The statistical significance of 9902b is to be determined by the Cox regression analysis where we know the pooled 225 patients 9901/9902a p value was 0.0006 vs. the Kaplan Meier p value of 0.011, in spite of a placebo crossover rate somewhat in excess of 70% It would seem to me that if one assumes the same treatment effect and event rate for 9902b as for the pooled 9901 and 9902a enrollees, the target p value threshold of 0.05 would be reached with substantially fewer events than if a Kaplan Meier derived p value was needed. Would this be true?
It is absolutely true that Cox Regression increases the power of the trial. But it isn't a huge amount. My guesstimate(!!!) is by the equivalent of about 20% more patients. (I.e. in this case the 9902b power would be about the same with 600 patients without Cox Regression). Note also that while, on average, Cox Regression is more likely to help your trial than hurt it, there will certainly be instances where it causes a good p value to pop over 0.05.
trials were stopped short of full planned enrollment due to unexpectedly high treatment effects, a caveat being that statistical data can have spikes during the trial period and stopping a trial short of full enrollment could be precipitated by such a spike.
This would almost always (I know of no exceptions - but won't swear there are none) be only per pre specified trial protocol. I.e. Interim looks by the DMSB can only stop a trial for bad events unless it is pre-specified by the company that they are willing to spend some p on the interim look.
