Hello all,
Apologies in advance if this is too basic.
I am trying to calculate the sample size for a non-inferiority trial looking at intervention A vs. Standard of Care (SoC).
My primary endpoint is the incidence of patients achieving a given quality of life score (QoL), in a given period of time. The endpoint will be measured at 4-time points. Achieving that QoL score at any given time point and maintaining it at the following would be considered as a respondent.
Thus I'm assuming I should use the power two proportions option
The estimate for the intervention A is 0.54 and for the SoC is 0.48, power 95%, alpha 5%
Actually, I'm not sure if I should use the two estimates or 0.54 and assume a minimum difference of example 5% meaning that a difference bigger than 5% between the two groups means that one is superior to the other.

But if I use the previous and go with:

power twoproportions 0.54 0.48, test(chi2) power(0.95) alpha(0.05)

I get a sample size that "seems" too big: 3,604 (not accounting for drop out rate) compared with the literature that's more like around 200

How should I factor in the non-inferiority part in the calculation above? Should I use a completely different calculation?

Thank you