Does anyone know if FDA will accept statistical analysis like a t-test to demonstrate that data from performance testing is substantially equivalent to the predicate device. For example, I might find that test results on the predicate device have a higher average value then the subject device. However, this difference might just be noise and not statistically significant. Could I claim with a certain confidence interval (say 95%) that the two are not different?
Thanks
Hello and welcome to the cove
There are actually 2 questions here:
1. Is the use of statistical techniques acceptable through the 510(k) review?
2. Can performance data be relied upon to substantiate equivalence with a predicate?
My answers:
1. As a general notion, yes, though you'd have to make sure your analysis is rigorous and your reasoning is robust (not sure that a t-test alone would make the case). There are a few professional statisticians around here and they may shed more light on the statistical aspect of your specific situation.
2. I would not take it as my first-choice route. Substantial equivalence, in crude terms, is determined by intended use and technological characteristics. I would resort to performance data only if there are technological differences and I was trying to argue that there are no new concerns regarding safety and effectiveness (even then, that would not be my preferred argument). To that end the data should, IMO, be extensive and the analysis pretty rigorous.
Cheers,
Ronen.