikalai  – Belarus, 2020-01-30 18:39  – Posting: # 21110
Views: 8,664

(edited by Mikalai on 2020-01-30 19:41)

Dear Helmut,

First of all, let's clarify a bit further. Why should we calculate CI twice if we do not plan control TIE.

» Read my last post again. And again. You do not know beforehand whether or not you will pass ABE. If not, you continue with the calculation CVwR and ABEL. If that happens, you will evaluate the data twice. That’s a textbook-example of multiplicity. Just by that the TIE will be \(1-(1-\alpha)^k=1-(1-0.05)^2=0.0975\). That’s not rocket science and already higher than with the usual framework, where we calculate the 90% CI only once. Add the the potential bias of CVwR and you are in deep shit. Excuse my French.

As I understand the formula of CI for ABE and RABE/ABEL is the same (2 sequence 4-period study). Or I am wrong? We calculate ABE CI. If Cmax is out of range, we than calculate the RR for ref drug and recalculate a new bioequivalence interval if the CV is higher than 30. And then we compare whether our old ABE CI is within the new interval. In this case, we calculate CI once. Am I wrong?

In terms of the decision tree, this approach is used. It is not unique. Multiple studies were accepted in Europe. It seems that there have been no complaints from European regulators.

I would not like to discuss whether we should or not control TIE in ABEL/RABE in this branch, because it may divert from the main topic. But I can explain my position. It seems that to control TIE we may have to change the alpha after getting results from the study sample. It potentially can reduce power and the only way to balance this is to recruit more subjects. The question is how many? One should take into consideration that ABEL/RABE trials are more challenging: high dropout rates (longer than usual BE trials) and riskier (more AE because of more blood and more drugs). If we can find a solution when we can increase the sample size slightly, then it is OK; otherwise, we may approach the sample size of a 2-period trial that basically invalidates the whole concept.

There is also another point. In Europe, we cannot expand limits for AUC and can for Cmax when it is safe. Why cannot we tolerate in this situation TIE that is higher than 5% (why 5%?), let's say 10%? Nothing is 'carved in the stone'. It appears that no drugs were withdrawn because of inflated TIE yet.

Also whether we have reliable methods to control TIE statistically on which regulators agree?

Finally, I disagree that pharmacovigilance is senseless. If it is done properly, it should and can pick up bad players (drugs and companies).

Best regards

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