Interim Analysis & "Alpha Spending" in RCT's using Bayesian Analyses

[ADAlthousePhD]

@Adam_Omidpanah

This is an ethical issue too, of companies seeking statistical significance by just doing bigger and bigger and bigger trials. Sure if a drug is harmful you hopefully know sooner rather than later. But randomizing patients and waffling about seeking statistical significance (whether you are Bayesian or frequentist) means you are probabilistically denying patients access to the tried-and-true treatments with known risk profiles. For instance, in a study of bananas as analgesics, if there weren’t equipoise, I’d be mad and say give me the damn aspirin!

To me, I prefer the rigidity of formal stopping rules and alpha spending for those reasons.

Maybe I’m misinterpreting something here, but why do you believe that Bayesian designs don’t have formal stopping rules, or that they would lead to bigger and bigger trials?

I’ve cited this example a few times but the DAWN trial was fully Bayesian and had a series of pre-planned interim looks (it terminated at the first possible look for efficacy):

https://www.nejm.org/doi/full/10.1056/nejmoa1706442