Non-Superiority [Design Issues]

posted by Helmut Homepage – Vienna, Austria, 2022-07-25 16:37 (18 d 21:20 ago) – Posting: # 23176
Views: 378

Hi Dennis,

» The goal of an RCT is to compare the difference of complication rates of CVD surgery between two groups (group A and group B).
» The patients in group A will take medicine (traditionally treatment) and the patients in group B without taking medicine.
»
» Notably, we want to design the RCT as a non-inferiority trial. That is, the effect of complication rates of patients without taking medicine in group B is not worse than the patients in group A with take medicine.

Hhm.

» So, could we design the RCT as a non-inferiority trial?

The other way ’round.

Higher response is considered ‘better’ → Non-Inferiority
Lower response is considered ‘better’  → Non-Superiority

I know, that’s confusing. Some background in this article.

You hope that the complication rates in group A (with medicine) are lower than in group B (without medicine), right? Hence, that’s a Non-Superiority trial.

[image]
Note: x-axis in log-scale. \(\delta\) made up out of thin air.


» Moreover, how to defining the non-inferiority margin at the situation?

You don’t need only to define the non-superiority margin \(\small{\delta}\) but also assume the variability. No idea.
You are dealing with complication rates, which are \(\small{0\leq x \leq 1}\). As an aside, you can’t use the function sampleN.noninf() of the [image]-package PowerTOST, because it handles only lognormal \((\small{x\in\mathbb{R^{+}}}\)) or normal \((\small{-\infty\leq x+\infty}\)) distributed data. I’m sure, PASS has a fancy method for that.

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